Review Article |
Open Access
|
| Published Online: 30 December 2025
A Comprehensive Review of Smart and Sustainable Waste Management
Using Artificial Intelligence, Internet of Things, and Robotics
Sneha R. Shegar,* Umesh Dattatray Gosavi, Arpita Ramdas Lende and Trupti Vijay Walunj
Department of Computer Engineering, Samarth College of Engineering & Management, Pune, Maharashtra, 412410, India
*Email: snehashegar1@gmail.com (S. R. Shegar)
J. Collect. Sci. Sustain., 2025, 1(3), 25412 https://doi.org/10.64189/css.25412
Received: 17 November 2025; Revised: 29 December 2025; Accepted: 30 December 2025
Abstract
Urbanization and population growth have made waste management more challenging in urban areas such as parks, streets, and public transport. Traditional waste collection requires significant manual labor and is inefficient, expensive, and poses health hazards to sanitation workers. Recent advances in robots, Artificial Intelligence (AI), and the Internet of Things (IoT) have enabled autonomous and intelligent waste management systems that can detect, collect, and separate waste. This paper reviews intelligent robotic solutions for automated waste collection and separation. Key subsystems are discussed, including perception, navigation, manipulation, sorting, and IoT for waste management data generation. Sensor technologies such as ultrasonic, inductive, and moisture sensors, along with machine vision and deep learning algorithms for waste classification, are examined. Communication architectures using Global System for Mobile Communications (GSM), Global Positioning System (GPS), and mobile applications for real-time tracking and operation are also discussed. Existing automated systems are reviewed, and despite significant progress, long-term challenges remain related to energy efficiency, outdoor operation, and large-scale deployment. The review further identifies critical research gaps in system-level integration, autonomy, and scalability, and highlights future directions toward unified AI–IoT–robotic frameworks, energy-aware designs, and adaptive navigation strategies for sustainable and smart urban waste management.
Graphical Abstract
Novelty statement
This review consolidates robotics, AI, and IoT into a unified perspective for autonomous waste collection in urban environments.