2018 IEEE 8th Annual Computing and Communication Workshop and Conference (CCWC) 2018
DOI: 10.1109/ccwc.2018.8301629
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Optimizing routine collection efficiency in IoT based garbage collection monitoring systems

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Cited by 14 publications
(2 citation statements)
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“…Activities in solid waste management performance for the collection of routs in MSW such as k-means clusters (Ray et al, 2018) and decision tree (Bakhshi & Ahmed, 2018). Finally, applying the ML approach will improve waste classification effectiveness and precision, reduce energy and recycling costs, and maximize waste management activities, both in economic and environmental terms.…”
Section: Swmmentioning
confidence: 99%
See 1 more Smart Citation
“…Activities in solid waste management performance for the collection of routs in MSW such as k-means clusters (Ray et al, 2018) and decision tree (Bakhshi & Ahmed, 2018). Finally, applying the ML approach will improve waste classification effectiveness and precision, reduce energy and recycling costs, and maximize waste management activities, both in economic and environmental terms.…”
Section: Swmmentioning
confidence: 99%
“…These suggested approaches have shown excellent results during real‐life testing and accomplished the objectives of identifying collection areas correctly, shortening the collection distance and reducing transport times and consumption of oil. Few other methods are also implemented to achieve the utmost performance for the collection of routs in MSW such as k‐means clusters (Ray et al, 2018) and decision tree (Bakhshi & Ahmed, 2018). Finally, applying the ML approach will improve waste classification effectiveness and precision, reduce energy and recycling costs, and maximize waste management activities, both in economic and environmental terms.…”
Section: Prediction Areas In Swmmentioning
confidence: 99%