التفاصيل البيبلوغرافية
| العنوان: |
Utilising Machine Learning Techniques For Waste Management. |
| المؤلفون: |
Tripathy, Jyotsnarani, Das, Manmathnath, Ojha, Rajesh Kumar |
| المصدر: |
Srusti Management Review; Jul-Dec2023, Vol. 16 Issue 2, p148-155, 8p |
| مصطلحات موضوعية: |
WASTE management, MACHINE learning, WASTE paper, CONVOLUTIONAL neural networks, CITY dwellers |
| مستخلص: |
Waste management is one of the biggest challenges facing the world today. The amount of solid garbage created by the growing urban population makes it hard to manage with current technologies. Artificial intelligence methods are used in this paper to identify waste. When waste is found, the system uses the camera as the only data source to determine its location. With greater than 95% certainty, the suggested system can discern between assets and waste in real time.The paper concludes by describing a system that can inspect and gather waste much like a human would. Different programs have been launched by the current Indian government to improve cleanliness and hygienic conditions. Megacities in India, for example, Ahmedabad, Hyderabad, Bangalore, Chennai, Kolkata, Delhi and more noteworthy Mumbai have dynamic monetary development and high wastage per capita. Scratch issues and difficulties such as absence of gathering and isolation at source, shortage of land, dumping of e-Waste, and so on. By using physical labour, the current waste accumulation framework compiles a variety of waste in an unsorted manner. The separation of this waste is a very repetitious, time-consuming, and wasteful task that frequently threatens the safety of the professionals.n order for the junk transfer to be carried out efficiently and productively, a framework that automates the waste isolation process is therefore required. The proposed approach accurately categories the loss into degradable and non-degradable using machine learning techniques like CNN. [ABSTRACT FROM AUTHOR] |
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| قاعدة البيانات: |
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