IoT and Real-time Data Analytics Optimize Greywater Recycling
Chitra Sabapathy Ranganathan, Virendra Singh Thakur, Ramakrishnan Raman, S. Sujatha, Swapnil Parikh
Abstract
Greywater recycling systems are an efficient solution to the problems of water shortages and unsustainable resource management. This research proposes a new method for greywater recycling that uses cloud servers and other IoT devices to improve the recycling process dramatically. Using IoT-enabled sensors in strategically placed locations inside greywater recycling units is the complete approach proposed by the analysis. These sensors, which gather real-time data, continuously monitor significant features such as water quality indicators, flow rates, temperatures, and other consumption patterns. This information may be transmitted, stored, and analyzed quickly with a seamless connection to the cloud server. The cloud server infrastructure is essential for the efficient operation of the system. As a central server, it allows for consolidated data and remote monitoring. Trends, outliers, and inefficient processes in operations may all be seen using real-time data analysis. With this information, decisions may be made now, facilitating continuous water purification and distribution system optimization. The method offers a complete, data-driven framework to improve system resilience, efficiency, and water use. This proposed system suggests the cutting-edge technology and improve sustainable water management methods.