Paper Title :Internet of Things based Waste Management System

Author : Ntshuxeko Makondo,Topside E. Mathonsi, Tshimangadzo M. Tshilongamulenzhe

Article Citation : Ntshuxeko Makondo ,Topside E. Mathonsi ,Tshimangadzo M. Tshilongamulenzhe , (2020 ) " Internet of Things based Waste Management System " , International Journal of Soft Computing And Artificial Intelligence (IJSCAI) , pp. 26-29, Volume-8,Issue-1

Abstract : Solid waste disposal is currently a major concern in the emerging and developed metropolitan cities. Given the growing population, garbage is also that. The vast unmanaged garbage collection pollutes the atmosphere, spoils the area's beauty and contributes to a health hazard. The method of gathering municipal waste is very complex and needs a large amount of money annually to collect and manage waste. Many high-income towns cover a portion of this burden by charging the residents fees. The remainder is covered by the tax revenue, which creates a financial strain on local governments. Waste management companies and municipalities have rarely used technological advances to boost productivity in operations. What they have done so far is enhancing the efficiencies of the roads, the excellent route optimization, and every dumpster's trash level must be physically tested by waste collection trucks. The manual method results in time and money wasted as trucks frequently hit dumpsters that do not need emptying. In this Internet era, the rising usage of the Internet of Things (IoT), smart devices and sensors and machine-to-machine (M2M) connectivity have the potential to reduce needless expenses caused by inefficiencies in the operation of waste collection processes. As a result, this paper proposes the use of IoT and smart sensors, for waste management in order to ensure that waste management companies improve operational performance, reduce costs and increase customer satisfaction. Keywords - Internet of Things (IoT), Network Management, Planning Tasks, Efficient Channel Assignment, Resource Management, LRANN algorithm

Type : Research paper

Published : Volume-8,Issue-1

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