Research Publications Authored by SLIIT Staff
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This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.
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Publication Embargo IGOE IoT framework for waste collection optimization(IEEE, 2017-01-27) Lokuliyana, S; Jayakody, A; Rupasinghe, L; Kandawala, SWaste 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.Publication Embargo IGOE IoT framework for waste collection optimization(IEEE, 2017-01-27) Lokuliyana, S; Jayakody, J. A. D. C. A.; Rupasinghe, L; Kandawala, SWaste 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.