Smart Computing and Systems Engineering (SCSE)
Permanent URI for this communityhttp://repository.kln.ac.lk/handle/123456789/18936
Browse
2 results
Search Results
Item Utilizing mobile based technologies in monitoring solid waste in Sri Lanka: A case study(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Dasinaa, S.; Rajivkanth, S.An exponential increase in solid waste is a crucial concern for all citizens including policy makers. This issue has been building up over a period of time due to inadequate planning and implementation of measures to segregate, collect, tranbsport and dispose solid waste in the country. Despite many initiatives being taken to resolve the problems associated with the collection of waste, the issue of piled up garbage has been a common site. Though technology has advanced and unlike previously many people have access to it and use it, the use of such resources to solve daya to day problems of citizens is poor. Therefore, the current study was focused towards the technological approaches over the collection of solid waste that accumulates more in urban areas, especially in Sri Lanka. IoT, GPS, Geo-fencing and RFID is incorporated to design a model for the successful collection of solid waste on a timely efficient manner. It is expected that the solution will enable customers and policy makers the ability to address this important issue and ensure that the environment is kept clean. In addition, this model will function with minimum cost and will take only minimum to time for customers to use.Item Applicability of crowdsourcing for traffic-less travelling in Sri Lankan context(International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, 2018) Senanayake, J.M.D.; Wijayanayake, J.Traffic is one of the most significant problem in Sri Lanka. Valuable time can be saved if there is a proper way to predict the traffic and recommend the best route considering the time factor and the people’s satisfaction on various transportation methods. Therefore, in this research using crowdsourcing together with data mining techniques, data related to user mobility were collected and studied and based on the observations, an algorithm has been developed to overcome the problem. By using developed techniques, the best transportation method can be predicted. Therefore, people can choose what will be the best time slots & transportation methods when planning journeys. The algorithm correctly predict the best traffic-less traveling method for the studied area of each given day & the given time. Throughout this research it has been proven that to determine the best transportation method in Sri Lankan context, data mining concepts together with crowdsourcing can be applied. Based on a thorough analysis by extending the data set of the collection stage, it was shown that this research can be extended to predict the best transportation method with consideration of existing traffic in all the areas.