MUMBAI, India, Oct. 12 -- Intellectual Property India has published a patent application (202641118341 A) filed by Ms. Nalini B Massistant Professor; Rns Institute Of Technology, Bengaluru.; Gagan Uday Panditrncs; Divya B V Rncs; Mr. Manjunath G Sassistant Professor; Poorvik Prncs; and Lohith L Prncs on October 03, 2026, for Econexus: An Ai- And Iot-Enabled Smart Waste Management System With Intelligent Waste Classification, Route Optimization, And Citizen Reward Platform For Sustainable Smart Cities.
Inventors include Ms. Nalini B M Assistant Professor; Mr. Manjunath G Sassistant Professor; Divya B V Rncs; Lohith L Prncs; Gagan Uday Panditrncs; and Poorvik Prncs.
The application for the patent was published on October 09, 2026, under issue no. 41/2026.
Abstract: The present invention relates to EcoNexus, an AI- and IoT-enabled smart waste management system that integrates physical waste detection, image-based machine learning classification, sensor-assisted classification, semi-automated waste segregation, centralized data processing, collection management, route planning, real-time collector tracking, and citizen rewards within a unified platform. The proposed system comprises a waste segregation unit equipped with an infrared sensor, moisture sensor, metal proximity sensor, camera, Arduino Uno, Raspberry Pi 3, and servo-operated mechanical sorting mechanism. The infrared sensor detects the presence of waste, while the moisture and metal sensors provide physical characteristics of the waste. A camera captures an image of the detected waste, and a lightweight MobileNetV2-based TensorFlow Lite machine learning model deployed on the Raspberry Pi performs image-based classification. The current classification framework categorizes waste into three categories: wet, dry, and metal. Sensor information and machine-learning output are combined through a decision-fusion process to determine the final waste category. The resulting classification is provided to the sorting mechanism, which positions a servo-controlled diverter to direct the waste toward the corresponding collection container. The Raspberry Pi further acts as an edge-processing and IoT gateway device for transmitting classification and sensor information to a centralized Node.js/Express backend. The backend stores and processes the data using MongoDB and provides APIs for the citizen mobile application, collector mobile application, and administrator web dashboard. The citizen application supports pickup requests, collection-status monitoring, waste history, complaints, segregation-related rewards, and reward redemption. The collector application provides assigned collection tasks, route information, navigation support, collection-status updates, and location sharing. The administrator dashboard provides centralized monitoring of users, collectors, pickups, complaints, routes, rewards, waste information, and system activity. The integrated architecture provides a unified approach to intelligent waste classification, collection coordination, citizen participation, and administrative monitoring, while providing a modular platform capable of future expansion.
Disclaimer: Curated by HT Syndication.
