Development of IoT‐based real‐time drainage monitoring system

Panner Selvam, Shatiish (2022) Development of IoT‐based real‐time drainage monitoring system. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)

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Abstract

Nowadays, technologies are rapidly advancing in this world, including the type of monitoring system used. In addition, the evolution of the Internet of Things (IoT) has made people’s life more convenient and practical where it supports everyone to be connected to any things, and anywhere, via the Internet. It has been reported that the current drainage system in most of the countries is still using manpower which may expose them to many hazards and accidents. Therefore, monitoring the status of the drainage from time to time is very crucial to avoid accidents to happen. Several researchers have focused on developing drainage monitoring systems, however, most of the system are using GSM module to send the monitored data to the control room which introduced latency. Therefore, the purpose of this work is to develop an IoT-based Real-Time Drainage Monitoring System to monitor the drainage system. In this work, the proposed system is designed to detect the depth of the water, the level of gas concentration at the drainage area, and the flow rate of the water flow in the drain using a laser sensor, gas sensor, and flow meter sensor, respectively. Besides, the system is also equipped with a GPS module to locate the location of the monitored area. For monitoring purposes, the system is integrated with the Blynk server application where all of the monitored data including the depth of the water, gas concentration, and the flow rate of water in the drain will be stored in the cloud server via WiFi connection. In addition, a notification will be sent out to the in-charge person if any of the sensors exceed the threshold value. The proposed system has been tested and the results show that the system has high reliability and measured and the actual reading has high accuracy with a margin error of 3%.

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