| Title |
Smart waste management paradigm in perspective of IoT and forecasting models |
| ID_Doc |
44691 |
| Authors |
Anjum, M; Shahab, S; Umar, MS |
| Title |
Smart waste management paradigm in perspective of IoT and forecasting models |
| Year |
2022 |
| Published |
International Journal Of Environment And Waste Management, 29, 1 |
| DOI |
10.1504/IJEWM.2022.120621 |
| Abstract |
Municipal solid waste management has evolved as a major component of smart city services that encompasses a variety of tasks from household collection to final disposal/recycling. This paper critically discusses, firstly, mathematical and statistical aspect of solid waste management services in the direction of smart city development. Secondly, it proposes novel and intelligent waste management architecture through adoption of state-of-art internet of things (IoT) technologies. Mathematical and statistical aspect covers the comprehensive information of forecasting models. This paper classifies the models on the basis of influencing factors (socio-economic and demographic), planning period (short, medium and long) and ranking methods in order to foresee the amount of waste generated. Paper also emphasises on adoption of IoT technologies in proposed waste management architecture and a comprehensive and thorough survey of IoT technologies is also presented to explore their characteristics and applications in waste management system. Further, an intelligent waste management architecture is proposed for real-time monitoring of smart bin, collecting vehicle, dynamic scheduling, and route optimisation. |
| Author Keywords |
municipal solid waste; MSW; smart bin; smart vehicle; work server; spatial technology; internet of things technologies; dynamic scheduling and routing |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Emerging Sources Citation Index (ESCI) |
| EID |
WOS:000889120900003 |
| WoS Category |
Engineering, Environmental; Environmental Sciences |
| Research Area |
Engineering; Environmental Sciences & Ecology |
| PDF |
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