Developing an IoT-Based Multi-Sensor System for Real Time Fire Detection and Spatial Analysis to Improve Campus Safety
Khairul Nizam Abdul Maulud, Universiti Kebangsaan Malaysia, Malaysia
Nexus Approach for a Sustainable Environment: From Individual Modeling Approaches to Digital Twins
Anthony Lehmann, University of Geneva, Switzerland
Available Soon
Mihai Daniel Nita, Transilvania University of Brasov, Romania
Developing an IoT-Based Multi-Sensor System for Real Time Fire Detection and Spatial Analysis to Improve Campus Safety
Khairul Nizam Abdul Maulud
Universiti Kebangsaan Malaysia
Malaysia
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Brief Bio
Sr Ts. Gs. Dr Khairul Nizam Abdul Maulud is an Assoc. Prof. at the Faculty of Engineering & Built Environment, Universiti Kebangsaan Malaysia (UKM). He was also appointed as a Deputy Executive Director (Sustainability), UKM Strategy Center, Universiti Kebangsaan Malaysia. Previously, he was the Head of Earth Observation Centre, Institute of Climate Change, Universiti Kebangsaan Malaysia. He joined Universiti Kebangsaan Malaysia in 2001 after completing his B.Sc. in Geoinformatics from the University of Technology, Malaysia. He received his M.Sc in Geoinformatics from the University of Technology, Malaysia and PhD in Civil & Structural from Universiti Kebangsaan Malaysia. Currently, he has published more than 151 journal papers, 44 books and book chapters in book and 99 proceedings in national and international proceedings. He has been involved as a principal researcher and consultant works for more than 100 research grants, 46 consultant works in Malaysia. To date, he has supervised 36 PhD students, 15 Master's Students and 38 bachelor's degrees. His expertise is a Geospatial Technology, GIS and Geomatic and has almost 23 years of experience in research and consultancy. He has successfully completed almost 23 water-related projects including sea-level rise, geospatial analysis, landuse changes, water quality, shoreline erosion, water management using GIS and Coastal Vulnerability Index. He has received a Australia Awards Fellowship from Department of Foreign Affairs and Trade (DFAT) Australia and has undergone a fellowship program at the University of Technology Sydney, Australia. He now led high-impact research on climate change, especially on the physical and economic impacts. He also is an expert panel for the government of Malaysia, especially in coastal geomorphology, geospatial analysis and spatial water quality analysis. He is very active as an evaluation panel for research grants at the Ministry of Science, Technology and Innovation and the Ministry of Higher Education Malaysia.
Abstract
Since the year 2000, the smart city concept has been integrated into university campuses to address shared challenges in providing safe and comfortable environments for occupants. However, campuses face unique risks, such as high usage of paper-based products and combustible amenities, which can lead to severe fire incidents. Fire statistics from local university campuses have shown significant losses from such events. Conventional fire alarms on campuses have limitations, including a lack of real-time alerts during fire hazards and a focus on single sensing. Therefore, enhancing traditional fire alarms with a multi-sensor system is necessary. This study aims to develop an Internet of Things (IoT)-based sensor for real-time detection, alerting and notification of campus building stakeholders, utilizing IoT, wireless sensor networks (WSN) and a cloud database. The IoT-based sensor incorporates temperature, humidity, smoke, and flame sensors, with data stored in ThingSpeak, serving as a sensor visualization hub. Five simulations, based on fire ignition probabilities and building attributes, were conducted to assess the prototype's functionality, using geospatial tools for data analysis. Establishing a smart campus has become appealing with essential technologies such as IoT, WSN, cloud computing, and AI, leading to innovations in fire detection and safety measures integration. However, ensuring campus safety requires state-of-the-art sensors integrated with IoT technology and spatial-based analysis techniques. This study not only focuses on sensor development but also employs geospatial software analysis for spatial data quantification and identification of key sensor characteristics, aiding future analysis.
Nexus Approach for a Sustainable Environment: From Individual Modeling Approaches to Digital Twins
Anthony Lehmann
University of Geneva
Switzerland
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Brief Bio
Prof. Anthony Lehmann is a specialist in the field of Species Distribution Modeling (SDM). He pioneered the development of GRASP, the first package enabling spatial predictions based on point observations of plant and animal distributions. Since its publication, GRASP has been cited over 400 times and applied across diverse terrestrial and aquatic ecosystems, contributing to more than 20 co-authored publications. GRASP laid the foundation for subsequent tools like MAXENT, BIOMOD, and CARET, and was instrumental in addressing the challenge of presence-only data in SDM.
More recently, Prof. Lehmann has focused on leveraging hydrological modeling to inform decision-making processes. He initiated and coordinated the FP7 enviroGRIDS project, a four-year endeavor involving over 100 scientists aimed at bridging the gap between scientific data and decision-making in the Black Sea catchment. This project advanced Earth Observation capacity building, data-sharing practices, and the calibration of a large, complex hydrological model for the region.
Prof. Lehmann's recent research emphasizes spatially explicit assessments of ecosystem services. He coordinated the H2020 ERA-PLANET/GEOEssential project (2017–2021), which developed geoprocessing workflows to link Earth Observation data with environmental policy indicators using Essential Variables. Building on this expertise, he led the Swiss National Fund project SWATCH (2017–2020), focusing on eco-hydrological modeling of Swiss rivers, and is currently involved in the ValPar.CH project (2020–2023), exploring ecosystem services, biodiversity, and ecological infrastructures in and around Swiss regional parks.
Abstract
Evidence-based environmental management relies heavily on high-quality, accessible geospatial data. Despite the widespread adoption of Open Data policies across Europe, challenges persist in discovering and accessing data across temporal and spatial scales due to technical, political, economic, and cultural barriers. Moreover, the complexity of natural systems generates vast and often unmanageable amounts of data.
To address these challenges, the concept of Essential Variables (EVs) has been pivotal. Initially developed for Essential Climate Variables (ECVs), this framework has been adapted to define Essential Biodiversity Variables (EBVs) and, more recently, extended to the socio-ecological Earth system within a European project. Comprehensive monitoring of the Earth system requires robust Spatial Data Infrastructures (SDIs) to facilitate the dissemination of metadata and, ideally, analysis-ready data. However, the complexity and costs associated with SDI implementation—such as those observed in INSPIRE and GEOSS initiatives—pose significant obstacles, particularly in achieving seamless machine-to-machine data access through interfaces like APIs.
In recent years, advancements in geospatial workflows have shifted the focus toward defining and sharing complex analyses. Standard programming languages like Python and R, coupled with open platforms like GitHub, have significantly improved workflow reproducibility and accessibility. Additionally, the availability of diverse computing backends—from personal computers to cloud-based systems—has enabled scalable geospatial analyses.
We illustrate these developments with two case studies in Switzerland. The first involves defining the Swiss national ecological infrastructure through integrated workflows that combine species distribution modeling and ecosystem service assessments to prioritize landscapes, identifying the top 30% for conservation. The second focuses on hydrological modeling using the Soil and Water Assessment Tool (SWAT) to transform daily weather data into river water quality and quantity outputs.
Despite their success, these examples highlight opportunities for further integration within a Nexus framework, connecting Climate-Food-Water-Energy-Ecosystem domains to identify trade-offs and synergies in addressing complex environmental issues. Ultimately, the integration of these approaches into Digital Twins for the environment represents a transformative step toward converting essential variables into actionable insights for informed environmental decision-making.
Keynote Lecture
Mihai Daniel Nita
Transilvania University of Brasov
Romania
Brief Bio
Available Soon.