Publication:
IGOE IoT framework for waste collection optimization

dc.contributor.authorLokuliyana, S
dc.contributor.authorJayakody, J. A. D. C. A.
dc.contributor.authorRupasinghe, L
dc.contributor.authorKandawala, S
dc.date.accessioned2022-03-18T07:50:04Z
dc.date.available2022-03-18T07:50:04Z
dc.date.issued2017-01-27
dc.description.abstractWaste management has become a major issue in all the part of the world and tends to grow day by day. Mismanagement in waste has become one of the key environmental and health issue. With the increase of population, especially in the urban areas waste collection, categorization, and disposal has become a major hazard for the government authorities. An IoT based waste collection framework is proposed to automate the solid waste identification, localization and collection process. The authors are involved in the identifying key impact factors in the waste collection process and provide systematic and automated solution to optimize the process to achieve higher efficiency. A layered architecture is introduced to handle the waste collection process and an optimization algorithm is derived for the existing business process based on the proposed evaluation criteria. The final outcome is a complete framework which compromises the Inputs, Outputs, Guide and Enables. The main objective is to implement an optimized automated waste collection system with the use of a vast sensor network capable of gathering waste data and by implementing an optimization algorithm in waste collection.en_US
dc.identifier.citationS. Lokuliyana, J. A. D. C. A. Jayakody, L. Rupasinghe and S. Kandawala, "IGOE IoT framework for waste collection optimization," 2017 6th National Conference on Technology and Management (NCTM), 2017, pp. 12-16, doi: 10.1109/NCTM.2017.7872820.en_US
dc.identifier.doi10.1109/NCTM.2017.7872820en_US
dc.identifier.isbn978-1-5090-4729-1
dc.identifier.urihttps://rda.sliit.lk/handle/123456789/1722
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartofseries2017 6th National Conference on Technology and Management (NCTM);Pages 12-16
dc.subjectIGOEen_US
dc.subjectIoT frameworken_US
dc.subjectwaste collectionen_US
dc.subjectoptimizationen_US
dc.titleIGOE IoT framework for waste collection optimizationen_US
dc.typeArticleen_US
dspace.entity.typePublication

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