Category: Knowledge

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How to Achieve Sub-Meter Positioning Accuracy using Smartphone

By Shahabuddin Amerudin

Achieving sub-meter positioning accuracy using a smartphone involves utilizing a combination of techniques, technologies, and tools that optimize the device’s built-in Global Navigation Satellite System (GNSS) capabilities. While smartphones typically offer less precise positioning compared to dedicated high-end GNSS receivers, advancements in hardware and software have enabled the enhancement of smartphone-based positioning accuracy. Here’s how to achieve sub-meter accuracy:

  1. Utilize Multiple GNSS Constellations: Modern smartphones support multiple GNSS constellations, such as GPS (USA), GLONASS (Russia), Galileo (Europe), and BeiDou (China). Enabling multiple constellations improves signal reception, reduces signal obstructions, and enhances accuracy.
  2. Enable High-Precision Modes: Some smartphones have high-precision or enhanced GNSS modes that combine signals from different constellations, resulting in better accuracy. Enable these modes if available in your smartphone’s settings.
  3. Augmentation Services: Utilize augmentation services like Wide Area Augmentation System (WAAS) in the USA or Satellite-Based Augmentation System (SBAS) in other regions. These services provide correction data to enhance positioning accuracy.
  4. External GNSS Receivers: Attach an external high-precision GNSS receiver to your smartphone. These receivers offer better accuracy than built-in smartphone GNSS modules, often achieving sub-meter accuracy.
  5. Real-Time Kinematic (RTK) and Differential GNSS (DGNSS): If you’re looking for even higher accuracy, consider using RTK or DGNSS solutions. These techniques involve receiving corrections from a base station to enhance positioning accuracy. Some companies offer RTK kits that can be connected to smartphones via Bluetooth.
  6. Post-Processing: Record raw GNSS data with your smartphone and use post-processing software to enhance accuracy later. This involves comparing the raw data to reference data and applying correction algorithms.
  7. Use External Antennas: External antennas, designed for improved GNSS signal reception, can significantly enhance the accuracy of smartphone positioning. These antennas reduce signal interference caused by the human body and other obstructions.
  8. Optimize Signal Conditions: Clear line-of-sight to the sky is crucial for accurate positioning. Avoid obstructions such as buildings, trees, and tall structures that can block or reflect GNSS signals.
  9. Avoid Interference: Interference from electronic devices can affect GNSS signals. Turn off Wi-Fi, Bluetooth, and other wireless connections when using GNSS for positioning.
  10. Calibrate Sensors: Some smartphones use sensor fusion techniques to improve positioning accuracy. Calibrating sensors like accelerometers and gyroscopes can enhance the accuracy of the GNSS system.
  11. Use GNSS Positioning Apps: There are several smartphone apps available that optimize GNSS performance. These apps provide real-time information about satellite visibility, signal quality, and accuracy.
  12. Combine with Other Sensors: Integrating data from other sensors like accelerometers, gyroscopes, and barometers can improve positioning accuracy, especially in areas with weak GNSS signal reception.

It’s important to note that achieving sub-meter accuracy with a smartphone might still have limitations, especially in challenging environments like urban canyons or densely vegetated areas. The choice of method depends on the specific requirements of your application and the level of accuracy needed. Always stay updated with the latest software updates and improvements for your smartphone’s GNSS capabilities.

Suggestion for Citation:
Amerudin, S. (2023). How to Achieve Sub-Meter Positioning Accuracy using Smartphone. [Online] Available at: https://people.utm.my/shahabuddin/?p=6614 (Accessed: 14 August 2023).
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Pioneering High-Accuracy GNSS Positioning with Low-Cost Receivers and Smartphones

By Shahabuddin Amerudin

Introduction

In the dynamic landscape of navigation and positioning technology, a remarkable breakthrough has emerged: the accessibility of high-accuracy GNSS positioning through low-cost receivers and smartphones (Marchi et al., 2022). As we delve deeper into this realm, we uncover a transformative era of precision that was once reserved for specialized equipment. This article explores the advancements, implications, and the potential for achieving centimeter-level accuracy through these affordable solutions.

Empowering Ubiquity

The narrative begins with the widespread adoption of low-cost GNSS technology. This innovation is now not only accessible but also adaptable with minimal investment. The EGSA GNSS Market Report (2019) offers compelling insights, forecasting an astonishing rise in the global installed base of GNSS devices – a leap from 6.4 billion in 2019 to a projected 9.6 billion by 2029. This growth mirrors the expanding annual GNSS receiver shipments, which are poised to escalate from 1.8 billion units in 2019 to an impressive 2.8 billion units by 2029. The surge in devices per capita from 0.8 to 1.1 globally signifies a world embracing the potential of accurate positioning.

Layers of Price Segmentation

The GNSS receiver landscape unfolds in distinct price tiers, characterized by their affordability and application scope, as delineated by EGSA (2019):

  1. Mass-market receivers – Priced below 5 €, these receivers dominate the market, constituting approximately 90 percent of shipments. Primarily catering to smartphones and wearables, they usher in precision for the masses.
  2. Rise receivers – Positioned in the price range of 5 € to 150 €, this segment showcases an impressive estimated annual growth rate of 6 percent. Their versatility spans unpowered assets, road infrastructure, and drone applications, fostering innovation in various sectors.
  3. High-end receivers – Anchoring the premium tier, these receivers command prices above 150 €. Despite accounting for less than 3 percent of total GNSS receiver shipments, they are the stalwarts of precision across diverse professional domains.

Elevating the GNSS Downstream Market

The burgeoning GNSS downstream market is fueled by revenues from mass-market and mid-end devices (<150 €), in tandem with augmentation services. Projections from EGSA (2019) underscore a monumental revenue surge, scaling from 150 € billion in 2019 to a staggering 325 € billion by 2029.

Redefining Smartphone and Low-Cost Receiver Performance

The heart of this transformation lies in the recalibration of performance benchmarks for low-cost GNSS solutions. High-end receivers, traditionally synonymous with dual signal frequencies (L1+L2), usher in centimeter-level accuracy and erode biases, underscoring their utility for precision-centric tasks. In contrast, the prevailing mass-market receivers, exemplified by the likes of u-blox, operate on a single signal frequency (L1), a configuration more sensitive to ionospheric perturbations. This sensitivity inherently influences performance, a challenge that modern advancements have confronted (Cina and Piras, 2015).

Eclipsing the Conventional

Smartphone Advancements: Modern smartphones have engineered a paradigm shift in the perception of attainable accuracy. The advent of u-blox and other single-frequency GNSS receivers for smartphones has shattered preconceived notions. Their capabilities, showcased vividly by Dabove et al. (2020), reverberate with astounding precision in static and kinematic positioning scenarios. The metamorphosis is anchored in an amalgamation of robust GNSS signals, infrastructural amplifications dedicated to GNSS positioning (spanning CORS, network, NRTK, and more), and an escalating interest from user communities and industry giants invested in top-tier positioning solutions (Dabove et al., 2020).

Expanding Horizons

Enhanced Positioning Strategies: The confluence of mass-market receivers with the offerings of GNSS permanent station networks yields a fertile ground for innovation. Cina and Piras (2015) exemplify this synergy with their groundbreaking work on precise and cost-effective landslide monitoring. This fusion elevates accuracy and affordability, driving progress across diverse applications.

The Unveiling of Precision

Comparative Performance Insights: Drawing a comparative lens between modern smartphones and u-blox GNSS receivers in real-time and post-processing contexts yields compelling revelations. The u-blox receiver consistently secures an upper hand, attaining precision levels within a remarkable 5 cm and accuracy honed to an exceptional 1 cm. Meanwhile, smartphone outcomes present slight disparities, often ranging in the order of meters due to the inherent noise within measurements (Dabove et al., 2020). Despite this, the potential for reliable positioning using these technologies remains undeniably promising. Enhancing this potential further lies the prospect of integrating advanced external antennas, propelling the realm of performance to even greater heights (Dabove et al., 2020).

Conclusion

The voyage into the world of high-accuracy GNSS positioning through low-cost receivers and smartphones has embarked upon a new trajectory. What was once a realm reserved for specialized devices has now been democratized, ensuring that centimeter-level accuracy is within reach for myriad applications. The implications ripple across sectors, reshaping possibilities and redefining precision.

References

Cina, A. and M. Piras (2015). Performance of low-cost GNSS receiver for landslides monitoring: Test and results, Geomatics, Natural Hazards and Risk, 6(5-7): 497-514. 

Dabove, P., V. Di Pietra and M. Piras (2020). GNSS Positioning Using Mobile Devices with the Android Operating System, ISPRS International Journal of Geo-Information, 9(4): 220. 

EGSA (European Global Navigation Satellite Systems Agency) (2019). GNSS Market Report. Issue 6; Retrieved from https://www.gsa.europa.eu/market/market-report; accessed on 20 April, 2020. 

Marchi, M. D., Diantini A. and Pappalardo, S.E. (2022). Drones and Geographical Information Technologies in Agroecology and Organic Farming. CRC Press.

Suggestion for Citation:
Amerudin, S. (2023). Pioneering High-Accuracy GNSS Positioning with Low-Cost Receivers and Smartphones. [Online] Available at: https://people.utm.my/shahabuddin/?p=6611 (Accessed: 14 August 2023).
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Unveiling Spatial Relationships: Predictive Applications of Regression Analysis

By Shahabuddin Amerudin

Introduction

In the realm of data analysis, regression analysis stands as a powerful tool that facilitates the exploration, understanding, and prediction of spatial relationships. By unraveling the intricate connections between variables, it provides insights into the factors driving observed spatial patterns. In this article, we delve into the fascinating world of regression analysis, focusing on its predictive applications through two distinct examples: the prediction of human deaths and the analysis of grave demand.

Regression analysis forms the cornerstone of modern statistical analysis, enabling us to move beyond mere correlation and into the realm of causation. As we journey through the depths of this method, we will explore its various techniques, from Ordinary Least Squares (OLS) to Geographically Weighted Regression (GWR), each contributing to our understanding of spatial phenomena. Join us as we uncover the mechanics, applications, and nuances of regression analysis, using human mortality and the demand for graves as our lenses into this dynamic field.

Among the array of regression techniques, Ordinary Least Squares (OLS) stands as the foundational technique, serving as the starting point for spatial regression analyses. OLS constructs a comprehensive model for the variable under scrutiny, such as the prediction of human deaths or the demand for graves, resulting in a single regression equation encapsulating that process.

Geographically Weighted Regression (GWR) is another influential spatial regression technique, finding increased adoption in geography and other fields. GWR generates localized models for the variable in focus. It involves fitting separate regression equations to each individual data point, capturing unique relationships within the immediate context. When employed effectively, these methods provide robust statistical tools for investigating and estimating linear relationships.

The nature of linear relationships is often either positive or negative. For instance, when local death rates rise with an increase in air pollution levels, it indicates a positive correlation. Similarly, if the demand for graves decreases as the population density rises, this signifies a negative relationship. Fig. 1 illustrates these positive, negative, and neutral relationships between variables.

Fig. 1: Basics of Correlation Analysis (Source: Kannan, M. and Singh, M. (2021))

While correlation analysis gauges the strength of relationships between two variables, regression analysis delves deeper, aiming to quantify the extent to which one or more variables potentially contribute to positive or negative changes in another.

Unveiling Ordinary Least Squares (OLS)

Consider the equation depicted in Fig. 2, where the dependent variable (y) embodies the process being predicted or understood, such as the prediction of human deaths or the estimation of grave demand. In this equation, the dependent variable takes its place on the left side of the equation. The process of regression begins with a set of known y values, which are used to construct and calibrate the regression model. These known y values are often referred to as observed values.

Fig. 2: Regression Equation (Source: Kannan, M. and Singh, M. (2021))

Independent/explanatory variables (x) are the driving forces behind modeling or predicting the values of the dependent variable. In the regression equation, these variables are positioned on the right side of the equation and are termed explanatory variables. The dependent variable responds to changes in these explanatory variables. For instance, predicting the demand for graves might involve variables such as population growth, cultural practices, urbanization levels, and mortality rates.

Regression coefficients (β) are calculated by the regression tool, representing the strength and direction of the relationship between each explanatory variable and the dependent variable. A positive relationship between grave demand and population growth, for instance, results in positive coefficients. Conversely, negative relationships yield negative coefficients. Strong relationships are reflected in large coefficients, while weak relationships manifest as coefficients closer to zero. The regression intercept (β0) signifies the expected value of the dependent variable when all independent variables are zero.

P-values indicate the probability that the coefficients for each independent variable are significantly different from zero. Small P-values indicate that a coefficient significantly contributes to the model, while coefficients near zero indicate minimal predictive impact unless supported by strong theoretical reasoning.

R2/R-Squared and Adjusted R-Squared gauge model performance. R-squared values range from 0 to 100%, with a value of 1.0 indicating a perfect fit. Adjusted R-Squared considers model complexity. Residuals measure the unexplained portion of the dependent variable.

Constructing a regression model entails iteratively selecting effective independent variables, utilising the regression tool to identify predictive variables, and refining the model for the optimal fit.

Navigating Geographically Weighted Regression (GWR)

Geographically Weighted Regression (GWR) offers a localized variant of linear regression, creating distinct equations for each data point by incorporating dependent and explanatory variables within a defined bandwidth. GWR’s efficacy hinges on user-defined parameters such as Kernel type, Bandwidth method, Distance, and Number of Neighbors.

For optimal results, GWR is most suited for datasets with numerous data points and is less effective for smaller datasets or multipoint data. Its outputs encompass a summary report, an Output feature class, and a diagnostic table. GWR is particularly useful when dealing with spatially varying relationships.

Practical Applications of Regression Analysis

Regression analysis finds application in diverse scenarios. For instance, it aids in modeling the prediction of human deaths to identify high-risk regions and comprehend the contributing factors. Analyzing property loss due to fatalities as influenced by factors like medical services access, response times, and population density is another application. In the realm of urban planning, regression helps dissect the demand for graves in relation to population growth, cultural dynamics, and mortality patterns.

Furthermore, regression analysis offers a means to test hypotheses. Investigating the correlation between urban development and grave demand, or exploring the relationship between healthcare access and human deaths, provides valuable insights. The tool also serves as a predictive instrument, helping anticipate trends in mortality rates or estimating the future demand for graves in regions without sufficient data.

In situations where interpolation falls short due to limited data, regression analysis provides a robust alternative, enabling prediction by modeling various phenomena.

Ultimately, regression analysis empowers researchers to uncover intricate relationships and harness predictive capabilities across a spectrum of scenarios, shedding light on the dynamics of human deaths and the demand for graves.

Conclusion

In the realm of data analysis, the power of regression analysis shines through as a beacon of insight. By bridging the gap between observation and prediction, it empowers us to decode the hidden narratives of spatial relationships. In this article, we embarked on a journey through the landscape of regression analysis, guided by the predictive applications within the context of human mortality and grave demand.

From the foundational principles of OLS to the nuanced approach of GWR, we explored the spectrum of techniques that allow us to unravel the mysteries of spatial phenomena. We witnessed how regression analysis can transform raw data into actionable insights, providing a roadmap to anticipate future trends and outcomes. By delving into the intricacies of our chosen examples, we gained a deeper appreciation for the role of regression analysis in shaping our understanding of the world around us.

As we conclude this exploration, we recognize that regression analysis is not merely a statistical tool, but a gateway to informed decision-making. Its applications span a multitude of disciplines, empowering researchers, policymakers, and analysts to make sense of complex relationships and harness the power of prediction. As we continue to unlock the potential of regression analysis, we stand at the cusp of a future where data-driven insights shape the world in unprecedented ways.

References

Kannan, M. and Singh, M. (2021). Geographical Information System and Crime Mapping. CRC Press: Taylor & Francis.

Suggestion for Citation:
Amerudin, S. (2023). Unveiling Spatial Relationships: Predictive Applications of Regression Analysis. [Online] Available at: https://people.utm.my/shahabuddin/?p=6605 (Accessed: 14 August 2023).
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The Evolution of Location Based Services: A Critical Review and Analysis

By Shahabuddin Amerudin

Abstract

Location Based Services (LBS) have undergone remarkable transformations since the publication of the seminal paper “The Development of Location Based Services in Malaysia” in 2009. This paper offers an extensive review and analysis of the original article in the context of recent advancements and trends in LBS technology. By critically examining the original paper’s content, relevance, and implications for today’s technological landscape, this review aims to provide a comprehensive understanding of the evolution of LBS.

1. Introduction

The original paper, published in 2009, explored the development of LBS in Malaysia, particularly in conjunction with the National Spatial Database Infrastructure (NSDI) and the Open Location Service (OpenLS) platform. However, the last decade has witnessed exponential technological growth, reshaping the landscape of LBS and expanding its potential far beyond the scope of the original paper. In this review, we delve into the progression of LBS, analyzing how it aligns with the paper’s objectives and uncovering new perspectives.

2. Scope and Relevance

The original paper was instrumental in laying the groundwork for understanding LBS within the context of the NSDI and OpenLS. While its contribution was valuable, it was limited by the technological constraints of its time. The scope primarily centered on technological integration and the potential benefits, leaving out considerations for challenges, drawbacks, and real-world implementations. Thus, this review aims to fill the gap by examining the paper’s content through a contemporary lens.

3. Technological Evolution

3.1 Standards and APIs

The paper underscored the importance of OpenLS and SOAP-based web services as foundations for LBS. Today, RESTful APIs have gained dominance due to their lightweight communication and compatibility with modern web technologies. Moreover, standards such as GeoJSON and GeoPackage have emerged as versatile options for geospatial data exchange, offering a departure from the XML-centric approach discussed in the original paper.

3.2 Mobile Application Development

While the original paper emphasized mobile phones as the primary platform for LBS, the smartphone revolution has redefined mobile application development. Advanced devices equipped with GPS, sensors, and augmented reality capabilities have paved the way for dedicated LBS applications that provide seamless and immersive user experiences.

3.3 Positioning Technologies

The paper’s recognition of accurate location determination remains pertinent. However, the advancement of positioning technologies, including Global Navigation Satellite Systems (GNSS), Wi-Fi-based positioning, and indoor positioning systems, has revolutionized location accuracy and enabled the development of hyper-localized LBS applications.

3.4 Data Privacy and Security

The paper briefly touched on privacy concerns. Subsequent to its publication, the landscape of data privacy and security has been fundamentally altered by regulations like GDPR. Modern LBS development places a heightened emphasis on protecting user data, warranting comprehensive discussions on privacy mechanisms and legal considerations.

4. Modern Considerations

4.1 Cloud Computing

An area that the original paper did not explore extensively is cloud computing. Cloud services have revolutionized LBS platforms, enabling scalable data storage, real-time data processing, and enhanced accessibility. The paper’s focus on SOAP-based web services could benefit from a broader discussion of cloud-based architectures.

4.2 Real-time Data and AI

Advancements in LBS extend to the integration of real-time data feeds and artificial intelligence (AI). AI-driven algorithms analyze location data to offer personalized recommendations, optimize routes, and predict user behavior. This dimension of LBS development has far-reaching implications for user engagement and satisfaction.

4.3 User Experience (UX)

Although the original paper mentioned user interface design, it did not delve into the critical aspect of user experience (UX). In the modern context, creating intuitive interfaces, employing responsive design principles, and prioritizing user-centric features are paramount for the success of LBS applications.

5. Conclusion

The original paper “The Development of Location Based Services in Malaysia” was instrumental in sparking discussions about LBS within the context of NSDI and OpenLS. However, the transformative technological advancements and shifting landscape of LBS since its publication necessitate a comprehensive reevaluation. While the original paper contributed historical insights into OpenLS and SOAP-based web services, a more encompassing analysis considering recent trends, standards, APIs, cloud computing, AI, privacy, and UX is essential to fully appreciate the evolution of LBS in contemporary contexts. As LBS continues to shape our digital world, understanding its journey is paramount for envisioning its future possibilities.

6. Reference

Ahmad Haris Abdul Halim, Sri Devi Ravana and Maizatul Akmar Ismail (2009). The Development of Location Based Services in Malaysia. [Online] Available at: https://www.geospatialworld.net/article/the-development-of-location-based-services-in-malaysia/ (Accessed:13 July 2023).

Suggestion for Citation:
Amerudin, S. (2023). The Evolution of Location Based Services: A Critical Review and Analysis. [Online] Available at: https://people.utm.my/shahabuddin/?p=6597 (Accessed: 14 August 2023).
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Exploring the Transformative Applications of Artificial Intelligence and Machine Learning in Geospatial Technology

By Shahabuddin Amerudin

Abstract

Geospatial technology has emerged as a pivotal discipline with far-reaching implications in numerous fields, including environmental science, geography, urban planning, and agriculture. The fusion of Artificial Intelligence (AI) and Machine Learning (ML) with geospatial analysis has ushered in an era of unprecedented advancements, elevating the capabilities of geospatial technology to new heights. This comprehensive academic article delves into the multifaceted applications of AI and ML in geospatial technology, elucidating their roles in land cover mapping, flood prediction and monitoring, precision agriculture, and traffic management. By understanding these innovative applications, readers can contribute meaningfully to the evolution of geospatial technology and address complex challenges in environmental conservation and resource management effectively.

1. Introduction

Geospatial technology has evolved exponentially over the years, owing to advancements in data collection, spatial analysis, and visualization techniques. The convergence of AI and ML technologies with geospatial analysis has opened new vistas of opportunities in diverse domains. In this article, we embark on an exploration of the myriad applications of AI and ML in geospatial technology, delving into their potential transformative impact on addressing critical environmental challenges.

2. Unpacking AI and ML in Geospatial Technology

AI serves as the hallmark of human-like intelligence in machines, endowing them with the ability to think, reason, and learn. ML, a subfield of AI, empowers machines to acquire knowledge from experience and adapt without explicit programming. The integration of AI and ML with geospatial technology optimizes decision-making processes and augments the efficiency of geospatial analysis.

3. Precision Land Cover Mapping

Land cover mapping, a fundamental aspect of geospatial analysis, involves identifying and categorizing different land cover types within a specific geographic area. Traditionally, land cover mapping relied on the manual interpretation of satellite imagery, making it time-consuming and laborious. AI and ML have revolutionized this process, enabling automated analysis of vast amounts of satellite imagery data. AI algorithms effectively discern forests, grasslands, urban areas, and other land cover types, while ML algorithms continuously refine their accuracy through machine learning models (Fu et al., 2021).

4. Advancing Flood Prediction and Monitoring

Floods pose significant threats to lives and property, necessitating accurate prediction and real-time monitoring. AI and ML have emerged as powerful tools in this domain. By leveraging historical flood data, weather patterns, and other relevant factors, AI algorithms can forecast the likelihood of floods in specific areas. Moreover, geospatial technology facilitates real-time monitoring, providing crucial information to emergency responders and the public during flood events (Pathirana et al., 2018).

5. Precision Agriculture: Optimizing Crop Management

Precision agriculture revolutionizes crop management by utilizing data and technology to optimize yields, reduce waste, and enhance resource efficiency. AI and ML play pivotal roles in this transformative agricultural approach. AI algorithms proficiently analyze satellite imagery and other data sources, enabling the assessment of crop health, identification of pests and diseases, and yield predictions. ML algorithms further enhance precision agriculture by continuously learning from data to improve prediction accuracy (Barbedo, 2019).

6. Intelligent Traffic Management

Traffic management is a critical aspect of urban planning and transportation. AI and ML have emerged as valuable assets in optimizing traffic flow, reducing congestion, and improving safety. By analyzing traffic patterns, road networks, and other relevant data, AI algorithms efficiently develop models for intelligent traffic management. The ML component of these algorithms refines predictions and recommendations over time based on the continuous influx of new data. Real-time traffic monitoring facilitated by geospatial technology ensures timely information dissemination to drivers and transportation authorities, thus contributing to more efficient traffic management (Tariq et al., 2020).

7. Conclusion

The fusion of AI and ML with geospatial technology has heralded an era of transformative applications, fostering innovation and problem-solving across diverse domains. As undergraduate students endeavor to contribute to the evolution of geospatial technology, a comprehensive understanding of these technologies’ applications is vital. By harnessing the power of AI and ML, readers can pioneer innovative solutions, addressing complex environmental and resource management challenges and shaping a sustainable future for the field of geospatial technology.

References

Barbedo, J. G. A. (2019). Machine learning techniques for crop yield prediction and climate change impact assessment in agriculture. Computers and Electronics in Agriculture, 163, 104859.

Fu, J., Ma, J., Wang, J., & Chang, C. (2021). A deep learning framework for automatic land cover mapping using aerial imagery. Remote Sensing of Environment, 263, 112-126.

Pathirana, A., Perera, B. J. C., & Marpu, P. R. (2018). A review of artificial intelligence-based models for flood inundation prediction. Journal of Hydrology, 557, 631-642.

Tariq, U., Ali, A., Abbas, S., Abbas, F., & Imran, A. S. (2020). Urban traffic management using machine learning: A comprehensive review. Sustainable Cities and Society, 61, 102329.

Suggestion for Citation:
Amerudin, S. (2023). Exploring the Transformative Applications of Artificial Intelligence and Machine Learning in Geospatial Technology. [Online] Available at: https://people.utm.my/shahabuddin/?p=6595 (Accessed: 31 July 2023).
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Emerging Trends in GIS Software Systems: The Impact of Artificial Intelligence on Environmental Conservation and Resource Management

By Shahabuddin Amerudin

Abstract

Geographic Information Systems (GIS) play a vital role in environmental conservation and natural resource management. In recent years, the integration of Artificial Intelligence (AI) into GIS software has led to revolutionary advancements, enhancing the capabilities and intelligence of GIS applications. This article explores the emerging trends in GIS software systems that leverage AI technologies, focusing on various aspects such as interaction methods, data visualization, predictive modelling, spatial analysis, real-time decision-making, autonomous data collection, data fusion, precision agriculture, and environmental risk assessment. These trends are transforming the way government agencies and organizations address complex environmental challenges, promoting sustainable practices and fostering more efficient resource management.

1. Introduction

Geographic Information Systems (GIS) have emerged as powerful tools for environmental conservation and natural resource management, facilitating data analysis, spatial visualization, and informed decision-making. Recent advancements in Artificial Intelligence (AI) are revolutionizing GIS software, expanding its functionalities and enabling more sophisticated applications. This article aims to explore the emerging trends in GIS software systems, showcasing how the integration of AI is enhancing environmental conservation and resource management efforts.

2. Integration of Artificial Intelligence in GIS

AI integration into GIS software has unlocked a plethora of capabilities, including machine learning, pattern recognition, and natural language processing. These AI-driven functionalities elevate GIS systems from mere data analyzers to intelligent decision-making platforms, capable of processing vast datasets and extracting meaningful insights (Jones et al., 2019).

3. Enhancing User Experience: Interaction Methods

The adoption of intuitive and natural interaction methods, such as voice commands and gesture-based controls, significantly improves GIS user experience, especially in field applications. Researchers have found that integrating voice recognition into GIS enables users to perform complex tasks hands-free, making GIS tools more user-friendly and accessible (Smith et al., 2021).

4. Unleashing Insights: Data Visualization Techniques

AI-powered data visualization tools have proven effective in automatically generating insightful and interactive visualizations. By leveraging algorithms and AI, GIS users can gain deeper insights from complex environmental data, facilitating better understanding and communication of spatial information (Chen et al., 2020).

5. Proactive Planning: Predictive Modelling

AI-based predictive modelling empowers agencies to forecast environmental changes, species distributions, and potential resource impacts. These forecasts enable proactive planning and conservation efforts, providing decision-makers with valuable insights for sustainable management strategies (Brown et al., 2018).

6. Efficient Spatial Analysis

AI-enhanced spatial analysis algorithms have significantly improved the efficiency of processing large datasets. Researchers have reported that AI-driven spatial analysis allows for faster extraction of meaningful patterns and identification of spatial relationships, enhancing the accuracy of environmental monitoring and management (Wang et al., 2019).

7. Real-time Decision-making

AI algorithms process incoming data in real-time, allowing GIS systems to provide instant insights during critical situations, such as disaster response or conservation emergencies. Real-time decision-making is crucial in ensuring effective environmental interventions and timely resource allocation (Lee et al., 2020).

8. Autonomy in Data Collection

AI-driven GIS applications can autonomously collect and process geospatial data through drones, satellites, or Internet of Things (IoT) devices. Continuous and real-time environmental monitoring facilitated by AI technologies enhances data accuracy and supports dynamic ecosystems’ adaptive management (Gao et al., 2019).

9. Comprehensive Data Fusion and Integration

AI facilitates data fusion from diverse sources, such as satellite imagery, social media, and sensor data. The comprehensive view offered by such integration supports holistic decision-making in resource management, as researchers have shown in studies on integrated environmental data platforms (Diaz-Viloria et al., 2018).

10. Sustainable Farming: Precision Agriculture and Natural Resource Management

AI-driven GIS solutions enable precision agriculture, optimizing resource utilization, crop yield prediction, and water management. Researchers have demonstrated that AI-driven precision agriculture practices promote sustainable farming, minimizing resource waste and environmental impacts (Yang et al., 2019).

11. Environmental Risk Assessment

AI-powered GIS systems analyze potential hazards, vulnerable areas, and the impact of climate change, supporting better preparedness and mitigation strategies. Researchers have highlighted the importance of AI-driven risk assessment models in managing environmental risks and guiding conservation efforts (Ruan et al., 2021).

12. Conclusion

The integration of AI technologies into GIS software systems has unlocked significant potential in the field of environmental conservation and natural resource management. The emerging trends presented in this article are reshaping GIS applications, allowing for more informed decision-making, precise environmental monitoring, and sustainable resource management. As AI continues to evolve, GIS software will play an increasingly pivotal role in addressing environmental challenges and promoting a more sustainable future.

References

Brown, G., McDonald, R., & van Riper, C. J. (2018). Predictive modeling for environmental decision support: Advances, challenges, and opportunities. Journal of Environmental Management, 205, 42-52.

Chen, S., He, L., & Xu, X. (2020). An artificial intelligence-based method for environmental data visualization. Journal of Visual Communication and Image Representation, 69, 102815.

Diaz-Viloria, N., Aznar-Sánchez, J. A., Contreras-Medina, L. M., & Jiménez-Martínez, R. (2018). A comprehensive framework for environmental data fusion. Information Fusion, 39, 122-132.

Gao, P., Zhu, L., & Chen, Y. (2019). A review of autonomous data collection technologies in environmental monitoring. Environmental Monitoring and Assessment, 191(9), 569.

Jones, D., Durfey, P., & Wing, M. G. (2019). Geospatial decision support system based on artificial intelligence for local authorities. The Journal of Urban Technology, 26(4), 97-112.

Lee, Y., Kim, H., Kim, J., & Han, S. (2020). Real-time decision support system for environmental management using AI. Journal of Environmental Management, 270, 110989.

Ruan, J., Xu, Y., He, Z., & Sun, X. (2021). AI-based environmental risk assessment for conservation planning. Science of the Total Environment, 759, 143606.

Smith, A. J., Gómez, A. E., & Chow-Fraser, P. (2021). Voice-enabled GIS for improved accessibility and efficiency. Transactions in GIS, 25(2), 531-548.

Wang, L., Wang, W., Hu, M., & Wu, Z. (2019). An AI-driven spatial analysis method for environmental monitoring. Environmental Science and Pollution Research, 26(31), 31843-31853.

Yang, H., Huang, X., Cheng, B., & Lang, Y. (2019). AI-driven precision agriculture for sustainable resource management. Resources, Conservation and Recycling, 144, 291-299.

Suggestion for Citation:
Amerudin, S. (2023). Emerging Trends in GIS Software Systems: The Impact of Artificial Intelligence on Environmental Conservation and Resource Management. [Online] Available at: https://people.utm.my/shahabuddin/?p=6593 (Accessed: 31 July 2023).
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The Evolution of GIS Software 

By Shahabuddin Amerudin

The evolution of GIS software has been marked by key milestones and advancements that have shaped the current landscape of geospatial technology:

1. Early Beginnings (1960s-1970s):

  • GIS roots can be traced back to the 1960s when early computer systems were used for basic spatial analysis. Early GIS focused on storing and managing spatial data with minimal analytical capabilities.

2. Mainframe and Early Desktop GIS (1980s-1990s):

  • In the 1980s, the introduction of mainframe GIS systems allowed larger-scale data processing and analysis. The 1990s saw the emergence of desktop GIS software with more user-friendly interfaces and analytical functionalities.

3. Introduction of Vector Data Models:

  • The adoption of vector data models in the 1980s facilitated the representation of geographic features as points, lines, and polygons, enabling more precise spatial analysis.

4. Integration of Remote Sensing and GPS (1990s):

  • The integration of remote sensing and GPS technologies into GIS software expanded the range of available geospatial data, allowing for more accurate mapping and monitoring of environmental changes.

5. Web-Based GIS (Late 1990s-2000s):

  • The late 1990s saw the rise of web-based GIS, enabling data sharing and interactive mapping through web browsers. Web mapping applications revolutionized data accessibility and public engagement.

6. Open Source GIS (2000s):

  • The early 2000s witnessed the rise of open-source GIS software, such as QGIS and GRASS GIS, which promoted collaboration, customization, and cost-effectiveness in GIS implementation.

7. Mobile GIS and Location-Based Services (2000s-2010s):

  • The proliferation of smartphones and mobile devices led to the development of mobile GIS applications, empowering field data collection and location-based services.

8. Cloud-Based GIS (2010s):

  • The 2010s brought cloud-based GIS platforms that allowed organizations to store, analyze, and share geospatial data through the cloud, enhancing scalability, accessibility, and collaboration.

9. Big Data and Spatial Data Science (2010s):

  • Advancements in big data and spatial data science enabled the processing and analysis of massive geospatial datasets, leading to more sophisticated spatial analytics and decision-making.

10. Integration of AI and Machine Learning (Present):

  • Present-day GIS software leverages AI and machine learning algorithms to automate spatial analysis, pattern recognition, and predictive modelling, opening new possibilities for advanced geospatial applications.

The evolution of GIS software has witnessed significant milestones and technological advancements, transforming the field of geospatial technology. From basic data storage to sophisticated analytics and real-time web-based applications, GIS software has become an indispensable tool for environmental conservation, resource management, urban planning, disaster response, and various other disciplines. The continuous innovation in GIS software continues to shape the future of geospatial technology, enabling data-driven decision-making and sustainable development.

Suggestion for Citation:
Amerudin, S. (2023). The Evolution of GIS Software. [Online] Available at: https://people.utm.my/shahabuddin/?p=6591 (Accessed: 31 July 2023).
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Sub-Meter Accuracy in Consumer Smartphones: Advancements and Challenges in GNSS Positioning

By Shahabuddin Amerudin

Source: https://blog.junipersys.com

Sub-meter accuracy in the context of GNSS (Global Navigation Satellite System) refers to the capability of a receiver to determine its position with an accuracy of less than one meter, typically in the range of centimeters or decimeters. This level of accuracy is highly desirable for various applications, including augmented reality, precise navigation, surveying, agriculture, and other location-based services where high precision is crucial.

To achieve sub-meter accuracy, GNSS receivers need access to highly accurate and precise satellite positioning data. Traditional consumer-grade GNSS receivers, such as those found in smartphones, typically provide accuracy in the range of a few meters, which is sufficient for many general navigation purposes but not suitable for applications requiring high precision.

Several factors contribute to the challenge of achieving sub-meter accuracy in consumer smartphones:

  1. Limited Observables: Consumer smartphones typically have limited access to the satellite constellations and signals. For instance, they may receive only L1 (single frequency) signals from GPS and Galileo constellations, while multi-frequency access is limited to only certain satellites.
  2. Noisy Environment: Smartphones have compact designs, and their GNSS antennas are often shared with other communication hardware like Bluetooth and Wi-Fi receivers. This setup leads to noisy electromagnetic interference, reducing the signal quality from GNSS satellites.
  3. Signal Quality and Multipath: The quality of GNSS signals received by smartphones can be affected by factors like multipath, where the signals bounce off surrounding objects, causing inaccuracies in the position calculation.
  4. Real-Time Constraints: Achieving sub-meter accuracy in real-time is more challenging than post-processing data after collection. Real-time positioning requires fast and efficient algorithms that can handle the limited observations and noisy environment of smartphones.

To address these challenges and achieve sub-meter accuracy, researchers and developers have been working on innovative methodologies and algorithms. Some of the techniques used to improve accuracy in consumer smartphones include:

  1. Precise Point Positioning (PPP): PPP is a GNSS positioning technique that can achieve high accuracy by using advanced mathematical models to account for ionospheric and tropospheric errors. By combining dual-frequency measurements when available and using real-time ionospheric models, PPP can enhance the accuracy of single-frequency observations.
  2. SFDF Combination: Single-Frequency Dual-Frequency (SFDF) combination is a method to combine L1 (single frequency) and L5 (dual-frequency) observations in smartphones. This technique compensates for the lack of dual-frequency measurements in most satellites, improving the accuracy of positioning results.
  3. Signal-to-Noise Ratio (SNR) Weighting: SNR is a measure of the signal quality received by the smartphone’s GNSS receiver. Applying SNR weighting in the positioning algorithm can help filter out poor-quality measurements and improve the overall accuracy.
  4. Pre-processing Filters: Implementing pre-processing filters to remove poor-quality observations caused by multipath or other interference can enhance the accuracy of the final position solution.
  5. Real-Time Corrections: Accessing real-time corrections from GNSS augmentation systems or base stations can significantly improve the accuracy of the positioning results.

Despite the challenges, ongoing research and advancements in GNSS technology have made it possible to achieve sub-meter accuracy on consumer smartphones. By implementing sophisticated algorithms, utilizing real-time corrections, and optimizing the use of available observations, smartphone users can experience improved accuracy, making it suitable for various high-precision applications.

Suggestion for Citation:
Amerudin, S. (2023). Sub-Meter Accuracy in Consumer Smartphones: Advancements and Challenges in GNSS Positioning. [Online] Available at: https://people.utm.my/shahabuddin/?p=6588 (Accessed: 31 July 2023).
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A Review: Accuracy for the Masses: Real-Time Sub-Meter in a Consumer Receiver?

By Shahabuddin Amerudin

Accuracy for the Masses: Real-Time Sub-Meter in a Consumer Receiver?

Authors: Joshua Critchley-Marrows, Marco Fortunato and William Roberts

Publication Date: April 6, 2020

The article discusses a new methodology aimed at achieving sub-meter Global Navigation Satellite System (GNSS) accuracies in consumer devices such as smartphones. The goal is to enable applications like augmented reality and visually impaired navigation to function with higher precision. The article explores the challenges of achieving high accuracy in mass-market GNSS receivers, especially in the context of real-time positioning. It also introduces an alternative approach to Precise Point Positioning (PPP) to improve accuracy in challenging receiver environments.

Key Points:

  1. Challenges in Mass-Market GNSS Receivers: Mass-market GNSS receivers in consumer devices have limitations such as limited observation data from satellite constellations and restricted access to multi-frequency measurements. Additionally, the design of smartphones, with shared antennas and other communication hardware, can introduce noise and interference, affecting positioning accuracy. As a result, the typical accuracy achievable in ideal conditions is a few meters.
  2. Sub-Meter Accuracy Goals: The article sets a benchmark of achieving 50 cm accuracy for smartphone positioning due to the increasing demand for location-based apps requiring higher precision.
  3. The FLAMINGO Initiative: The methodology presented in the article is developed as part of the FLAMINGO initiative, which enables real-time PPP and Real-Time Kinematic (RTK) GNSS positioning on smartphones. The FLAMINGO service has achieved sub-meter positioning accuracies in real-time, but it relies on base station infrastructure within approximately 30 km of the user.
  4. Methodology Overview: The proposed methodology involves modifications to traditional GNSS processing. It includes a preprocessing stage to remove poor GNSS observables, a combination of single-frequency PPP with dual-frequency ionospheric-free combination, and signal-to-noise ratio and elevation-based noise weighting.
  5. Poor-Measurement Rejection: The preprocessing stage filters out poor GNSS observables using three detection strategies: Code-Minus-Carrier, Phase Range Rate, and Pseudorange Rate. These strategies identify and remove observations with errors caused by factors like multipath or cycle slips.
  6. SFDF Combination: To compensate for the mix of single-frequency and dual-frequency observations from smartphones or mass-market receivers, the methodology proposes the use of SFDF (Single Frequency, Dual Frequency) combination. This combination reduces error terms and improves vertical accuracy.
  7. Model Weighting: The methodology uses both elevation and signal-to-noise ratio (SNR) as weights in the GNSS processing algorithm. The combination of these weights enhances the precision of the positioning solution.
  8. Implementation and Test Results: The methodology is tested on real-time receiver trials, and the results are compared to an idealized post-processing scenario. The real-time solutions show less accuracy compared to the post-processed ideal case due to the challenges and limitations of smartphone environments. The SFDF model and SNR weighting show improvements in vertical accuracy.

Conclusion

The article presents a novel methodology to achieve sub-meter GNSS accuracies in consumer devices like smartphones. While the ideal case demonstrates high accuracy in post-processing, real-time implementation faces challenges due to the complex and noisy environment of smartphones. Nevertheless, the methodology shows promise for improving vertical accuracy and provides valuable insights for future GNSS research and development in consumer applications. Achieving sub-meter accurate PPP in real-time remains a goal with significant potential benefits.

Suggestion for Citation:
Amerudin, S. (2023). A Review: Accuracy for the Masses: Real-Time Sub-Meter in a Consumer Receiver? [Online] Available at: https://people.utm.my/shahabuddin/?p=6586 (Accessed: 31 July 2023).
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Review Article: World Sees Record Heat Waves

Source: https://www.statista.com/chart/27403/global-heat-waves/

The article by Anna Fleck discusses global heatwaves and presents preliminary data from the World Meteorological Organization (WMO) regarding recent temperature records. It highlights that the world has just experienced the hottest week on record (average July 3-9) following the hottest June on record.

The article provides examples of temperature records being broken in various regions around the world. In South Asia, an exceptional heatwave occurred in April and May 2023, resulting in national temperature records being broken in Thailand, Vietnam, and Laos. Australia and Uruguay also matched their national temperature records last year, while the UK saw its all-time high temperature surpassing 40°C in July 2022.

The article further mentions peak temperatures recorded in Canada, Turkey, Spain, and Italy during the summer of 2021, which was described as one of the hottest on Earth. The temperature recorded in Syracuse, Italy, at 48.8°C, is reported to be the highest ever measured in Europe, pending certification by the WMO. Additionally, it highlights temperature records in Antarctica, France, Belgium, and Germany in recent years.

The article concludes by mentioning the highest officially recorded temperature on Earth, which occurred in Furnace Creek, California, in 1913, reaching 56.7°C. This record still stands.

Overall, the article provides a brief overview of recent global heatwaves and records broken in various countries. It highlights the severity and frequency of extreme heat events occurring in different regions around the world.

Source: https://www.statista.com/chart/27403/global-heat-waves/

Suggestion for Citation:
Amerudin, S. (2023). Review Article: World Sees Record Heat Waves. [Online] Available at: https://people.utm.my/shahabuddin/?p=6542 (Accessed: 13 July 2023).
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Understanding Location Accuracy Requirements in Various Applications

By Shahabuddin Amerudin

Introduction

Location accuracy plays a vital role in numerous applications, enabling precise positioning, navigation, and tailored experiences. Different applications have varying location accuracy requirements based on their specific use cases and objectives. In this article, we explore a range of applications and their location accuracy needs, spanning from high accuracy requirements in the millimeter range to general accuracy needs within a few meters.

  1. Surveying and Mapping Applications (mm to cm accuracy): Applications used for professional surveying, cartography, or mapping often require extremely high accuracy. These applications demand location accuracy in the millimeter to centimeter range to ensure precise delineation of boundaries, topographical mapping, and engineering projects.
  2. Autonomous Vehicles (cm accuracy): Autonomous vehicles, including self-driving cars, require reliable and accurate positioning for safe navigation. Location accuracy within the centimeter range is necessary to ensure precise localization and path planning, enabling vehicles to detect obstacles and make accurate driving decisions.
  3. Augmented Reality (AR) Applications (cm to dm accuracy): AR applications that overlay virtual content on the real world require moderate accuracy for proper alignment. Location accuracy within the centimeter to decimeter range is typically sufficient to ensure virtual objects are accurately placed and aligned with the physical environment.
  4. Precision Agriculture (dm accuracy): Applications used in precision agriculture, such as crop monitoring or autonomous farming, benefit from location accuracy within the decimeter range. This level of accuracy allows for precise mapping of field conditions, targeted application of resources, and monitoring of crop health.
  5. Construction and Building Information Modeling (BIM) (dm to m accuracy): Construction and BIM applications require accurate positioning for planning and coordination. Location accuracy within the decimeter to meter range helps ensure accurate alignment of building elements, clash detection, and accurate material takeoffs.
  6. Emergency Services (m accuracy): Emergency services applications, including emergency response and disaster management systems, require location accuracy within a few meters. This level of accuracy is critical for quickly and accurately identifying the location of emergencies, coordinating response efforts, and providing timely assistance.
  7. Navigation and Routing Applications (m accuracy): Navigation and routing applications, such as turn-by-turn navigation or route planning, generally require accuracy within a few meters. This level of accuracy enables accurate guidance, real-time traffic updates, and reliable estimated time of arrival (ETA) calculations.
  8. Geolocation-Based Services (m accuracy): Geolocation-based services, including finding nearby points of interest or location-based recommendations, typically require accuracy within a few meters. This level of accuracy ensures relevant information is provided based on the user’s proximity to specific locations.
  9. Fitness and Activity Tracking Apps (m accuracy): Fitness and activity tracking apps, such as running or cycling trackers, often require accuracy within a few meters. This level of accuracy is sufficient for mapping and tracking user movements during various activities.
  10. Social Media Check-In Apps (m accuracy): Social media check-in apps rely on accurate location information to tag user posts with their current location. Accuracy within a few meters ensures that users can accurately share their location and connect with others nearby.
  11. Weather and Environmental Monitoring (m accuracy): Weather and environmental monitoring apps provide localized weather forecasts or track environmental conditions. Accuracy within a few meters helps provide accurate and location-specific weather information.
  12. Public Transportation Apps (tens of meters accuracy): Public transportation apps that provide information on bus or train schedules typically require accuracy within tens of meters. This level of accuracy ensures accurate departure and arrival information, and helps users locate nearby transit stops or stations.
  13. Real Estate and Property Apps (tens of meters accuracy): Real estate and property apps, including property search or rental platforms, benefit from accuracy within tens of meters. This level of accuracy helps users find properties in their desired location or explore nearby amenities.
  14. Location-Based Gaming Apps (tens of meters accuracy): Location-based gaming apps, such as treasure hunts or location-based challenges, generally require accuracy within tens of meters. This level of accuracy allows for precise placement of in-game elements and enhances the gaming experience by aligning virtual content with the user’s physical surroundings. However, in some cases, the required accuracy is typically within a few meters.
  15. Social Networking and Local Recommendations (tens to hundreds of meters accuracy): Social networking apps and local recommendation platforms often rely on accuracy within tens to hundreds of meters. This level of accuracy provides a general idea of the user’s location, allowing for location-based social interactions and delivering relevant recommendations based on nearby points of interest.
  16. Outdoor Recreation and Adventure Apps (tens to hundreds of meters accuracy): Outdoor recreation and adventure apps, such as hiking or trail mapping applications, generally require accuracy within tens to hundreds of meters. This level of accuracy allows users to navigate trails, find landmarks, and plan their outdoor activities effectively. However, in some cases, the required accuracy is typically within a few meters.
  17. Delivery and Logistics Apps (tens to hundreds of meters accuracy): Delivery and logistics apps, including package tracking or fleet management systems, typically require accuracy within tens to hundreds of meters. This level of accuracy enables efficient route planning, real-time tracking of shipments or vehicles, and effective management of logistics operations. However, in some cases, the required accuracy is typically within a few meters.
  18. Field Data Collection and Surveys (tens to hundreds of meters accuracy): Field data collection apps used for surveys, research, or asset management purposes generally require accuracy within tens to hundreds of meters. This level of accuracy allows for effective mapping and data collection, providing valuable insights for various industries and research projects. However, in some cases, the required accuracy is typically within a few meters.
  19. Location-Based Attendance and Access Control (tens to hundreds of meters accuracy): Applications used for attendance tracking, access control systems, or workforce management often require accuracy within tens to hundreds of meters. This level of accuracy allows for efficient monitoring of personnel and assets within designated areas.
  20. IoT (Internet of Things) and Asset Tracking (tens to hundreds of meters accuracy): IoT applications and asset tracking systems that monitor the location of objects or assets typically require accuracy within tens to hundreds of meters. This level of accuracy is sufficient for general tracking and management of assets across various industries. However, in some cases, the required accuracy is typically within a few meters.

Conclusion

It’s important to note that these accuracy ranges are general guidelines and can vary depending on specific application requirements and user expectations. Additionally, advancements in technology, such as the availability of higher-quality GNSS receivers or the integration of sensor fusion techniques, may further improve location accuracy in various applications.

Developers should consider the specific needs of their applications and strike a balance between the required accuracy and the available resources and technologies. It’s also important to inform users about the expected accuracy level and manage their expectations to ensure a satisfactory user experience.

Advancements in technology and the ongoing development of positioning techniques are expected to further improve location accuracy across various applications, allowing for more precise and tailored experiences in the future.

Suggestion for Citation:
Amerudin, S. (2023). Understanding Location Accuracy Requirements in Various Applications. [Online] Available at: https://people.utm.my/shahabuddin/?p=6530 (Accessed: 6 July 2023).
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Understanding Location Accuracy in Consumer Smartphones

By Shahabuddin Amerudin

Introduction

Consumer smartphones have become integral to our daily lives, offering a wide range of features and functionalities, including location-based services. The accuracy of location information provided by smartphones is crucial for navigation, mapping, and various location-dependent applications. In this article, we explore the general capabilities of consumer smartphones in achieving location accuracy and the factors that influence it.

GPS Technology and Accuracy

Global Positioning System (GPS) is a widely used positioning technology in smartphones. With high-quality GPS receivers, smartphones can achieve location accuracy within a few meters under ideal conditions. GPS relies on signals from satellites orbiting the Earth to determine precise location coordinates.

GNSS Capabilities

Many modern smartphones support multiple Global Navigation Satellite Systems (GNSS), including GPS, GLONASS, Galileo, and BeiDou. GNSS-capable smartphones have the advantage of accessing signals from multiple satellite constellations, enhancing location accuracy. By leveraging a combination of satellite signals, smartphones can achieve improved accuracy and reliability, particularly in challenging environments.

Assisted Positioning Techniques

Smartphones often employ assisted positioning techniques such as Assisted GPS (A-GPS) or Assisted GLONASS (A-GLONASS). These techniques leverage cellular networks or Wi-Fi data to assist in determining the user’s location. By utilizing additional data sources, smartphones can enhance positioning speed and accuracy, especially in urban environments or when GPS signals are weak or obstructed.

Sensor Fusion for Improved Accuracy

Sensor fusion technologies play a crucial role in enhancing location accuracy. By integrating GPS data with information from other sensors like accelerometers, gyroscopes, or magnetometers, smartphones can improve accuracy and stability. Sensor fusion allows smartphones to compensate for temporary signal loss, obstructions, or other limitations, resulting in more reliable location information.

Network-Based Positioning

In addition to satellite-based positioning, smartphones can utilize network-based methods such as Wi-Fi positioning or cell tower triangulation. When GPS signals are weak or unavailable, these techniques estimate the user’s location based on Wi-Fi network information or signals from nearby cell towers. While network-based positioning provides coarser accuracy within tens to hundreds of meters, it serves as a valuable backup when satellite signals are limited.

Factors Affecting Location Accuracy

Location accuracy in smartphones can vary due to various external factors. The availability of satellite signals, environmental conditions, signal interference, and the specific hardware and software capabilities of the smartphone all influence accuracy. Additionally, smartphone manufacturers may employ proprietary technologies or algorithms to optimize location accuracy in their devices, resulting in varying performance across different models.

Determining Location Accuracy

To determine the precise location accuracy of a particular smartphone model, it is best to refer to the specifications provided by the manufacturer. However, independent tests and reviews that evaluate the device’s performance in real-world scenarios can provide valuable insights. These tests assess factors such as accuracy under different conditions, signal acquisition time, and performance in challenging environments.

Conclusion

Consumer smartphones on the market today offer varying levels of location accuracy, ranging from a few meters to sub-meter accuracy under optimal conditions. By leveraging GPS, GNSS capabilities, assisted positioning, sensor fusion, and network-based methods, smartphones strive to provide accurate location information. However, it’s important to consider external factors and individual device capabilities that can impact accuracy. Regular advancements in smartphone technology continue to enhance location accuracy, contributing to improved user experiences and the growth of location-based applications in our daily lives.

Suggestion for Citation:
Amerudin, S. (2023). Understanding Location Accuracy in Consumer Smartphones. [Online] Available at: https://people.utm.my/shahabuddin/?p=6527 (Accessed: 6 July 2023).
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Understanding Location Inaccuracy in Mapping Applications

By Shahabuddin Amerudin

Shown GPS Location on the System
User’s Real Position on Site

Introduction

Location accuracy plays a crucial role in mapping applications, allowing users to navigate, find points of interest, and track their movements. However, it’s important to acknowledge that location inaccuracy can sometimes occur, leading to discrepancies between the displayed location and the user’s actual position. In this article, we explore the various factors that contribute to location inaccuracy and discuss strategies to mitigate its impact on mapping applications.

GPS Accuracy

GPS (Global Positioning System) relies on satellite signals to determine precise location coordinates. However, several factors can affect the accuracy of GPS signals. Device limitations, such as lower-quality GPS receivers, can result in less accurate location readings. Environmental conditions, like dense urban areas or deep indoor environments, can weaken GPS signals or introduce multipath interference, leading to inaccuracies. Additionally, the number and positioning of visible satellites at any given time can impact the accuracy of GPS readings.

Geolocation Errors

Mapping applications often rely on geolocation APIs to retrieve the user’s position. However, these APIs can introduce errors or inaccuracies in the reported location. The accuracy value provided by geolocation APIs may not always reflect the true error in the location estimation. Factors such as signal noise, limited sensor data, or the interpolation of location data can contribute to discrepancies between the reported location and the user’s actual position.

Network and Signal Interference

In scenarios where GPS signals are weak or unavailable, mapping applications may fall back on network-based positioning methods like Wi-Fi or cell tower triangulation. However, network connectivity issues or signal interference can affect the accuracy of these methods. Unreliable or spotty Wi-Fi networks, for example, may introduce inaccuracies in determining the user’s location. Similarly, obstacles or environmental conditions can interfere with the strength and quality of cellular signals, impacting the accuracy of cell tower triangulation.

User Permissions

To access precise location information, users need to grant location permissions to mapping applications. If users do not grant precise location permissions or disable location services on their devices, geolocation APIs may resort to less accurate positioning methods. This fallback mechanism, while providing approximate location data, can introduce additional inaccuracies compared to when precise location permissions are granted.

Device or Browser Limitations

Location accuracy can also be influenced by the device or browser being used. Different devices and browsers may have varying levels of geolocation capabilities and support for high-precision GPS. Older devices or browsers may lack advanced positioning technologies or have less accurate GPS receivers, leading to decreased location accuracy. It’s important for developers to consider these limitations when building mapping applications.

Mitigating Location Inaccuracy

While achieving perfect location accuracy in all scenarios is challenging, there are strategies developers can employ to improve the accuracy of displayed location in mapping applications:

  • Encouraging users to be in open areas: Advise users to be in open spaces with a clear view of the sky whenever possible. This can enhance GPS signal strength and reduce obstructions that may lead to inaccuracies.
  • Informing users about limitations: Set appropriate user expectations by providing information about the potential factors that can affect location accuracy. Educating users about the variability of accuracy readings can help manage their expectations.
  • Implementing error handling: Develop robust error handling mechanisms to handle cases where location accuracy is low or undetermined. Inform users when the accuracy falls below a certain threshold and provide appropriate feedback to avoid misleading information.
  • Considering additional positioning methods or APIs: Explore alternative positioning methods or APIs that can complement GPS data. Combining GPS with Wi-Fi or cellular network information can improve accuracy in urban areas or when GPS signals are weak.
  • Regularly updating applications and libraries: Stay up-to-date with updates and bug fixes related to geolocation functionality. Regularly check for new releases of libraries or APIs used in the mapping application to benefit from improvements that can enhance location accuracy.

Conclusion

Location inaccuracy in mapping applications can occur due to various factors, including GPS limitations, geolocation errors, network and signal interference, user permissions, and device/browser limitations. While efforts can be made to improve location accuracy, achieving pinpoint accuracy in all scenarios may not always be possible due to external factors and limitations.

By understanding the factors that contribute to location inaccuracy and implementing strategies to mitigate its impact, developers can enhance the user experience and provide more reliable location information. It is essential to manage user expectations, provide accurate error handling, and explore alternative positioning methods or APIs when necessary.

As technology continues to advance and new positioning techniques emerge, ongoing research and development efforts aim to improve location accuracy in mapping applications. By staying informed and adapting to advancements in geolocation technology, developers can strive for increasingly accurate and reliable location data in their applications.

Suggestion for Citation:
Amerudin, S. (2023). Understanding Location Inaccuracy in Mapping Applications. [Online] Available at: https://people.utm.my/shahabuddin/?p=6523 (Accessed: 6 July 2023).
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Factors that can Contribute to Human Death

There are numerous factors that can contribute to human death. These factors can be categorized into various domains, including medical, environmental, behavioral, socioeconomic, and accidental causes. Here are some common factors associated with human death:

  1. Disease and Illness: Various diseases and medical conditions can lead to death, such as cardiovascular diseases (heart attacks, strokes), cancer, respiratory diseases, infectious diseases (pneumonia, HIV/AIDS), diabetes, neurodegenerative disorders (Alzheimer’s disease, Parkinson’s disease), and many others.
  2. Accidents and Injuries: Unintentional injuries, including road accidents, falls, drowning, poisoning, burns, and occupational accidents, are major causes of death worldwide. Additionally, intentional injuries such as suicides and homicides contribute to mortality rates.
  3. Lifestyle and Behavioral Factors: Certain behaviors and lifestyle choices can increase the risk of death. These include tobacco smoking, alcohol and drug abuse, poor nutrition and diet, lack of physical activity, and risky sexual behavior leading to the transmission of sexually transmitted infections.
  4. Socioeconomic Factors: Socioeconomic conditions can influence mortality rates. Factors such as poverty, limited access to healthcare services, inadequate nutrition, and environmental hazards in low-income areas can contribute to higher mortality rates.
  5. Environmental Factors: Environmental conditions can have a significant impact on human health and mortality. These include exposure to air pollution, water contamination, extreme weather events (heatwaves, hurricanes, floods), natural disasters, and exposure to toxic substances.
  6. Genetic and Hereditary Factors: Some individuals may be predisposed to certain genetic or hereditary conditions that increase their susceptibility to diseases or health complications, which can ultimately lead to death.
  7. Age and Aging: Advancing age is a significant risk factor for mortality. The likelihood of death generally increases with age due to the natural aging process and the accumulation of age-related diseases and health conditions.
  8. Access to Healthcare: Limited access to healthcare services, including preventive care, diagnostics, and treatment, can result in delayed or inadequate medical interventions, leading to increased mortality rates.
  9. Occupational Hazards: Certain occupations carry higher risks of mortality due to occupational hazards and exposures, such as industrial accidents, exposure to harmful substances, or work-related stress.
  10. Social and Environmental Determinants: Social factors, such as education, social support, community cohesion, and access to clean water and sanitation, can impact mortality rates. Additionally, factors like war, conflict, and displacement can contribute to increased mortality rates in affected populations.

It is important to note that the prevalence and significance of these factors may vary across regions and populations. Understanding and addressing these factors play a crucial role in public health initiatives, healthcare planning, and mortality risk reduction strategies.

In the context of Malaysia, a diverse and rapidly developing country, various factors influence the mortality patterns and health outcomes of its population. By examining these factors, policymakers, healthcare professionals, and researchers can identify priority areas for intervention and develop targeted strategies to reduce mortality rates and improve overall population health.

The factors influencing human death in Malaysia are multifaceted and can be categorized into several broad areas. These factors include non-communicable diseases (NCDs), communicable diseases, accidents and injuries, maternal and child health, and age-related factors. Each of these categories plays a significant role in shaping mortality patterns and reflects the unique health challenges faced by the Malaysian population.

Non-communicable diseases, such as cardiovascular diseases, cancer, diabetes, and chronic respiratory diseases, are major contributors to mortality in Malaysia. Lifestyle factors, including unhealthy diet, physical inactivity, tobacco use, and alcohol consumption, contribute to the prevalence of these diseases. Additionally, communicable diseases, such as respiratory infections, diarrheal diseases, HIV/AIDS, malaria, and tuberculosis, continue to pose a significant health burden in certain regions and populations.

Accidents and injuries, ranging from road traffic accidents to workplace incidents and violence, contribute to a substantial number of deaths in Malaysia. Addressing these preventable causes of death requires targeted interventions in areas such as road safety, occupational health and safety, and violence prevention.

Maternal and child health is another critical area influencing mortality rates in Malaysia. Improving access to quality healthcare during pregnancy and childbirth, addressing malnutrition, and enhancing maternal and child healthcare services are essential for reducing maternal and neonatal mortality rates and improving overall health outcomes for mothers and children.

Finally, age-related factors, including degenerative diseases, frailty, and age-related physiological changes, contribute to mortality rates, particularly among the elderly population. As Malaysia’s population ages, understanding and addressing the unique health needs of older adults becomes increasingly important.

To gain a comprehensive understanding of the factors contributing to human death in Malaysia, it is crucial to examine available data, conduct research studies, and collaborate across sectors. By doing so, policymakers and healthcare professionals can develop evidence-based strategies and interventions to reduce mortality rates, improve health outcomes, and enhance the overall well-being of the Malaysian population.

References

  1. World Health Organization (WHO). (2020). The top 10 causes of death. Retrieved from https://www.who.int/news-room/fact-sheets/detail/the-top-10-causes-of-death
  2. Centers for Disease Control and Prevention (CDC). (2021). Leading causes of death. Retrieved from https://www.cdc.gov/nchs/fastats/leading-causes-of-death.htm
  3. GBD 2019 Causes of Death Collaborators. (2020). Global burden of 369 diseases and injuries in 204 countries and territories, 1990-2019: A systematic analysis for the Global Burden of Disease Study 2019. The Lancet, 396(10258), 1204-1222.
  4. Lopez, A. D., Mathers, C. D., Ezzati, M., Jamison, D. T., & Murray, C. J. (Eds.). (2006). Global burden of disease and risk factors. World Bank Publications.
  5. Murray, C. J., Lopez, A. D., & Jamison, D. T. (Eds.). (1996). The global burden of disease: A comprehensive assessment of mortality and disability from diseases, injuries, and risk factors in 1990 and projected to 2020 (Vol. 1). Harvard University Press.
  6. Naghavi, M., Makela, S., Foreman, K., O’Brien, J., Pourmalek, F., Lozano, R., … & Ezzati, M. (2010). Algorithms for enhancing public health utility of national causes-of-death data. Population health metrics, 8(1), 9.
Suggestion for Citation:
Amerudin, S. (2023). Factors that can Contribute to Human Death. [Online] Available at: https://people.utm.my/shahabuddin/?p=6519 (Accessed: 26 June 2023).
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Achieving Multiple Professional Titles: Exploring the Multifaceted Career of an Accomplished Individual

By Shahabuddin Amerudin

Introduction

In certain professional fields, individuals have the opportunity to accumulate multiple professional titles, representing various levels of expertise and qualifications. These titles, such as “Sr” “Ts.” “Ir.” and “Dr.” are indicative of significant achievements and expertise in specific domains. In this discussion, we will explore the multifaceted career of an accomplished individual who has attained multiple professional titles, and the implications of such achievements.

The Significance of Multiple Professional Titles

When an individual possesses multiple professional titles, it showcases a diverse range of accomplishments and qualifications. Each title represents a distinct level of expertise within a specific professional domain. For example, the “Sr” title denotes expertise in surveying, “Ts.” signifies proficiency as a Professional Technologist, “Ir.” designates the status of a Professional Engineer, and “Dr.” represents the attainment of a doctoral degree. Each of these titles carries its own unique value and contributes to the individual’s overall professional profile.

Expanding Opportunities and Expertise

Having multiple professional titles allows individuals to explore diverse career opportunities and broaden their areas of expertise. With each additional title, individuals can venture into different sectors, projects, and roles that align with their expanded skill set. For instance, a professional with the “Sr” and “Ir.” titles can leverage their surveying expertise and engineering knowledge to take on projects that require a multidisciplinary approach. This versatility opens doors to a wider range of career prospects and increases the individual’s marketability.

Enhanced Credibility and Professional Recognition

Accumulating multiple professional titles enhances an individual’s credibility and professional recognition within their respective fields. Each title represents a significant achievement, demonstrating the individual’s commitment to continuous learning and professional development. This collection of titles highlights their breadth of knowledge and expertise, which can be particularly valuable when pursuing leadership positions, consulting opportunities, or academic roles. The accumulation of multiple titles strengthens their professional reputation and can garner respect among peers, colleagues, and potential employers.

Personal Satisfaction and Motivation

Attaining multiple professional titles can also bring personal satisfaction and a sense of accomplishment. Each title represents a milestone in one’s career journey, reflecting the dedication, hard work, and expertise acquired over time. The pursuit of additional titles can serve as a motivating factor, driving individuals to continue expanding their knowledge and pushing the boundaries of their professional capabilities. This ongoing pursuit of excellence fuels personal growth, establishes a lifelong learning mindset, and inspires others in the field.

Balancing Priorities and Specializations

While the accumulation of multiple professional titles is commendable, it is essential to strike a balance between various roles, responsibilities, and specializations. Managing diverse professional identities requires individuals to carefully allocate their time, energy, and resources. It is important to assess the synergies and overlaps between different titles and ensure that the pursuit of additional titles aligns with personal and career goals. By strategically managing priorities and leveraging the collective expertise gained through multiple titles, individuals can maximize their impact and contributions within their chosen fields.

Conclusion

The attainment of multiple professional titles signifies the remarkable achievements and expertise of individuals who have dedicated themselves to continuous learning and professional development. These titles open doors to expanded career opportunities, enhance professional recognition, and provide personal satisfaction. However, it is crucial for individuals to maintain a balance between their various roles and specializations, ensuring that their pursuits align with their overarching goals. Ultimately, the accumulation of multiple professional titles showcases an individual’s commitment to excellence and positions them as accomplished professionals within their respective fields.

Suggestion for Citation:
Amerudin, S. (2023). Achieving Multiple Professional Titles: Exploring the Multifaceted Career of an Accomplished Individual. [Online] Available at: https://people.utm.my/shahabuddin/?p=6505 (Accessed: 26 June 2023).
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The Impact of the “Sr” Title in Academic Circles: Assessing Its Significance in Professional Communication

By Shahabuddin Amerudin

Introduction

As an academic, the use of professional titles holds importance in establishing credibility and recognition within your field. The “Sr” title from the Royal Institution of Surveyors Malaysia (RISM) is often seen as a mark of expertise and professional standing. However, it is essential to critically assess the impact of incorporating the “Sr” title when presenting oneself in academic contexts, such as on business cards, email signatures, or letters. In this discussion, we will explore the experiences and perceptions surrounding the utilization of the “Sr” title in academic communication and assess its actual significance in shaping one’s career.

Limited Impact on Career Advancement

Contrary to expectations, many academics report that the inclusion of the “Sr” title on their business cards, email signatures, or letters did not yield significant career advancement. In academia, the emphasis is typically placed on research contributions, teaching excellence, and academic achievements rather than specific professional titles. While the “Sr” title may indicate a level of expertise in utilizing GIS technologies for surveying purposes, its direct impact on academic recognition or promotion may be limited.

Focus on Academic Accomplishments

In the academic realm, your reputation is primarily built upon your scholarly contributions, publications, grants, and collaborations. Academic success is more often associated with the quality and impact of your research work rather than the professional title you hold. Therefore, academics may find it more beneficial to highlight their academic qualifications, such as degrees, certifications, affiliations with academic societies, and notable research achievements, rather than relying solely on professional titles like “Sr.”

Importance of Networking and Collaboration

Building a strong network and establishing collaborations with colleagues and researchers within your field are essential for academic growth. While the “Sr” title may not have a direct impact on career advancement, networking opportunities provided by professional organizations like RISM can be valuable. Engaging with fellow professionals, participating in conferences, and contributing to relevant communities can enhance your visibility and open doors to collaborative projects and research opportunities.

Academic Culture and Perception

The perception of professional titles within the academic community may vary. In some cases, the “Sr” title may not carry the same weight or recognition as it does within the surveying profession. Academic circles often prioritize scholarly achievements, teaching effectiveness, and contributions to the field. Therefore, it is important to understand the prevailing culture and expectations within your academic discipline when considering the significance of professional titles in your career.

Emphasising Academic Identity and Expertise

As an academic, it is crucial to emphasize your academic identity and expertise in your communication. Instead of solely relying on the “Sr” title, consider highlighting your academic qualifications, research focus, teaching experience, and any prestigious awards or grants received. Emphasizing these aspects will help to establish your credibility as a scholar and contribute to the recognition and respect you receive within your academic community.

Conclusion

While the “Sr” title may hold significance within the surveying profession, its impact on career advancement and recognition in academic circles may be limited. Academics should prioritize showcasing their academic accomplishments, research contributions, teaching excellence, and collaborations within their field. Building a strong network, engaging in scholarly activities, and emphasizing one’s academic expertise will likely have a more substantial impact on career progression and reputation in academia than the inclusion of a specific professional title.

Suggestion for Citation:
Amerudin, S. (2023). The Impact of the "Sr" Title in Academic Circles: Assessing Its Significance in Professional Communication. [Online] Available at: https://people.utm.my/shahabuddin/?p=6503 (Accessed: 26 June 2023).
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Navigating the Path to Professional Recognition: Choosing Between the “Sr” or “Gs” Title for a Graduate in GIS Program

By Shahabuddin Amerudin

Introduction

For graduates in Geographic Information Systems (GIS) programs, the journey towards professional recognition often includes the decision of whether to pursue the “Sr” title from the Royal Institution of Surveyors Malaysia (RISM) or the “Gs” title from the Institute of Geospatial and Remote Sensing Malaysia (IGRSM). Both titles carry significance within the GIS field, but understanding their nuances and benefits is essential for making an informed choice. In this article, we will explore the factors to consider when deciding between the “Sr” and “Gs” titles for GIS graduates.

Royal Institution of Surveyors Malaysia (RISM) – “Sr” Title

The “Sr” title granted by RISM carries recognition and prestige within the surveying profession. As a GIS graduate, joining RISM and obtaining the “Sr” title demonstrates a commitment to the surveying field and signifies a higher level of expertise in utilizing GIS technologies for surveying purposes. RISM offers networking opportunities, professional development programs, and resources specific to the surveying profession. The “Sr” title adds credibility and professional standing to your GIS expertise, particularly within the surveying industry.

Institute of Geospatial and Remote Sensing Malaysia (IGRSM) – “Gs” Title

IGRSM, on the other hand, focuses specifically on geospatial and remote sensing professionals. As a GIS graduate, joining IGRSM and obtaining the “Gs” title showcases specialization in geospatial technologies, mapping, and remote sensing applications. IGRSM provides access to a community of professionals engaged in geospatial disciplines and offers events, workshops, and publications centered around advancements in geospatial technologies. The “Gs” title highlights your expertise in the broader realm of geospatial sciences beyond surveying, positioning you as a proficient GIS professional.

There are several factors to consider:

a. Career Goals and Interests

Evaluate your career goals and interests to determine which title aligns better with your aspirations. If your focus is primarily on surveying and land-related applications, the “Sr” title from RISM may be more suitable. Conversely, if you have a broader interest in geospatial technologies and remote sensing applications beyond surveying, the “Gs” title from IGRSM may be a better fit.

b. Industry Relevance

Research the specific industry requirements and expectations in your chosen GIS career path. Some sectors may place more emphasis on surveying and value the “Sr” title, while others may prioritize a broader understanding of geospatial technologies and remote sensing, favoring the “Gs” title. Understanding industry preferences will help you align your professional recognition with the expectations of potential employers or clients.

c. Networking and Professional Development Opportunities

Consider the networking and professional development opportunities offered by each organization. Assess the events, conferences, workshops, and publications provided by RISM and IGRSM. Identify the resources and platforms that will support your ongoing learning and professional growth. Evaluate which organization can provide the most relevant connections and learning opportunities to advance your GIS career.

d. Cost-Benefit Analysis

Take into account the membership fees, examination costs, and financial commitments associated with each organization. Conduct a cost-benefit analysis to assess the value derived from the respective memberships and titles. Consider the potential return on investment in terms of career advancement, networking, access to resources, and industry recognition.

e. Long-Term Career Impact

When contemplating the long-term career impact of choosing between the “Sr” title from RISM or the “Gs” title from IGRSM, several factors come into play. Firstly, consider how each title will shape your professional profile. Reflect on the type of projects, responsibilities, and roles you aspire to in your GIS career. If you envision a career focused on surveying and land-related applications, the “Sr” title may be highly regarded by employers and clients within that sector. On the other hand, if your interests lie in broader geospatial technologies, mapping, and remote sensing applications, the “Gs” title may position you as a versatile GIS professional capable of handling diverse projects.

f. Personal Growth and Skill Development

Evaluate the opportunities for personal growth and skill development provided by each organization. Consider the continuing education programs, certifications, and technical resources offered by RISM and IGRSM. Determine which organization can offer the resources and support to enhance your GIS skills and keep you updated with the latest advancements in the field.

g. Peer Recognition and Industry Reputation

Research the reputation and recognition of both RISM and IGRSM within the GIS industry. Consider the perceived value and recognition associated with the “Sr” and “Gs” titles. Assess the level of respect and credibility that these titles hold among industry professionals and potential employers. A title that is highly regarded within the GIS community can enhance your professional reputation and open doors to new opportunities.

Considering Alternatives

If you choose not to pursue the “Sr” title from RISM or the “Gs” title from IGRSM, it does not necessarily mean that your GIS career will be hindered. Professional titles are not the sole determinant of success in the field. Many GIS professionals have built successful careers without specific titles.

However, it is important to note that obtaining a professional title can bring certain advantages and recognition within the industry. The titles demonstrate a commitment to professional development and expertise in specific areas of GIS. They can enhance your credibility, open doors to networking opportunities, and provide access to resources and knowledge specific to the respective organizations.

If you decide not to pursue a title, it becomes even more crucial to focus on other aspects of your career development. This includes gaining practical experience, acquiring additional certifications or specialized training, building a strong portfolio, and staying up-to-date with the latest advancements in GIS technology and applications. Networking with professionals in the field, joining relevant industry associations, and participating in conferences and workshops can also contribute to your professional growth and create opportunities.

Ultimately, the value of a professional title lies in its ability to differentiate you in the job market and showcase your dedication to continuous learning and professional development. However, it is not the only path to success in GIS. By focusing on building your skills, experience, and industry reputation through alternative means, you can still thrive and excel in your GIS career.

Conclusion

Choosing between the “Sr” title from RISM or the “Gs” title from IGRSM is a crucial decision for GIS graduates seeking professional recognition. By considering factors such as career goals, industry relevance, networking opportunities, cost-benefit analysis, long-term career impact, personal growth, and industry reputation, you can make an informed choice that aligns with your aspirations and maximizes your potential for success. Remember that both titles carry significance and can enhance your professional standing in the GIS field. Ultimately, it is essential to select the title that best complements your career path, interests, and future goals.

Suggestion for Citation:
Amerudin, S. (2023). Navigating the Path to Professional Recognition: Choosing Between the "Sr" or "Gs" Title for a Graduate in GIS Program. [Online] Available at: https://people.utm.my/shahabuddin/?p=6501 (Accessed: 26 June 2023).
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Evaluating the Value of Professional Memberships: Making Informed Career Decisions

By Shahabuddin Amerudin

Introduction

Professional memberships provide individuals with opportunities for career advancement, industry recognition, and access to valuable resources. With esteemed titles such as “Sr” for surveyors with the Royal Institution of Surveyors Malaysia (RISM), “Ts.” for Professional Technologists with the Malaysia Board of Technologists (MBOT), and “Ir.” for Professional Engineers with the Institute of Engineers Malaysia (IEM), these designations carry prestige and signify professional achievement. However, it is crucial to delve deeper into the advantages and disadvantages before committing to these professional memberships. This article will explore the factors to consider when evaluating the worth of professional memberships, specifically focusing on RISM, MBOT, and IEM.

Alignment with Career Goals

To assess the value of professional memberships, consider how well they align with your career goals. RISM membership, with the title “Sr,” is relevant for surveyors seeking recognition within the surveying industry in Malaysia. MBOT membership, with the “Ts.” designation, caters to technologists looking to establish themselves professionally. IEM membership, with the “Ir.” title, is beneficial for engineers aiming to enhance their standing within the engineering field. Evaluate whether these memberships and titles will contribute to your professional growth and align with your long-term career aspirations.

Evaluating Membership Benefits

Examine the benefits offered by RISM, MBOT, and IEM. Determine if these organizations provide access to networking events, educational resources, professional development programs, and industry-specific publications. Consider whether these benefits are valuable for enhancing your skills, knowledge, and professional reputation. Additionally, assess whether the organizations offer specialised support, such as regulatory guidance or representation within the industry.

Networking Opportunities

Professional organizations act as platforms for networking and collaboration. Evaluate the size and diversity of the membership bases in RISM, MBOT, and IEM. Assess the potential to connect with experienced professionals, industry leaders, and peers within your field. These networking opportunities can foster relationships that lead to collaboration, career opportunities, and knowledge sharing.

Cost-Benefit Analysis

Membership fees and associated costs should be carefully evaluated. Consider the financial investment required to join and maintain membership in RISM, MBOT, and IEM. Compare these costs with the potential benefits, such as enhanced professional status, increased job opportunities, and access to exclusive resources. Assess the value these memberships provide in relation to your career goals and financial circumstances.

Reputation and Credibility

The reputation and credibility of professional organizations are essential factors to consider. Evaluate the standing of RISM, MBOT, and IEM within their respective industries. Research their recognition among employers, clients, and peers. Determine if the membership titles, such as “Sr,” “Ts.,” or “Ir.,” are widely respected and recognised as symbols of professional competence and expertise.

Commitment and Involvement

Consider the level of commitment and involvement expected from members. Evaluate whether you have the time, energy, and willingness to actively participate in the organizations’ activities, committees, or volunteering opportunities. Active engagement can maximise the benefits derived from membership, allowing you to contribute to the profession, expand your network, and enhance your professional growth.

Industry Requirements and Regulations

Research whether membership in RISM, MBOT, or IEM is mandatory or preferred within your industry. Certain employers or job positions may require specific professional memberships as part of their hiring criteria. Assess the industry’s expectations for professional recognition and whether the membership titles align with the requirements for your desired career advancement.

Conclusion

Joining professional organizations like RISM, MBOT, or IEM can provide numerous benefits for career growth and professional development. By evaluating factors such as alignment with your career goals and the specific benefits offered by each organization, you can make an informed decision about the worth of joining.

Regarding RISM, membership and the “Sr” title can bring recognition and credibility within the surveying industry in Malaysia. It provides opportunities to network with experienced surveyors, gain insights into industry trends, and access resources tailored to the profession. The organization may also offer professional development programs, continuing education opportunities, and platforms to showcase your expertise.

For MBOT, membership and the “Ts.” title can be advantageous for professional technologists. It showcases your commitment to ethical practices and upholds industry standards. MBOT may provide access to specialized training programs, conferences, and forums where you can interact with fellow technologists and stay updated on emerging technologies and practices. Additionally, the organization’s recognition may be valued by employers and clients, boosting your professional credibility.

Membership in IEM and the “Ir.” title can be particularly valuable for engineers. IEM offers a wide range of benefits, including access to technical resources, industry publications, and professional development opportunities. The organization conducts seminars, conferences, and workshops, enabling engineers to stay updated on advancements in their field. IEM’s reputation can enhance your professional standing and provide opportunities to network with influential figures in the engineering industry.

When evaluating these memberships, it is important to consider the cost-benefit ratio. While there may be membership fees and associated expenses, weigh them against the potential advantages, such as career advancement opportunities, industry recognition, and access to valuable resources. Consider your budget, the potential return on investment, and how the membership aligns with your long-term career aspirations.

Ultimately, the decision to join RISM, MBOT, or IEM should be based on a thorough evaluation of your specific career goals, the benefits offered by each organization, and the potential impact on your professional growth and development. By conducting thorough research and considering these factors, you can make an informed decision that aligns with your career objectives and maximizes the benefits of professional membership.

Suggestion for Citation:
Amerudin, S. (2023). Evaluating the Value of Professional Memberships: Making Informed Career Decisions. [Online] Available at: https://people.utm.my/shahabuddin/?p=6499 (Accessed: 26 June 2023).
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Survey Analysis Report: UTM and Kg. Sg. Timun CSR Programme Feedback

By Shahabuddin Amerudin

Introduction

This report presents the analysis of a post-programme survey conducted to gather feedback on the UTM and Kg. Sg. Timun CSR Programme. The survey aimed to evaluate participants’ satisfaction, assess the programme’s effectiveness in meeting expectations, and gather suggestions for improvement. The survey was administered online, and participants were asked to share their thoughts and experiences regarding various aspects of the programme.

Survey Details

The online survey was open for responses from June 13, 2023, to June 19, 2023. A total of 33 students were scheduled to participate in the programme; however, one participant was unable to attend on the designated day. Out of the remaining 32 participants, 30 completed the survey, resulting in a response rate of 93.8%.

Purpose and Methodology

The survey aimed to gather feedback to evaluate the UTM and Kg. Sg. Timun CSR Programmes and make improvements for future initiatives. The survey questions were developed using a combination of closed-ended and open-ended formats. Closed-ended questions utilised a Likert scale, while open-ended questions provided participants with an opportunity to provide detailed feedback. The survey was administered online, and participant identities were kept confidential.

Analysis

The survey responses were analysed using both quantitative and qualitative approaches. For the closed-ended questions, quantitative analysis involved calculating summary statistics such as mean, median, and mode to assess participants’ overall satisfaction and perceptions of different programme aspects. Frequency distributions and percentages were also computed to depict the distribution of responses.

The open-ended questions were subjected to qualitative analysis. Responses were categorised and coded to identify common themes, patterns, and suggestions. The qualitative analysis aimed to uncover participants’ experiences, suggestions for improvement, and any concerns raised during the programme.

Findings

Based on the survey analysis, several key findings emerged. The majority of participants expressed high satisfaction with the UTM and Kg. Sg. Timun CSR Programme, highlighting its positive impact. The programme effectively met participants’ expectations in terms of providing hands-on learning opportunities and practical experience in mangrove conservation. Programme facilitators received positive feedback for their guidance and facilitation of activities.

The programme was successful in raising participants’ awareness about the importance of mangrove conservation, although some participants suggested providing additional information to enhance their knowledge further. The resources provided, such as the Mangrove Forest Tree Identification and Geotagging mobile app and online database, were perceived as useful, but participants raised suggestions for improvement.

The boat excursions and firefly-watching activities were generally well organised, though some room for improvement was noted. The fee collected for food, boat rides, and the firefly-watching activity was considered reasonable by the majority of participants, but a few expressed concerns, particularly regarding the boat ride fee from a student’s perspective.

Participants expressed a willingness to pay additional fees for transportation, programme merchandise, or other related expenses in future programmes, depending on the specific items or services offered. The programme had a positive impact on participants’ understanding of the Mangrove Forest Tree Identification and Geotagging mobile app and online database, but further support and engagement opportunities were suggested.

Recommendations

To enhance participants’ knowledge and engagement, it is recommended to improve the educational content and resources provided in the UTM and Kg. Sg. Timun CSR Programmes. This can be achieved by incorporating additional information, workshops, or presentations to deepen their understanding of mangrove conservation. Continuously updating and expanding the resources, such as the Mangrove Forest Tree Identification and Geotagging mobile app and online database, will ensure they remain informative, user-friendly, and relevant.

Addressing participant feedback is crucial to improving the programme. Specifically, it is important to take into account their suggestions regarding the organisation of boat excursions, firefly-watching activities, and concerns about fees. By gathering feedback and identifying areas for improvement, adjustments can be made to enhance the overall organisation and execution of these activities. It is also recommended to evaluate the fee structure to ensure it remains reasonable and accessible, considering the perspectives of students and affordability.

To create more impactful CSR programmes, it is essential to tailor future initiatives to meet participant preferences and expectations. Conducting pre-programme surveys or focus groups to gather input and insights on participants’ needs and interests can provide valuable information. Additionally, it is important to continuously evaluate the effectiveness of the CSR programmes by gathering feedback from participants and making necessary adjustments. This iterative approach will help UTM and Kg. Sg. Timun create meaningful and engaging experiences while fostering continuous improvement in their CSR initiatives.

Conclusion

Overall, the survey findings indicate a high level of interest in participating in future CSR programmes organised by UTM and Kg. Sg. Timun. To ensure continued success, it is recommended that future programmes focus on delivering valuable content, addressing suggestions for improvement, and incorporating participants’ preferences and expectations.

The survey analysis provides valuable insights that can inform programme evaluation and improvement, enabling UTM and Kg. Sg. Timun to enhance their future initiatives and ensure the continued success of their CSR programmes.

References:
Amerudin, S. (2023). UTM and Kg. Sg. Timun Empower Mangrove Conservation through an Innovative CSR Programme. [Online] Available at: https://people.utm.my/shahabuddin/?p=6427 (Accessed: 23 June 2023).

Amerudin, S. (2023). Comprehensive Analysis of Survey Feedback: UTM and Kg. Sg. Timun CSR Programme. [Online] Available at: https://people.utm.my/shahabuddin/?p=6482 (Accessed: 23 June 2023).

Amerudin, S. (2023). UTM and Kg. Sg. Timun Empower Mangrove Conservation through an Innovative CSR Programme. [Online]. Available at: https://news.utm.my/2023/06/utm-and-kg-sg-timun-empower-mangrove-conservation-through-an-innovative-csr-programme/?_gl=11m4f3of_gaMjAzNTkxNjMwNi4xNjgzMTAzNzUx_ga_N3HJW8G3P7*MTY4NzUwNjI5Ny42OC4xLjE2ODc1MDcyMTQuMC4wLjA. (Accessed: 23 June 2023).

Suggestion for Citation:
Amerudin, S. (2023). Survey Analysis Report: UTM and Kg. Sg. Timun CSR Programme Feedback. [Online] Available at: https://people.utm.my/shahabuddin/?p=6480 (Accessed: 23 June 2023).