Issue |
E3S Web Conf.
Volume 501, 2024
International Conference on Computer Science Electronics and Information (ICCSEI 2023)
|
|
---|---|---|
Article Number | 01010 | |
Number of page(s) | 4 | |
Section | Applied Computer Science and Electronics for sustainability | |
DOI | https://doi.org/10.1051/e3sconf/202450101010 | |
Published online | 18 March 2024 |
Intelligent waste management using IoT, blockchain technology and data analytics
Doctor of Law (DSc), Professor, Head of the Department of Cyber Law, Tashkent State University of Law, Uzbekistan
* Corresponding author: said.gulyamov1976@gmail.com
Waste management is a growing challenge globally, with major impacts on social health, greenhouse gas emissions, and sustainable development. This paper provides an in-depth analysis on the potential of emerging technologies like the Internet of Things (IoT), blockchain platforms, big data analytics and artificial intelligence to enable more intelligent, sustainable waste management systems. A robust methodology of literature review, real-world case analysis, deduction and critical reasoning was utilized. The key findings are: (1) logistics optimization through machine learning driven dynamic routing and load optimization, reducing costs by 25-40%, (2) GHG emission reductions above 15% from optimized transportation, (3) 40%+ improvements in recycling rates and landfill diversion through waste stream automation and citizen engagement apps, and (4) over 50% reduction in waste contamination enabled by automated waste characterization using image recognition. However, barriers like infrastructure costs, lack of capabilities, and change management constrain adoption. Targeted pilots, open data sharing, and partnerships can drive implementation. Intelligent waste systems are critical for cities to cost-effectively tackle the growing waste challenge while meeting sustainability goals.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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