Tag Archives: utm

STRENGTHENING RESEARCH SKILLS – SYSTEMATIC LITERATURE REVIEW (SLR) TRAINING DAY 2

STRENGTHENING RESEARCH SKILLS – SYSTEMATIC LITERATURE REVIEW (SLR) TRAINING DAY 2

Day 2 of our Systematic Literature Review (SLR) training, continuing the journey of building strong research skills within my lab. Led by Hafiz Usman Mehmood, this personal coaching session for lab members focused on advanced techniques and practical applications of SLR.

Key topics covered included:

1. The PRISMA Framework

2. Thematic Analysis & Qualitative Synthesis

3. Structuring Papers & Reporting Results

“The beautiful thing about learning is that no one can take it away from you.” – B.B. King

These sessions aim to prepare our research group to confidently undertake systematic reviews, ensuring their work is rigorous and impactful. It’s rewarding to see the enthusiasm and dedication from everyone involved.

#ResearchSkills #SystematicLiteratureReview #LabTraining #AcademicExcellence #PostgraduateResearch #Mentorship

GREEN BELTS IN 3D – A NATURAL SOLUTION FOR TRAFFIC NOISE MITIGATION

GREEN BELTS IN 3D – A NATURAL SOLUTION FOR TRAFFIC NOISE MITIGATION

This is our latest publication titled “Traffic Noise Absorption and Propagation in a Three-Dimensional Spatial Environment” in Geoplanning: Journal of Geomatics and Planning.

This research explores the role of tree canopies as noise barriers using advanced LiDAR-based 3D models. By visualizing tree structures in 3D, we analyzed their noise absorption performance and identified how green belts can effectively reduce traffic noise propagation.

Okay the Key Findings:

-Tree leaves play a major role in absorbing noise.

-3D Convex Hull and Concave Hull methods improve canopy surface estimation.

-Voxel-based models provide better accuracy for leaf surface area and density analysis.

The study emphasizes the potential of green belts as cost-effective and sustainable noise mitigation solutions, particularly for developing countries.

Imagine quieter roads and healthier urban environments that is powered by nature and technology.

Read the full paper here: https://ejournal.undip.ac.id/index.php/geoplanning/article/download/60822/pdf

#NoisePollution #GreenInfrastructure #3DVisualization #TrafficNoise #Sustainability #UrbanPlanning #GeospatialTech #ResearchImpact

CELEBRATING A NEW COPYRIGHT ACHIEVEMENT!

CELEBRATING A NEW COPYRIGHT ACHIEVEMENT!

Today, we are excited to announce that our product entitled “Presentation Rubric for Geoinformatics (SBEG)” has been Copyrighted by the Innovation and Commercialization Center (ICC) of Universiti Teknologi Malaysia (UTM). This achievement will further enable tools for education and research in geoinformatics. The copyright is registered under reference IP/CR/05605, dated 3 December 2024.

This rubric is designed to streamline and enhance the assessment process for geoinformatics presentations, providing a structured and comprehensive approach to evaluating quality and impact. It’s a step forward in promoting academic excellence and innovation.

At UTM, we are not only conducting groundbreaking research, but also pioneering research in education, bridging knowledge and practice to empower the next generation of scholars and innovators.

“Education is the most powerful weapon which you can use to change the world” – Nelson Mandela

Thank you to UTM ICC for their continued support and to everyone who contributed to the success of this product. Together, we are driving impactful advancements in education and research. Let’s continue to push boundaries, inspire minds, and shape the future.

#CopyrightGranted #Innovation #Geoinformatics #EducationTools #AcademicExcellence #UTM #ResearchAndEducation #InspiringTheFuture

3D CITY MODELLING FOR HIGH-RISE BUILDING MAINTENANCE!

3D CITY MODELLING FOR HIGH-RISE BUILDING MAINTENANCE!

Our latest research article, “Transforming High-Rise Residential Maintenance: A 3D Spatio-Temporal Model Utilizing Industry 4.0 and Lean Principles”, in the prestigious journal Facilities.

This study introduces a 3D spatio-temporal maintenance model that combines cutting-edge Industry 4.0 technologies (like IoT, AI, and big data) with lean maintenance principles to:
-Optimize maintenance schedules
-Enhance resource allocation
-Improve decision-making processes
-Reduce downtime and costs
-Increase tenant satisfaction through better building performance

The key highlights:
1) Integration of real-time data analytics for predictive maintenance.
2) Advanced 3D visualizations to identify maintenance trends and priorities.
3) A framework designed for sustainability and efficiency in high-rise residential buildings.

This model represents a game-changer in facility management by addressing the unique challenges of high-rise buildings and delivering proactive, data-driven maintenance strategies.

“From better planning to smarter solutions, this research paves the way for innovative and sustainable maintenance practices!”

Read the full article here: https://www.emerald.com/insight/content/doi/10.1108/f-06-2024-0085/full/html

#Industry4 #LeanMaintenance #3DModels #FacilitiesManagement #SpatioTemporal #HighRiseBuildings #Innovation #Sustainability

TRAFFIC NOISE PREDICTION USING MACHINE LEARNING!

TRAFFIC NOISE PREDICTION USING MACHINE LEARNING!

Our new research paper titled “Traffic Noise Prediction Model Using GIS and Ensemble Machine Learning: A Case Study at Universiti Teknologi Malaysia (UTM) Campus” has been published in the Q1-ranked journal Environmental Science and Pollution Research (Web of Science indexed)!

This study focuses on the application of Geographical Information Systems (GIS) and ensemble machine learning models to predict traffic noise levels, an important environmental concern. Our research provides a detailed analysis of how these innovative methods can be used to accurately predict noise propagation and assist in urban planning for noise mitigation strategies.

The results highlight the effectiveness of ensemble learning methods, such as Random Forest and Gradient Boosting, in providing accurate predictions compared to traditional models. This approach could lead to more effective noise control measures and improved quality of life in urban environments.

Check out the full study here:
Title: Traffic Noise Prediction Model Using GIS and Ensemble Machine Learning: A Case Study at Universiti Teknologi Malaysia (UTM) Campus
Link to the paper: https://rdcu.be/dWJaz

This study showcases the power of machine learning in tackling environmental challenges! Using advanced ensemble models like Random Forest, Gradient Boosting, and Extreme Gradient Boosting, the team has developed highly accurate predictions of traffic noise levels. This breakthrough combines GIS with cutting-edge machine learning techniques, making it a standout achievement in noise pollution research!

#TrafficNoise #MachineLearning #GIS #NoisePollution #UrbanPlanning #SustainableCities #EnvironmentalScience #ResearchImpact

GIS AND DATA SCIENCE – A TWO SIDES OF THE SAME COIN

GIS AND DATA SCIENCE – A TWO SIDES OF THE SAME COIN

GIS and Data Science are essentially the same at their core, both involve analyzing and extracting insights from data.

The difference? GIS takes it a step further by adding location to the mix, transforming data into spatial data.

This extra layer of location allows us to visualize patterns, make more informed decisions, and solve complex challenges related to geography, urban planning, environment, and much more.

In other words, GIS = Data Science + Location, unlocking endless possibilities for spatial analysis.

Ready to explore how spatial data enhances traditional data analysis? Dive into these key data science terms that drive both fields forward!

#GIS #DataScience #SpatialData #LocationIntelligence #SpatialAnalysis #BigData #MachineLearning #GeoAI #SmartCities

ONE IN A MILLION OPPORTUNITY – FULLY FUNDED PHD IN 3D GEOSPATIAL AI (GEO-AI)

ONE IN A MILLION OPPORTUNITY – FULLY FUNDED PHD IN 3D GEOSPATIAL AI (GEO-AI)

I am pleased to announce a 3-year fully-funded PhD position from 2024 to 2027, focusing on cutting-edge research in 3D Geospatial Artificial Intelligence (Geo-AI).

This research will be supervised by me, providing the opportunity to work closely on innovative solutions addressing urban sustainability challenges using state-of-the-art 3D geospatial analysis and AI models.

The PhD grant covers:

• Full tuition fee for the entire PhD duration

• Monthly allowance throughout the 3-year period

Eligibility:

• Open to local Malaysian students

• Strong interest in geospatial sciences, AI, and environmental sustainability

For more information or to apply, please contact me at mduznir@utm.my.

Come and join our group and push the boundaries of 3D geospatial AI.

#PhDOpportunity #GeoAI #GeospatialScience #AI #UrbanSustainability #UTM #Research #Innovation

NEXT YEAR EVENT: KEYNOTE SPEAKER AT PCIVI2025 IN LONDON!

NEXT YEAR EVENT: KEYNOTE SPEAKER AT PCIVI2025 IN LONDON!

I’ve been invited to serve as a Keynote Speaker at the Precision Global Forum on Civil, Structural, and Environmental Engineering (PCIVI2025), scheduled to be held from August 11-13, 2025, in London, UK.

This prestigious event, hosted by Reoozvelt, will bring together experts and professionals from around the world to discuss and share knowledge on key subjects in civil, structural, and environmental engineering. It’s an honor to contribute to this global platform and engage with fellow industry leaders.

Looking forward to enriching discussions and sharing insights at this significant forum. Many thanks to the PCIVI2025 organizing committee for this wonderful opportunity!

#PCIVI2025 #KeynoteSpeaker #CivilEngineering #StructuralEngineering #EnvironmentalEngineering #Conference2025 #Innovation

NEW PUBLICATION FROM OUR GROUP!

NEW PUBLICATION FROM OUR GROUP!

Our latest paper, “Navigating Immovable Assets: A Graph-Based Spatio-Temporal Data Model for Effective Information Management” has been published in the ISPRS International Journal of Geo-Information (IJGI)!

This research addresses the challenges of managing spatial and temporal data in asset management by introducing a graph-based spatio-temporal data model. Our approach integrates topological relationships and temporal sequences, using 3D city models and a NoSQL graph database to enhance asset management processes.

Key features include:

– A graph-based method for modeling building spaces using 3D data.

– A novel process model, Aggregated Directly-Follows Multigraph (ADFM), for temporal event management.

– Improved query efficiency and accuracy in managing complex asset data.

This work is a significant step forward in the field of geoinformatics and asset management, offering practical solutions for more effective decision-making.

You can read the full paper here:

– Website: https://www.mdpi.com/2220-9964/13/9/313

– PDF Version: https://www.mdpi.com/2220-9964/13/9/313/pdf

#AssetManagement #SpatioTemporalData #3DModeling #GraphDatabase #Geoinformatics #ResearchPublication

LATEST RESEARCH ON SMART CITY FRAMEWORKS

LATEST RESEARCH ON SMART CITY FRAMEWORKS

Our latest conference paper, “Dimensions and Attributes of Smart City Framework: Systematic Literature Review,” which is now published in the Developments and Applications in SmartRail, Traffic, and Transportation Engineering series (ICSTTE 2023). This research provides a comprehensive evaluation of smart city frameworks, focusing on the dimensions and attributes that are crucial for developing intelligent and sustainable urban environments.

Our study reviewed literature from 2014 to 2020, analyzing smart city parameters such as suprastructure, infrastructure, and infostructure. We explored how these elements, along with intelligent government services, can be optimized to better serve society. Our findings highlight the need for improved infrastructure and smarter city facilities, with government prioritizing public infrastructure as a key factor in realizing smart cities.

This research contributes to a deeper understanding of the essential components that make up smart cities, providing a conceptual diagram that simplifies the smart urban concept for policymakers and urban planners.

Discover more about our work and its implications for the future of urban planning: https://link.springer.com/chapter/10.1007/978-981-97-3682-9_41

#SmartCities #UrbanPlanning #SmartInfrastructure #TechInnovation #SustainableCities #ConferencePaper