J.J. Bandal
Anuradha Raut
Satvika Konde
Swati Dalvi
Pankaj Bhandare
Shrutika Baikar
- Student Department of Mechanical Engineering, Symbiosis Skills & Professional University Pimpri-Chinchwad Maharashtra India
- Professor Department of Mechanical Engineering, Symbiosis Skills & Professional University Pimpri-Chinchwad Maharashtra India
- student Department of Mechanical Engineering, Symbiosis Skills & Professional University Pimpri-Chinchwad Maharashtra India
- Student Department of Mechanical Engineering, Symbiosis Skills & Professional University Pimpri-Chinchwad Maharashtra India
- Student Department of Mechanical Engineering, Symbiosis Skills & Professional University Pimpri-Chinchwad Maharashtra India
- Student Department of Mechanical Engineering, Symbiosis Skills & Professional University Pimpri-Chinchwad Maharashtra India
Abstract
The increasing waste generation rate necessitates effective waste management, as unmanaged waste poses significant harm to humans and the environment, causing climate changes and hindering national financial development. An automated waste segregation system is crucial to avoid these issues and reduce recycling complexity. Waste cannot be fully appreciated in terms of its significance and financial value until it is separated. A suggested smart waste sorting system uses image processing-based software along with hardware. The system aims to efficiently sort waste, making it easier for groups to segregate them on a large scale. The hardware includes a Raspberry PI, sensors. The ultimate goal is automatic segregation of waste. The implementation of an automated waste segregation system is a crucial measure in mitigating the increasing rates of trash generation that present significant hazards to the environment and human health. Unmanaged trash not only impedes the advancement of the national economy but also adds to climate change. Effective waste segregation is the new paradigm that is required in light of waste management’s importance and cost consequences.
Keywords: Sensors, Raspberry PI, Waste, Human Health, Automated
[This article belongs to International Journal of Environmental Noise and Pollution Control(ijenpc)]
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References
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| Volume | 02 |
| Issue | 01 |
| Received | May 20, 2024 |
| Accepted | June 20, 2024 |
| Published | July 15, 2024 |