Title: AEROBINS: Intelligent Odor-Controlled Waste Management using IoT and Machine Learning


Authors: Rishita Soni, Shreya Mishra, Shailendra Charan, Sarvesh Gore, Nidhi Nigam


Published in: Volume 3 Issue 1 Jan June 2026, Page No. 181-187


DOI: 10.63844/IJAITR.v3.i1.2026.181-187 cite


Keywords: Smart Waste Management, Internet of Things (IoT), Gas Sensor Array, Decomposition Monitoring, BME688, MQ-04, Ultrasonic Sensor


Abstract: Cleanliness is not only the things that we see, it is also the things that we sense, breathe, and keep for the future. Rapid urbanization and increased waste production have resulted in bad odors that, besides causing health hazards, are also damaging the environment. Most of the currently available smart waste programs only keep track of how full the bins are and do not pay attention to the very important aspect of odor detection. Since an odor is the earliest indication of decomposition and a source of diseases, thus, its treatment is necessary. This is an AI-powered Smart Waste Management System that uses predictive analytics to keep off the waste from being smelly, which is the essence of the project. The system installs gas sensors, environmental sensors, and ultrasonic fill-level detection that are linked through ESP32 to a cloud platform for real-time monitoring. It is a machine learning model that anticipates the generation of odors due to the decomposition of the waste before the occurrence of the event, thus, making it possible to intervene on time and also to collect the waste in an optimized way. By integrating odor prediction with AI-based route optimization, the device becomes a means of improving hygiene, reducing human labor, and being a reliable partner for a sustainable Smart City future


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