Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/26527
Title: Development of Water Quality System in Residential Area
Authors: A Bakar, Dr. Mohd Izhar
Uddin, Syed Mohammed
Azman, Muhammad Afiq Syahmi
Keywords: NodeMCU, Thingspeak, IoT, GPS, SoC
Issue Date: 9-Jan-2023
Abstract: Water problems in the residential area happened quite often a few years back until now but remain unsettled, especially regarding low water pressure. The water provider purely needs a significant water monitoring and alert system to overcome this issue. Over the past years, Selangor Water Management Sdn Bhd has received 8,302 water theft complaints that lead to low water pressure and issued 997 request notices. The newspaper also reported that residents of Taman Sri Endah, Sri Petaling are frustrated over low water pressure in their neighborhood affecting about 40 houses. This project was made to detect the water problem by collecting data on the water flow rate and water existence at the home water meter. This project used liquid sensors such as water flow and presence sensors, NodeMCU Esp8266, GPS module, IoT platform, and Thingspeak. A Gmail notification email was modified to alert the water provider if the system detects any problem regardings the water parameter measured. A google maps was interfaced with the GPS module to locate the affected system’s node. Thingspeak was used as an online monitoring interface to illustrate graphs for water parameters and save the data in cloud storage. This project communicates well between hardware and software where it detects and uploads the data smoothly from NodeMCU to Thingspeak. The data has been illustrated well with the support of cloud storage to store data of the readings. The system can alert the water provider when it detects a problem with a Gmail notification complete with the location of the affected. This project is more focused on monitoring water quality and awareness of problems in providing water to customers is carried out.
Description: UniKL BMI
URI: http://hdl.handle.net/123456789/26527
Appears in Collections:Conference Papers



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