Title: Smart-bin: an innovative approach to waste management in smart cities

Authors: Chandani Sharma; Shweta Goyal; Anzar Ahmed

Addresses: CSE Department, MMICTBM (MCA), Maharishi Markandeshwar (Deemed to be University), Mullana-Ambala, Haryana, India ' EEE Department, GEU, Dehradun, Uttrakhand, India ' ECE Department, GEU, Dehradun, Uttrakhand, India

Abstract: Waste management is an escalating challenge in urban areas due to the rising volume of waste generated daily. Effective segregation of waste into dry and wet components is essential for proper disposal and recycling. This paper presents the design and development of a smart dustbin that automates waste segregation using Arduino Uno, support vector machine (SVM), TensorFlow, and advanced sensor technology. The system employs automated sensing, classification techniques, and machine learning models to accurately distinguish between dry and wet waste, enhancing the waste management process. By integrating SVM and TensorFlow for improved classification accuracy, the system optimises waste collection and promotes sustainable disposal practices. The findings demonstrate how this smart dustbin, with its intelligent automation and machine learning capabilities, can significantly improve waste management efficiency, reduce manual effort, and contribute to the development of cleaner, more sustainable urban environments in the context of smart city initiatives.

Keywords: waste management; smart dustbin; Arduino Uno; support vector machine; SVM; TensorFlow; advanced sensor technology.

DOI: 10.1504/IJTTC.2025.149732

International Journal of Technology Transfer and Commercialisation, 2025 Vol.21 No.4, pp.293 - 305

Received: 31 Aug 2024
Accepted: 14 Feb 2025
Published online: 11 Nov 2025 *

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