CELEBRATING THE ANNUAL STAFF PERFORMANCE CEREMONY
Thank you to the organizers. This year, I couldn’t attend the Staff Excellence Awards Ceremony. A big thank you to those who represented me to collect the certificates. May this serve as a catalyst for the coming years.
#StaffExcellence #December3rd #CelebratingSuccess #GratitudeAndRecognition #MotivationForTheFuture #PerformanceAwards #HonoringAchievement #TeamworkAndGrowth #AnnualCeremony #InspiringExcellence #AchievingTogether
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
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
STRENGTHENING RESEARCH SKILLS: SYSTEMATIC LITERATURE REVIEW (SLR) TRAINING
On Sunday, we kicked off Day 1 of the Systematic Literature Review (SLR) training session, a personal coaching initiative for my research group. This effort is dedicated to enhancing the research capabilities of my postgraduate students and lab members.
The session, conducted by our very own Lab 3D PhD student, Hafiz Usman Mehmood. He has a vast experience writing this type of paper. Our day 1 training covered critical aspects of SLR, including:
1. Introduction to SLR
2. Importance in Academic Research
3. Developing Research Questions
4. Selecting Databases & Searching Articles
5. Screening & Applying Inclusion/Exclusion Criteria
I believe that empowering young researchers with structured approaches like SLR is key to producing impactful, high-quality research.
These closed training sessions reflect our commitment to cultivating a strong research foundation within our lab. Tomorrow, we move to Day 2 with advanced topics, including the PRISMA framework and qualitative synthesis.
#ResearchSkills #SystematicLiteratureReview #LabTraining #AcademicExcellence #PostgraduateResearch #Mentorship
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
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!
THE CITRA KARISMA AWARD 2024!
Grateful to have been awarded the Award for Indexed Journal Publication at the Citra Karisma 2024, which is Universiti Teknologi Malaysia’s prestigious university achievements award. Basically this award acknowledges the significant research contributions in indexed journals throughout 2023.
I want to express my sincere thanks to Universiti Teknologi Malaysia for this honor and to all my colleagues and students for their continued support and collaboration. Let us keep to continue pushing the boundaries of knowledge and excellence in research.
Research publication is not solely a university’s KPI – it is one of the most valuable research products that reflects the entire journey of academic and scientific discovery. It’s a process that begins with brainstorming, shaping ideas into proposals, securing funding, and working tirelessly alongside fellow researchers. It involves countless hours of dedication, navigating challenges, and pouring in both sweat and tears to bring those ideas to fruition. Only then do we synthesize all of this hard work into a paper, not for personal gain but to share freely with the world, advancing knowledge for the betterment of humanity.
“The future belongs to those who believe in the beauty of their dreams.” – Eleanor Roosevelt
Let’s never stop aiming higher!
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
SHARING THE SUCCESS OF OUR PUBLICATION!
Our paper titled “Factors That Affect Spatial Data Sharing in Malaysia” has been making waves! Published in the ISPRS International Journal of Geo-Information (IJGI), our research has already been downloaded 1,309 times. This engagement underscores the importance and impact of our work in the geospatial community.
I’m deeply grateful to the ISPRS IJGI team for their support and for providing a platform to share our findings with a global audience. The journal’s impressive impact (Q2) and a Citescore of 6.9 (Q1) are a testament to its role in advancing geospatial research.
Looking forward to continuing our collaboration and contributing more research to this esteemed journal. If you haven’t yet, feel free to check out the paper here: http://www.mdpi.com/2220-9964/11/8/446
#ResearchImpact #GeospatialData #SpatialDataSharing #AcademicPublishing #ISPRS #Geoinformatics @MDPIOpenAccess
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
