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History of Geographic Information Systems (GIS) Development: An Overview

By Shahabuddin Amerudin

The development of Geographic Information Systems (GIS) dates back to the 19th century, when the use of geographic information to address complex issues began. In 1832, French geographer Charles Picquet produced an early version of a GIS by creating a map-based representation of cholera spread in Paris using color gradients. This marked the earliest application of spatial analysis in epidemiology.

In 1854, English physician John Snow expanded this concept by mapping a cholera outbreak in London and linking it to contaminated water. This illustrated the problem-solving potential of maps in epidemiology. The groundwork laid during this time led to the emergence of modern GIS.

During the 20th century, several key players like the Harvard Laboratory for Computer Graphics, Canada Geographic Information System, Environmental Systems Research Institute (ESRI), and UK’s Experimental Cartography Unit shaped the field. However, it wasn’t until satellite imaging technology emerged that GIS gained commercial traction, with ESRI seizing the opportunity.

In the early 20th century, a printing technique called photozincography allowed maps to separate layers for vegetation, water, and developed land, resembling GIS. Yet, it lacked analytical capabilities.

The first significant computer-geography fusion was in 1959, when Waldo Tobler introduced MIMO (Map In–Map Out), a system to apply computers to cartography. Over time, GIS evolved from a concept to a science, with Roger Tomlinson’s work on the Canadian Geographic Information System (CGIS) and the emergence of raster and vector data analysis methods as milestones.

The 1960s saw GIS shaped by key individuals, adapting cartography and geography to the emerging computer technology. In the mid-1960s, SYMAP and GRID established foundations for raster and vector data analysis, respectively. Society’s environmental concerns further fueled GIS development.

The late 1970s and early 1980s marked the adoption of GIS by national agencies and academic institutions. ESRI became a dominant player, and commercial GIS software vendors emerged. Open-source GIS like GRASS began moving GIS from research to business environments.

Since the late 1980s, usability improvement and mainstream adoption have been key focuses. The 1990s to 2010s brought significant technological advancements, expanding GIS’s capabilities. Open-source GIS software like Quantum GIS (QGIS) gained prominence, and GIS became vital in tandem with the Internet of Things (IoT), artificial intelligence (AI), and predictive analytics.

Today, GIS applications encompass crime mapping, public health strategies, and more. As it integrates with web, cloud computing, real-time data, and IoT, GIS addresses challenges such as population growth, resource depletion, and pollution. The history of GIS showcases the efforts of researchers, programmers, and analysts who paved the way for versatile tools benefiting various organizations.

Suggestion for Citation:
Amerudin, S. (2023). History of Geographic Information Systems (GIS) Development: An Overview. [Online] Available at: https://people.utm.my/shahabuddin/?p=6599 (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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Development of A Web Map-Based Muslim Cemetery Application in Kangkar Pulai

https://kppusara.kstutm.com

Alhamdulillah… Praise be to God, and with His blessings, I am delighted to share the successful completion of another undergraduate dissertation under my supervision. Muhammad Syafiq bin Mat Tahir, a student pursuing a Bachelor of Science in Geoinformatics during the session 2022/2023, has accomplished a remarkable project titled “Development of A Web Map-Based Muslim Cemetery Application in Kangkar Pulai.”

Throughout his project, Muhammad Syafiq skillfully designed a website accessible through the URL: https://kppusara.kstutm.com. This website serves as an invaluable resource for the public, enabling them to effortlessly search for grave information and precise locations within Kampung Melayu Kangkar Pulai, Johor.

The significance of this project cannot be overstated, as it stands to provide numerous benefits to the community. With the easy-to-use interface and comprehensive cemetery information at their fingertips, users will be able to find and locate graves more efficiently, easing the burden during their visits and fostering a deeper connection with their departed loved ones.

Muhammad Syafiq’s dedication and ingenuity in developing this web-based application are commendable, as it demonstrates the practical application of geospatial in addressing real-world challenges and serving the needs of the local community. Undoubtedly, this accomplishment reflects his hard work and the knowledge he has acquired during his academic journey.

As a supervisor, I am immensely proud of Muhammad Syafiq’s achievements and the positive impact his project will have on the community. It is my hope that this work will inspire others to explore innovative solutions that leverage technology for the betterment of society. Congratulations to Muhammad Syafiq bin Mat Tahir for his exceptional work, and may his efforts continue to bring benefits and advancements to the field of Geoinformatics and beyond.

Friday, July 28, 2023.

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Revolutionising EV Charging

Source: SoyaCincau.com

The introduction of a mobile “EV powerbank” service, such as the EV Charge Go, represents a significant advancement in the realm of electric vehicles (EVs) and their accessibility. This innovative solution seems to address one of the key concerns surrounding EV adoption – the availability of charging infrastructure and the need for fast and convenient charging options.

The idea of being able to book a mobile EV powerbank and have it delivered to your doorstep is incredibly convenient. It effectively eliminates the worry of finding a nearby charging station or having to wait in line for an available charging point, which is often a concern for EV owners, especially in areas with limited charging infrastructure. This service could potentially transform the way people perceive and use electric vehicles, making them a more viable and practical option for daily commuting and long-distance travel alike.

The pricing structure, starting from RM22 for a 15-minute charge, including the deployment fee, appears to be reasonably competitive. However, it would be important to compare it with the cost of charging at traditional fixed charging stations to understand the value proposition better. The convenience and time-saving aspect of this service could justify the slightly higher cost for some users, but it would also be essential to ensure that the pricing remains competitive in the evolving EV market.

While the concept of a mobile EV powerbank is promising, there are several aspects to consider for its widespread implementation. Firstly, the range and capacity of these power banks need to be sufficient to cater to various EV models and battery sizes. It would be crucial to have a standardized and adaptable power bank that can serve a wide range of vehicles to ensure widespread adoption and avoid compatibility issues.

Moreover, the environmental impact of such a service should also be taken into account. The power banks themselves need to be charged, and the energy source for that charging could influence the overall sustainability of the service. Ideally, the power bank charging should be powered by renewable energy sources to align with the goal of reducing carbon emissions and promoting eco-friendly mobility.

Additionally, the scalability and availability of the mobile EV powerbank service need to be carefully planned. As the number of EV users grows, there will be a higher demand for such services, and it will be essential to have a robust logistical system in place to ensure timely deliveries and adequate coverage in various regions.

In conclusion, the introduction of a mobile “EV powerbank” service like EV Charge Go is an exciting development that has the potential to significantly enhance the convenience and accessibility of EV charging. The concept addresses one of the main barriers to EV adoption and offers a promising solution for urban dwellers, long-distance travelers, and areas with limited charging infrastructure. However, careful consideration must be given to factors like pricing, compatibility, sustainability, and scalability to ensure its long-term success and positive impact on the EV industry and the environment.

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KPpusara Website: Laman Web Tanah Perkuburan Melayu Kangkar Pulai

https://kppusara.kstutm.com

By Shahabuddin Amerudin

Landing web page
Web map of the grave
Searching deceased information page

URL: https://kppusara.kstutm.com

Presenting the remarkable and forward-thinking project developed by Muhammad Syafiq bin Mat Tahir, a final year student pursuing a Bachelor of Science in Geoinformatics during the session 2022/2023, under the expert guidance of Dr. Shahabuddin bin Amerudin. The culmination of his academic journey resulted in the creation of an ingenious web map-based Muslim Cemetery application for Kampung Melayu Kangkar Pulai, Johor.

Muhammad Syafiq’s unwavering dedication to this project is evident in the two intensive semesters he spent meticulously crafting every aspect of the application. He commenced with an in-depth user requirement analysis, engaging with the community to truly understand their needs. This empathetic approach ensured that the application was tailor-made to cater to the specific requirements of the cemetery’s stakeholders.

To enrich the application’s accuracy and relevance, Muhammad Syafiq personally undertook extensive on-site data collection, leaving no stone unturned to ensure that each grave’s location and details were meticulously documented. Through the adept use of advanced geospatial techniques, he skillfully integrated this comprehensive data with orthophoto imagery, seamlessly incorporating it into the web map. As a result, users can effortlessly navigate the map and access a wealth of information at their fingertips.

The heart of the application lies in its website development, meticulously constructed using a robust PHP-MySQL framework. Muhammad Syafiq’s coding expertise shines through in the application’s intuitive user interface and smooth functionality. The website’s elegant design and user-friendly experience set it apart from conventional cemetery management methods, bringing digital innovation to a traditionally analog domain.

Beyond the technical prowess, Muhammad Syafiq didn’t stop there. He conducted rigorous system evaluations, continuously seeking feedback and iterating to refine the application’s performance and address any potential issues. This commitment to constant improvement ensures that the application remains efficient and reliable, meeting the needs of users consistently.

Following a successful deployment and hosting at https://kppusara.kstutm.com, the application is already reaping remarkable benefits. Users can now effortlessly search for and locate graves of their loved ones, reducing the burden of time and effort and providing a meaningful and user-friendly experience. The application’s seamless integration of advanced technology has the potential to greatly enhance community engagement, fostering a strong sense of connection among cemetery visitors. Furthermore, the website’s responsive design ensures accessibility across different platforms and devices, allowing users to enjoy its features with utmost convenience.

Moreover, the digital transition from conventional paper and pen methods to a web map-based solution offers unparalleled efficiency and sustainability. Syafiq’s innovation not only modernizes cemetery management practices but also helps preserve environmental resources by reducing paper usage and waste.

In conclusion, Muhammad Syafiq bin Mat Tahir’s Muslim Cemetery application exemplifies the true spirit of innovation and social impact. Beyond its technical prowess, the project brings together compassion, empathy, and sustainability in a remarkable way. Its potential to revolutionize cemetery management and create a more connected community makes it a trailblazing contribution, setting a new standard for how technology can positively influence traditional practices.

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Dunia Geospatial II

Dunia Geospatial I
Sambungan: https://people.utm.my/shahabuddin/?p=5536

Oleh Shahabuddin Amerudin

Di setiap koordinat yang tertulis dengan indah,
Terbentang kisah tanah, laut, dan langit yang luas,
Peta ini menjadi jendela ke dunia yang nyata,
Melalui geospatial, semua rahasia terungkap dengan jelas.

Dari hutan tebal hingga padang pasir tandus,
Jejak manusia dan alam saling berpaut erat,
Titik-titik data menjadi benang merah cerita,
Yang menjalin sejarah, masa kini, dan masa yang akan datang.

Tak hanya sekedar angka, koordinat, atau nama tempat,
Geospatial membuka jendela ke kompleksiti kehidupan,
Dengan teknologi kita bisa menjelajahi masa lalu,
Serta meramalkan arah masa depan yang terbuka lebar.

Namun jangan kita melupakan, di balik layar digital,
Ada alam yang rentan, perlu perlindungan dan perhatian,
Peta bukan hanya tentang data, tapi tanggung jawab,
Melindungi bumi yang indah, tujuan mulia kita sebagai insan.

Jadi mari kita terus menggali, meneroka setiap sudut,
Dunia geospatial tak hanya tentang ilmu,
Tapi juga tentang bagaimana kita mengurus bumi ini,
Agar generasi mendatang tetap saksikan keajaibannya dengan bahagia.

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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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Wujudku BayanganMu

Usah lari mengejar bayanganmu
Henti langkah jika kau sedar
Tunduk bersimpuh hadap dirimu
Dirimu adalah bayanganNya

Jangan tempuh sempadan Laisa
Pasti langkahmu akan tersasar
Pandanglah alam jua dirimu
Semua ternyata wajahNya

Wujud ku bayanganMu
Wujud ku wajahMu
Wujud ku bayanganMu
Wujud ku wajahMu

Bukan aku DiriMu
Ku sekadar ceritaMu
Bukan aku DiriMu
Ku sekadar ceritaMu

Kau tiada pada si buta
Engkau Nyata pada yang tahu
Kau tiada pada si buta
Engkau Nyata pada yang tahu

Dibalik mata Kau yang memandangMu
Hilanglah aku nyata wujudMu
Dibalik mata kau yang memandangMu
Hilanglah aku nyata wujudMu

Wujud ku bayanganMu
Wujud ku wajahMu
Wujud ku bayanganMu
Wujud ku wajahMu

Bukan aku DiriMu
Ku sekadar ceritaMu
Bukan aku DiriMu
Ku sekadar ceritaMu

Kau tiada pada si buta
Engkau Nyata pada yang tahu
Kau tiada pada si buta
Engkau Nyata pada yang tahu

Dibalik mata Kau yang memandangMu
Hilanglah aku nyata wujudMu
Dibalik mata Kau yang memandangMu
Hilanglah aku nyata wujudMu

Hilanglah aku nyata wujudMu

Hilanglah aku nyata wujudMu.

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Teka-teki

Engkau engkau
Aku Aku

Aku bukan engkau
Engkau bukan Aku

Aku adalah engkau
Engkau adalah Aku