| Issue |
EPJ Web Conf.
Volume 367, 2026
Fifth International Conference on Robotics, Intelligent Automation and Control Technologies (RIACT 2026)
|
|
|---|---|---|
| Article Number | 03008 | |
| Number of page(s) | 9 | |
| Section | Smart and Sustainable Systems | |
| DOI | https://doi.org/10.1051/epjconf/202636703008 | |
| Published online | 29 April 2026 | |
https://doi.org/10.1051/epjconf/202636703008
IoT based Portable Manhole Gas Sensing System
1 School of Electronics Engineering, Vellore Institute of Technology, Chennai, Tamil Nadu, India
2 Centre for Healthcare Advancement, Innovation and Research, Vellore Institute of Technology, Chennai, Tamil Nadu, India
3 Department of Electronics and Communication Engineering, School of Engineering and Technology, CHRIST University, Bengaluru, Karnataka, India
* Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.
Published online: 29 April 2026
Abstract
Maintenance of sewage systems requires workers to enter confined manholes, where hazardous gases can build up. These toxic, flammable gases create a serious safety risk. To address this problem, a portable gas monitoring system based on IoT technology was designed for real time sensing and observation. The proposed system comprises of MQ- 4, MQ-6, and MQ-7 gas sensors, along with a DS18B20 temperature sensor, all interfaced to an ESP32 microcontroller. The data is then transmitted to a cloud platform built with Node.js and MongoDB, enabling real-time monitoring. Whenever the gas concentrations exceed the safety limits, alerts are triggered to enable early action. The experimental results show an accuracy of approximately ±2% compared to standard measurement instruments, with the latency less than 500 ms. Early warning of dangerous gas levels can significantly reduce risks during sewage maintenance.
© The Authors, published by EDP Sciences, 2026
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

