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Cost-Effective Autonomous Garbage Collecting Robot System using IoT and Sensor Fusion
Sengupta A, Varma V, Sai Kiran M, Johari A,
Published in Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
2019
Volume: 9
   
Issue: 1
Pages: 1 - 8
Abstract
Waste collection and management is a subject undergoing extensive study, and solutions are being proposed meticulously. Thanks to an exponential rise in population, there is an increased production of waste, and also a significant amount of litter consisting of plastic, paper, and other such products carelessly thrown about and scattered in public. Thus, the need for a more robust waste management strategy is essential. Presently, waste management techniques either lack efficiency, or incur high costs. Several Governmental as well as Non-Governmental Organizations have made efforts to clean public spaces. Collection of the unorganized and scattered garbage is the preliminary and most vital step of waste management, following proper segregation and disposal. This paper proposes, explains, and implements an original concept of making a modular, scalable and cost effective system for garbage collection. Making an efficient use of Internet of Things to maintain a constant connection between a central server and a network of garbage processing and collecting, independent, autonomous robots, we rely upon such a system to produce accurate results, as well as considerably reduce the cost, hence providing a feasible solution to minimize human effort and costs during waste collection. It provides a gateway towards implementing garbage collecting robots in smart cities. Rather than describing the design of a single robot, we propose an entire system of robots interconnected in a network, to optimize time, energy and overall speed. There is always a trade-off between accuracy, efficiency and cost of garbage collection, especially when robots get into the picture. Our purpose is to find the perfect balance between these factors.
About the journal
JournalInternational Journal of Innovative Technology and Exploring Engineering Regular Issue
PublisherBlue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
ISSN22783075
Open AccessNo