Team Members: Dr.P.Subashini, CMLI Coordinator,Professor of Computer Science.
Dr.M.Krishnaveni, CMLI Co-coordinator, Assistant Pofessor(SG), Departemnt of Computer Science.
Ms.E.Rathipriya,Technical Assistant,CMLI.
Ms.S.Srina, II M.Sc.CS.

Project Summary:

The Real-Time Error Identification and Nutrient Analysis System is designed to enhance the Solwearth Organic Waste Converter by integrating video processing and sensor technology for automated monitoring and analysis. The project aims to eliminate the need for manual inspection by providing real-time updates on the system's status through an Android application. A web camera continuously captures video of the decomposition process, and HSV color space-based image processing is used to analyze the waste conversion status. The Arduino Uno serves as the central controller, collecting real-time data from sensors. Load cell sensors measure the waste weight before and after decomposition, while an NPK sensor evaluates the manure’s nutrient content by measuring Nitrogen (N), Phosphorus (P), and Potassium (K) levels. The collected data, including weight measurements, decomposition status, and nutrient values, is sent to a ThingSpeak dashboard for remote monitoring and storage. Users can track the system's real-time status via an Android application, ensuring efficient waste processing and nutrient analysis.