Community Environmental Health Monitoring: Solar-Powered IoT Air Quality Assessment for Public Health Decision-Making
Authors
Center for Telecommunication and Innovation (CeTRI), Fakulti Teknologi dan Kejuruteraan Elektronik dan Komputer (FTKEK), Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100, Durian Tunggal, Melaka (Malaysia)
Center for Telecommunication and Innovation (CeTRI), Fakulti Teknologi dan Kejuruteraan Elektronik dan Komputer (FTKEK), Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100, Durian Tunggal, Melaka (Malaysia)
Center for Telecommunication and Innovation (CeTRI), Fakulti Teknologi dan Kejuruteraan Elektronik dan Komputer (FTKEK), Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100, Durian Tunggal, Melaka (Malaysia)
Center for Telecommunication and Innovation (CeTRI), Fakulti Teknologi dan Kejuruteraan Elektronik dan Komputer (FTKEK), Universiti Teknikal Malaysia Melaka (UTeM), Hang Tuah Jaya, 76100, Durian Tunggal, Melaka (Malaysia)
Faculty of Hotel and Tourism Management, Universiti Teknologi MARA, Melaka (Malaysia)
Article Information
DOI: 10.47772/IJRISS.2025.910000144
Subject Category: Environment
Volume/Issue: 9/10 | Page No: 1701-1715
Publication Timeline
Submitted: 2025-10-06
Accepted: 2025-10-14
Published: 2025-11-06
Abstract
Environmental health disparities notably affect communities that lack access to real-time air quality data, which is crucial for making informed public health decisions. This study develops and evaluates a solar-powered IoT environmental health monitoring system to address environmental health information inequities through sustainable, community-centered implementation. Temperature-humidity sensor, barometric pressure sensor, gas sensor, and optical dust sensor are integrated with ESP32 microcontroller and Things Board IoT platform, powered by solar panels, for energy autonomy. Mobile interface provide community members with real-time environmental data and local air quality information. Field deployment in Malacca, Malaysia, showed successful continuous operation with a highly cost-effective system that saved money compared to commercial alternatives and had zero operational electricity expenses due to solar autonomy. Results showed large multi-dimensional outcomes, including increased community environmental health awareness, social cohesion supporting collaborative action, and strong connection with six Sustainable Development Goals (SDG). The implementation greatly improved community access to real-time air quality data, addressing environmental health inequities and laying the groundwork for community-based activism. Environmental sustainability assessment found little ecological footprint with renewable energy operation supporting climate mitigation through fossil fuel displacement and adaptation through community monitoring capability. This study offers a reproducible, economically viable paradigm for technical innovation, community empowerment, environmental preservation, and sustainable development. The findings affect environmental health policy, community-based surveillance expansion, and environmental justice through accessible monitoring technology.
Keywords
Community environmental health monitoring
Downloads
References
1. Jo, J., Jo, B., Kim, J., & Choi, I. (2020). Implementation of IoT-based air quality monitoring system for investigating particulate matter (PM10) in subway tunnels. International Journal of Environmental Research and Public Health, 17(15), 5429. [Google Scholar] [Crossref]
2. Peixe, J. and Marques, G. (2024). Low-cost IoT-enabled indoor air quality monitoring systems: a systematic review. Journal of Ambient Intelligence and Smart Environments, 16(2), 167-180. [Google Scholar] [Crossref]
3. Saravanakumar, S., A, B., P, D., Janani, T., & Saravana, I. (2024). Solar energy powered advanced smart streetlight for remote areas. Int Res J Adv Engg Hub, 2(04), 1003-1009. [Google Scholar] [Crossref]
4. Li, Y., Sun, Z., Huang, M., Sun, L., Liu, H., & Lee, C. (2024). Self‐sustained artificial internet of things based on vibration energy harvesting technology: toward the future eco‐society. Advanced Energy and Sustainability Research, 5(11). [Google Scholar] [Crossref]
5. Dosymbetova, G., Mekhilef, S., Orynbassar, S., Kapparova, A., Saymbetov, A., Nurgaliyev, M., … & Koshkarbay, N. (2023). Neural network based active cooling system with IoT monitoring and control for lcpv silicon solar cells. IEEE Access, 1-1. [Google Scholar] [Crossref]
6. Múnera, D., Tobón, D., Aguirre, J., & Gómez, N. (2021). IoT-based air quality monitoring systems for smart cities: a systematic mapping study. International Journal of Electrical and Computer Engineering (IJECE), 11(4), 3470. [Google Scholar] [Crossref]
7. Ng, W. and Dahari, Z. (2020). Enhancement of real-time iot-based air quality monitoring system. International Journal of Power Electronics and Drive Systems (IJPEDS), 11(1), 390. [Google Scholar] [Crossref]
8. Shashank, G., Lohit, V., Venkata, G., & Vishal, S. (2022). IoT Based Air Quality Monitoring System. Technoarete Transactions on Internet of Things and Cloud Computing Research, 2(1). [Google Scholar] [Crossref]
9. Jose, A., Abraham, C., Soman, A., Ajumal, T., & Shibu, A. (2024). IoT based solar powered air purifier with air quality monitoring system. E3s Web of Conferences, 529, 04016. [Google Scholar] [Crossref]
10. Mondal, D. and Banerjee, A. (2022). Implementation of IoT for air quality surveillance. IJEAST, 7(8), 151-159. [Google Scholar] [Crossref]
11. Zhou, M., Abdulghani, A., Imran, M., & Abbasi, Q. (2020). Internet of things (iot) enabled smart indoor air quality monitoring system., 89-93. [Google Scholar] [Crossref]
12. Taştan, M. (2022). A low-cost air quality monitoring system based on internet of things for smart homes. Journal of Ambient Intelligence and Smart Environments, 14(5), 351-374. [Google Scholar] [Crossref]
13. Jahandar, M., Kim, S., & Lim, D. (2021). Indoor organic photovoltaics for self‐sustaining iot devices: progress, challenges and practicalization. Chemsuschem, 14(17), 3449-3474. [Google Scholar] [Crossref]
14. Lin, L., Chen, Z., Wang, Y., & Jiang, L. (2022). Improving anomaly detection in IoT-based solar energy system using smote-pso and svm model. 360, 123-131. [Google Scholar] [Crossref]
Metrics
Views & Downloads
Similar Articles
- Methane Emissions from Municipal Solid Waste - Case Study in Cai Rang District, Can Tho City, Vietnam
- Youth Activism, Intentional Integration of Policies to Raise Awareness on Climate Change Action among the Youth
- Breathing Spaces: Environmental & User Experience in Dhanmondi and Zigatola Multistoried Apartments, Dhaka, Bangladesh
- Effects of Solid Waste Disposal on Soil Quality in Makurdi Metropolis, Benue State, Nigeria
- Environmental Impact of Artisanal and Small-Scale Gold Mining in Borgu Local Government Area