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INTERNATIONAL JOURNAL OF CREATIVE RESEARCH THOUGHTS - IJCRT (IJCRT.ORG)
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ISSN Approved Journal No: 2320-2882 | Impact factor: 7.97 | ESTD Year: 2013
Call For Paper - Volume 12 | Issue 7 | Month- July 2024
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Published Paper Details:
Paper Title
An Examination of Machine Learning Approaches for Enhancing Efficiency in Smart Waste Management Systems
Authors
Shubham Kumar, Bidhan Kumar Singh, Aniket Kumar, Aman Kumar, Swati Gupta
Keywords
Smart Waste Management, Intelligent Waste Management, IoT, Smart Bin
Abstract
Unused disposal is a hard work for Economically developing countries alike. Biggest problem is that the public garbage cans often overflow well before they are due to be emptied again. This results in elevated levels of smokes, beetles, and houseflies produced by waste management which can cause some serious health disease. A comprehensive analysis is conducted in the latest research, focusing on the integration of machine learning techniques in enhancing smart waste management practices. With this technology, the system may optimize waste disposal by selecting the most efficient route using machine learning. ML-IoT-based design includes equipment that measures weight of rubbish adjusted to network environment as well as containing information about waste management Comparing these studies should give readers a complete understanding of the smart waste management domain
IJCRT's Publication Details
Unique Identification Number - IJCRT24A5043
Paper ID - 261535
Page Number(s) - j398-j408
Pubished in - Volume 12 | Issue 5 | May 2024
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Shubham Kumar, Bidhan Kumar Singh, Aniket Kumar, Aman Kumar, Swati Gupta, "An Examination of Machine Learning Approaches for Enhancing Efficiency in Smart Waste Management Systems", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 5, pp.j398-j408, May 2024, Available at :http://www.ijcrt.org/papers/IJCRT24A5043.pdf
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Volume 12 | Issue 7
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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