Real-time Monitoring System for Safe Drinking Water Safety Using IoT and Cloud Computing

This research develops an Internet of Things-based system for continuously monitoring and analyzing drinking water quality. The system's main purpose is to provide a reliable and efficient solution to the crucial problem of constantly monitoring and analyzing drinking water to reduce rising con...

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Bibliographic Details
Published in:2024 International Conference on Advances in Data Engineering and Intelligent Computing Systems (ADICS) pp. 1 - 6
Main Authors: Raman, Ramakrishnan, Deshpande, Ashish
Format: Conference Proceeding
Language:English
Published: IEEE 18.04.2024
Subjects:
Cloud computing
Cloud Storage
IoT
Real-Time Monitoring
Scalability
Sensors
Temperature distribution
Temperature measurement
Temperature sensors
User interface
User interfaces
Water quality
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Summary:This research develops an Internet of Things-based system for continuously monitoring and analyzing drinking water quality. The system's main purpose is to provide a reliable and efficient solution to the crucial problem of constantly monitoring and analyzing drinking water to reduce rising concerns about its health. This technology is suggested for real-time analysis of drinking water quality. The NodeMCU platform, an analog TDS sensor, and a waterproof temperature sensor are used to measure various water quality parameters. The sensor information is sent to a cloud server, where it can be stored and analyzed. The system uses advanced cloud computing and data analytics to store, analyze, and evaluate the collected information. These techniques can identify anomalies and patterns and provide valuable insights into water quality. Predictive models are built using historical data to predict changes in water quality and identify risks. An accessible webpage interface stored in the cloud makes the information analyzed and insights available to users. Users such as water authorities, policymakers, and people can view the current water quality status, detect data from past data, and receive alerts in case of abnormal conditions. Contributing to better water management and public health, it provides a secure and efficient method for monitoring and analyzing drinking water quality.
DOI:10.1109/ADICS58448.2024.10533575