IoT-Enabled Waste Management Solutions: A Cross-System Analysis for Sustainable
Keywords:
Smart waste management, Internet of Things(IoT), Hybrid IoT model, Urban-rural comparison, Sustainable waste managementAbstract
The global solid waste crisis, projected to reach 3.88 billion tons annually by 2050, requires efficient, scalable, and inclusive management solutions. Traditional systems are inefficient, costly, and environmentally harmful, while IoT-enabled approaches offer real-time monitoring, predictive analytics, and optimized routing—yet they remain predominantly urban-focused, with rural and low-resource areas underserved and lacking direct comparative studies. This research bridges this gap through a systematic cross-system analysis of recent publications, synthesizing IoT technologies (sensors, LoRaWAN/NB-IoT, AI integration), urban and rural applications, pilots, efficiency outcomes, costs, sustainability impacts, and barriers. Findings show urban systems deliver 30–40% efficiency gains, reduced emissions, and enhanced recycling via dense networks and smart city integration, while rural adaptations (solar-powered bins, edge computing) achieve only 15–25% improvements due to connectivity gaps, power limitations, and scalability issues. The study’s novelty is the proposed hybrid model architecture, which integrates urban AI sophistication (predictive analytics, blockchain security) with rural resilience features (solar energy, edge processing, context-aware switching) to enable adaptive performance across contexts. This unified framework demonstrates potential for 25–35% overall efficiency gains, stronger data security, and equitable adoption through modular, low-cost designs and community interfaces. Outcomes indicate significant potential to reduce landfill emissions, advance circular economy principles, and support SDGs 11 and 12, provided future efforts prioritize rural field trials, policy incentives, and advanced AI integration for truly inclusive, sustainable waste management worldwide.
References
Addas, A., Khan, M. N., & Naseer, F. (2024). Waste management 2.0 leveraging internet of things for an efficient and eco-friendly smart city solution. *PLoS ONE*, 19(7), e0307608. https://doi.org/10.1371/journal.pone.0307608
Afkarien, A. K., Astawa, I. G. P., & Nadziroh, F. (2025). Development of IoT-based smart waste management systems for organic and non-organic waste in smart cities. *The Indonesian Journal of Computer Science*, 14(2).
Ahmed, K., Dubey, M. K., Kumar, A., & Dubey, S. (2024). Artificial intelligence and IoT driven system architecture for municipality waste management in smart cities: A review. *Measurement: Sensors*, 36, 101395. https://doi.org/10.1016/j.measen.2024.101395
Ajibola, O. A., & Ogbolumani, O. A. (2024). Smart battery storage integration in an IoT-based solar-powered waste management system. *Journal of Digital Food, Energy & Water Systems*, 5(2).
Al Yarubi, K. S., Khairy, S. O. F., Hossain, S. M. E., & Hayder, G. (2025). Internet of Things-driven waste management: Paving the way for sustainable smart cities. *Processes*, 13(4), 1140. https://doi.org/10.3390/pr13041140
Alourani, A., Ashraf, M. U., & Aloraini, M. (2025). Smart waste management and classification system using advanced IoT and AI technologies. *PeerJ Computer Science*, 11, e2777. https://doi.org/10.7717/peerj-cs.2777
Boostani, F., Golzary, A., Huisingh, D., & Skitmore, M. (2024). Mapping the future: Unveiling global trends in smart waste management research. *Results in Engineering*, 24, 103485. https://doi.org/10.1016/j.rineng.2024.103485
Brighente, A., Conti, M., Di Renzone, G., Peruzzi, G., & Pozzebon, A. (2023). Security and privacy of smart waste management systems: A cyber–physical system perspective. *IEEE Internet of Things Journal*, 11(5), 7309–7324. https://doi.org/10.1109/JIOT.2023.3322323
Devi, A., Singh, N., Thandra, N., Gupta, N., Salman, Z. N., & Natarajan, K. (2025). AI and IoT-enabled smart urban waste management system for efficient collection, segregation, and disposal. *E3S Web of Conferences*, 619, 03002. https://doi.org/10.1051/e3sconf/202561903002
Fidje, E., Haddara, M., & Langseth, M. (2023). Sustainable smart waste management adoption challenges in developing countries. *Procedia Computer Science*, 219, 905–914. https://doi.org/10.1016/j.procs.2023.01.366
Gaurav, A., Gupta, B. B., Arya, V., Attar, R. W., Bansal, S., Alhomoud, A., & Chui, K. T. (2025). Smart waste classification in IoT-enabled smart cities using VGG16 and Cat Swarm Optimized random forest. *PLoS ONE*, 20(2), e0316930. https://doi.org/10.1371/journal.pone.0316930
Henaien, A., Elhadj, H. B., & Fourati, L. C. (2024). A sustainable smart IoT-based solid waste management system. *Future Generation Computer Systems*, 157, 587–602. https://doi.org/10.1016/j.future.2024.04.022
Hussain, I., Elomri, A., Kerbache, L., & El Omri, A. (2024). Smart city solutions: Comparative analysis of waste management models in IoT-enabled environments using multiagent simulation. *Sustainable Cities and Society*, 103, 105247. https://doi.org/10.1016/j.scs.2024.105247
Ibrahim, I. A., & Baballe, M. A. (2024). A comprehensive review of how the smart waste management system works. *Journal Homepage: https://gjrpublication.com/gjrecs*, 4(5).
Idoko, D. O., Imarenakhue, W. M., Olade, A. D., Oppong, R. A., Bah, M. B., Elue, H. C., & Fadeke, A. A. (2024). Development of smart waste management technologies using IoT solutions for environmental sustainability in urban infrastructure planning. *International Journal of Innovative Science and Research Technology*, 9(12), 1–8.
Ishaq, A., Mohammad, S. J., Bello, A.-A. D., Wada, S. A., Adebayo, A., & Jagun, Z. T. (2025). Smart waste bin monitoring using IoT for sustainable biomedical waste management. *Environmental Science and Pollution Research*, 32(32), 19434–19449. https://doi.org/10.1007/s11356-025-33032-5
Lakhouit, A. (2025). Revolutionizing urban solid waste management with AI and IoT: A review of smart solutions for waste collection, sorting, and recycling. *Results in Engineering*, 104018. https://doi.org/10.1016/j.rineng.2025.104018
Nwokediegwu, Z. Q. S., Ugwuanyi, E. D., Dada, M. A., Majemite, M. T., & Obaigbena, A. (2024). AI-driven waste management systems: A comparative review of innovations in the USA and Africa. *Engineering Science & Technology Journal*, 5(2), 507–516.
Olawade, D. B., Fapohunda, O., Wada, O. Z., Usman, S. O., Ige, A. O., & Ajisafe, O. (2024). Smart waste management: A paradigm shift enabled by artificial intelligence. *Waste Management Bulletin*, 2(2), 244–263. https://doi.org/10.1016/j.wmb.2024.02.002
Palagan, C. A., Joe, S. S. A., Mary, S. J. J., & Jijo, E. E. (2025). Predictive analysis-based sustainable waste management in smart cities using IoT edge computing and blockchain technology. *Computers in Industry*, 166, 104234. https://doi.org/10.1016/j.compind.2024.104234
Prova, N. N. I. (2024). Garbage intelligence: Utilizing vision transformer for smart waste sorting. *2024 Second International Conference on Intelligent Cyber Physical Systems and Internet of Things (ICoICI)*, 1213–1219. https://doi.org/10.1109/ICoICI61547.2024.10700345
Rahman, M. A., Tan, S. W., Asyhari, A. T., Kurniawan, I. F., Alenazi, M. J. F., & Uddin, M. (2024). IoT-enabled intelligent garbage management system for smart city: A fairness perspective. *IEEE Access*, 12, 82693–82705. https://doi.org/10.1109/ACCESS.2024.3398523
Sheng, T. J., Islam, M. S., Misran, N., Baharuddin, M. H., Arshad, H., Islam, M. R., Chowdhury, M. E. H., Rmili, H., & Islam, M. T. (2020). An internet of things based smart waste management system using LoRa and tensorflow deep learning model. *IEEE Access*, 8, 148793–148811. https://doi.org/10.1109/ACCESS.2020.3015827
Singh, J., El-Sappagh, S., Ali, F., Goyal, S. B., & Kumar, M. (2025). Smart waste management: A systematic review and scientometric analysis of artificial intelligence applications. *Environment, Development and Sustainability*, 1–31. https://doi.org/10.1007/s10668-025-04832-5
Suhardono, S., Lee, C.-H., Phan, T. T. T., & Suryawan, I. W. K. (2025). Resident action in smart waste management during landfill disclosure transition: Insights from Yogyakarta's smart city initiatives. *Cleaner Production Letters*, 8, 100093. https://doi.org/10.1016/j.clpl.2025.100093
Sutikno, T., Ardiansyah, A., Pujiyanta, A., & Handayani, L. (2024). Artificial intelligence technologies in urban smart waste management. *High-tech and Innovative Series*, 1, 55–66.
William, P., Patil, J. M., Panda, S., Venugopal, A., Vidyullatha, P., Kumar, N. M., & Jandwani, A. (2024). An optimized framework for implementation of smart waste collection and management system in smart cities using IoT based deep learning approach. *International Journal of Information Technology*, 16(8), 5033–5040. https://doi.org/10.1007/s41870-024-02098-2
