2025
doi: 10.12720/jait.16.11.1501-1510
Enhanced Urban Infrastructure Management: IoT-Based Smart Manhole Monitoring System
Saniya Ansari1,*
,
Kanchan Vaidya1 ,
Ankush Kadu1 ,
Deshinta Arrova Dewi2 ,
Farook Sayyad3 ,
Shabnam Sayyad4 ,
Vijayakumar Varadarajan5
- 1Department of Elelctronics and Tele Communication Engineering, Ajeenkya D Y Patil School of Engineering, Pune, India
- 2Center for Data Science and Sustainable Technologies, INTI International University, Nilai, Malaysia
- 3Department of Mechanical Engineering, Ajeenkya D Y Patil School of Engineering, Pune, India
- 4Department of Computer Engineering, AISSMS College of Engineering, Pune, India
- 5Department of Computer Engineering, Ajeenkya D Y Patil University, Pune, India
- Manuscript receivedNovember 20, 2024
- revisedJanuary 23, 2025
- acceptedFebruary 19, 2025
- publishedNovember 7, 2025
Abstract
A smart city strives to enhance society by offering cleaner and improved amenities, with smart underground infrastructure pivotal to achieving this goal. Monitoring the drainage system is essential to maintaining a clean and healthy environment. Manhole monitoring is inefficient and slow, leading to delays in addressing drainage issues. The suggested system offers a low-cost, low-maintenance alternative, which plots manhole coordinates using Global Positioning System (GPS). Traffic is alerted to impending manholes to avoid them, and information is updated every five minutes. The machine learning algorithm utilized by the system for assessing every state is based on Q-learning. The admin office receives a notification outlining the problem whenever there are sudden changes to the settings. By enhancing manhole maintenance, this strategy will have a significant positive social impact. To guarantee efficacy, a test dataset will be used to test and evaluate the Q-Learning Reinforcement Learning algorithm based on policies and rewards.
Keywords
- Global Positioning System (GPS)
- manhole
- Q-learning
- thinkspeak
- twilio
- water level
- product innovation
- process innovation
How to Cite
Saniya Ansari, Kanchan Vaidya, Ankush Kadu, Deshinta Arrova Dewi, Farook Sayyad, Shabnam Sayyad, and Vijayakumar Varadarajan, "Enhanced Urban Infrastructure Management: IoT-Based Smart Manhole Monitoring System," Journal of Advances in Information Technology, vol. 16, no. 11, pp. 1501-1510, 2025. https://doi.org/10.12720/jait.16.11.1501-1510
Copyright & License
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
