IoT-Based Automated Dust Bins and Improved Waste Optimization Techniques for Smart City

Author:

Singh Khushwant1,Yadav Mohit2ORCID,Yadav Ramesh Kumar3ORCID

Affiliation:

1. University Institute of Engineering and Technology, Maharshi Dayanand University, India

2. University Institute of Sciences, Chandigarh University, India

3. Christ University, India

Abstract

Effective waste management systems are essential for maintaining sustainability, environmental health, and cleanliness in the age of smart cities. This chapter provides a thorough analysis of the combination of cutting-edge waste minimization techniques with the deployment of an internet of things-based automatic dust bin. The suggested system optimizes garbage collection, lowers operating costs, and has a less environmental effect by combining the creative use of proximity sensors, real-time data analytics, and smart bin technologies. Remote monitoring and administration are made possible by the linked ecosystem that is created by the integration with the internet of things (IoT). In order to further promote environmentally friendly urban life, the study also examines waste-to-energy technology, circular economy ideas, and sustainable waste management techniques. The results provide insightful information for scholars, decision-makers, and urban planners looking for ground-breaking waste management solutions for today's cities.

Publisher

IGI Global

Reference72 articles.

1. IoT-Based Framework For Smart Waste Monitoring And Control System, A Case Study of Smart Cities.

2. Fabrication and analysis of ABS-HDPE-PC composite polymer filament used for FDM printing using hybrid algorithm

3. Artificial Intelligence and Machine Learning in Waste Management and Recycling

4. Role of Wireless Aided Technologies in the Solid Waste Management: A Comprehensive Review

5. AnomanyoE. D. (2004). Integration of municipal solid waste management in Accra (Ghana): Bioreactor treatment technology as an integral part of the management process. Lund University. https://lumes.lu.se/sites/lumes.lu.se/files/anomanyo_edward.pdf

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