Publication:
Computer-Vision Enabled Waste Management System for Green Environment

dc.contributor.authorHewagamage, P.
dc.contributor.authorMihiranga, A.
dc.contributor.authorPerera, D.
dc.contributor.authorFernando, R.
dc.contributor.authorThilakarathna, T.
dc.contributor.authorKasthurirathna, D.
dc.date.accessioned2022-02-07T08:38:56Z
dc.date.available2022-02-07T08:38:56Z
dc.date.issued2021-12-09
dc.description.abstractWaste management has become a critical requirement to maintain a green environment in Sri Lanka as well as other countries. Town councils have to regularly collect different types of wastes to clean cities/towns. Hence managing the waste of the cities is a challenging task. However, most of the urban councils currently use a manual approach to managing waste. However, it results in many difficulties for the people and cleaning staff who involve in the process by following strict guidelines. Issues due to waste contamination, no proper information management of waste collection, and no punctuality in removing waste from the garbage bins are some of the significant issues arising from the manual process. Due to the drawbacks of the manual approach, social issues, environmental issues, health issues can occur easily. This paper proposes a better solution to replace this manual system with an automated system to overcome these issues. Hence, the main objective of this research is to introduce an ICT-based innovative design that can be used to develop an effective waste management system in town councils. In the proposed model, we will introduce a Computer Vision-based smart waste bin system with real-time monitoring that incorporates various technologies such as computer vision, sensor-based IoT devices, and geographical information system (GIS) related technologies. Our proposed solution consists of a waste bin system, which is capable of automated waste segregation. Our design facilitates the admin users to expand the waste bin kit by adding more waste categories in a user-friendly manner, making our product adaptive in any environment. At the same time, waste bins can notify the real-time waste status. Our system generates the optimum collection routing path and displays it in a mobile app using those real-time status details. We also demonstrate a lowcost prototype.en_US
dc.description.sponsorshipCo-Sponsor:Institute of Electrical and Electronic Engineers (IEEE) Academic sponsor:SLIIT UNI Gold Sponsor :London Stock Exchange Group (LSEG)en_US
dc.identifier.doi10.1109/ICAC54203.2021.9671222en_US
dc.identifier.issn978-1-6654-0862-2/21
dc.identifier.urihttps://rda.sliit.lk/handle/123456789/988
dc.language.isoenen_US
dc.publisher2021 3rd International Conference on Advancements in Computing (ICAC), SLIITen_US
dc.subjectComputer Visionen_US
dc.subjectMachine learningen_US
dc.subjectConvolutional Neural Networksen_US
dc.subjectUnsupervised Clusteringen_US
dc.subjectInternet of Thingsen_US
dc.subjectCloud Computingen_US
dc.subjectGreen Environmenten_US
dc.titleComputer-Vision Enabled Waste Management System for Green Environmenten_US
dc.typeArticleen_US
dspace.entity.typePublication

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