Comprehensive IoT-Based Water Management System: Cloud Integration for Residential Conservation

In an era where water conservation is increasingly critical, this paper unveils a groundbreaking IoT-based system that revolutionizes water management through smart automation. By harnessing cutting-edge technologies such as the ESP32 microcontroller, this system seamlessly integrates with cloud services to deliver unparalleled efficiency in water monitoring and control. Equipped with an ultrasonic sensor for precise water level measurements and a rain sensor for immediate leak detection, the system stands at the forefront of innovation in water resource management. Designed to automatically adjust water levels and respond swiftly to leaks, this system minimizes waste and ensures optimal water use with remarkable precision. The advanced cloud infrastructure supports real-time data logging and analysis, facilitated by MQTT for agile data transmission and HTTP/REST APIs for smooth system integration. MongoDB’s robust database management enhances the system’s ability to handle and interpret vast amounts of data effectively. The user experience is further elevated through a dynamic interface built with React Native, offering a seamless and intuitive interaction across multiple devices. This pioneering solution not only advances smart water management technology but also highlights its transformative potential for conservation efforts. By combining IoT innovation with intuitive software, the system sets a new standard for efficient and sustainable water management in residential settings.

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Publication Details

Published
2024-10-01
DOI
https://doi.org/10.1109/r10-htc59322.2024.10778751
Primary Topic
Water Quality Monitoring Technologies
Type
article
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article

Comprehensive IoT-Based Water Management System: Cloud Integration for Residential Conservation

Nur Azhani Abd Razak, Ahmad Anwar Zainuddin, Mohamad Syafiq Asyraf Bharudin, Nik Nor Muhammad Saifudin et al.
Water Quality Monitoring Technologies
article

Comprehensive IoT-Based Water Management System: Cloud Integration for Residential Conservation

Nur Azhani Abd Razak, Ahmad Anwar Zainuddin, Mohamad Syafiq Asyraf Bharudin, Nik Nor Muhammad Saifudin, Aliah Maisarah Roslee, Muhamad Hazrin Fahmi Abd Halim
article en

Abstract

In an era where water conservation is increasingly critical, this paper unveils a groundbreaking IoT-based system that revolutionizes water management through smart automation. By harnessing cutting-edge technologies such as the ESP32 microcontroller, this system seamlessly integrates with cloud services to deliver unparalleled efficiency in water monitoring and control. Equipped with an ultrasonic sensor for precise water level measurements and a rain sensor for immediate leak detection, the system stands at the forefront of innovation in water resource management. Designed to automatically adjust water levels and respond swiftly to leaks, this system minimizes waste and ensures optimal water use with remarkable precision. The advanced cloud infrastructure supports real-time data logging and analysis, facilitated by MQTT for agile data transmission and HTTP/REST APIs for smooth system integration. MongoDB’s robust database management enhances the system’s ability to handle and interpret vast amounts of data effectively. The user experience is further elevated through a dynamic interface built with React Native, offering a seamless and intuitive interaction across multiple devices. This pioneering solution not only advances smart water management technology but also highlights its transformative potential for conservation efforts. By combining IoT innovation with intuitive software, the system sets a new standard for efficient and sustainable water management in residential settings.

International Islamic University Malaysia (MY)
Clean water and sanitation
Openalex Percentile: Top 78%
Water Quality Monitoring Technologies
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Comprehensive IoT-Based Water Management System: Cloud Integration for Residential Conservation — Nur Azhani Abd Razak, Ahmad Anwar Zainuddin, et al. · (2024) | TGRS Research Map | TGRS