AI-Driven Waste Monitoring and IoT-Based Collection System for Urban Sanitation Efficiency

Gokulan V; Sakthinarayanan S; Sarveshwar P; Kannan S; Indira S

doi:10.36948/ijfmr.2026.v08i02.68743

AI-Driven Waste Monitoring and IoT-Based Collection System for Urban Sanitation Efficiency

Author(s)	Gokulan V, Sakthinarayanan S, Sarveshwar P, Kannan S, Mrs Indira S
Country	India
Abstract	The fast growth of cities has created an increasing amount of waste, which has overwhelmed the collection systems that operate through fixed routes. The old-fashioned approaches produce inefficient business operations because they result in high fuel expenses[3] and full waste containers, and major harm to the environment. The paper presents an AI-based waste monitoring system which combines with IoT technology to solve these problems by providing smart monitoring and prediction capabilities. The system combines ESP32 microcontrollers with ultrasonic sensors to monitor bin levels continuously while machine learning models predict waste amounts, and the K-Nearest Neighbors (KNN) algorithm optimizes routes. Natural language processing (NLP) enables the chatbot to process citizen complaints. The system provides three main features, which include event-based resource distribution that modifies collection schedules for festivals and holidays, mobile-based photo submission for cleanliness reports, and real-time tracking of bin operations through interactive dashboards for municipal authorities. The expected pilot deployment validation through experiments showed multiple performance gains which included a 35% reduction in unnecessary collection trips, and a 28% decrease in fuel consumption, and waste prediction models reached 92% accuracy, and bin overflow events decreased by 84%. The scalable system contains four distinct layers which include an IoT hardware layer that collects sensor data, and a data processing layer which uses Flask backend and MongoDB storage, and a machine learning layer for prediction and optimization, and a user interface layer that provides responsive web and mobile applications to stakeholders. The solution offers real-time monitoring, and predictive maintenance, and optimized routing, and better citizen engagement. This creates a proper system for managing urban waste.
Keywords	Internet of Things, Artificial Intelligence, Machine Learning, Smart Waste Management, Route Optimization, Predictive Analytics, Natural Language Processing, Urban Sanitation.
Field	Computer > Data / Information
Published In	Volume 8, Issue 2, March-April 2026
Published On	2026-03-23
DOI	https://doi.org/10.36948/ijfmr.2026.v08i02.68743

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AI-Driven Waste Monitoring and IoT-Based Collection System for Urban Sanitation Efficiency

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