PROTOTYPING AN INTEGRATED IOT-BASED REAL-TIME SEWER MONITORING SYSTEM USING LOW-POWER SENSORS

Abstract

Improper monitoring of sewage networks may raise various issues such as overflows, pipe blockages, theft of manhole covers, leading to flooding and pollution, infrastructure damage, vehicles accidents, injury, and even death from falling into open manholes. The key objective of this research was to examine different elements and create a prototype architecture for a real-time sewer monitoring system. Implementation of the architecture involved constructing a data gathering station and experimenting with various wireless sensing devices to assess the precision of the sensors. In addition, the study sought to design a geographic information system that integrates algorithms capable of identifying sewer overflow, blocked pipes, and the presence of manhole covers. The performance of Sharp GP2Y0A41SK0F infrared, TF-Luna Benewake LiDar, TOF400 VL53L1X laser, JSN-SR04T ultrasonic distance sensors was tested in terms of their ability to monitor water level and manhole cover. Tests revealed the most favorable results in TOF400 VL53L1X at distances between 0.2 and 1.0 m (presumed distance to the manhole cover) with a standard deviation of 0.13–0.24, and in TF-Luna Benewake at distances between 1.0 and 5.0 m (presumed distance to the chamber bottom) with a standard deviation of 0.44–1.15. The deviation analysis has yielded equations that can be utilized to provide rough estimates of the accuracy levels of the aforementioned sensors, based on the measured distance. Additionally, the FC-28 analog and YL-63 infrared sensors were evaluated for detecting pipe blockages, with the YL-63 being more suitable. The outcomes of this study furnish valuable insights that can aid in achieving sustainable resolutions for issues related to sewer monitoring.