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      Design, implementation, and evaluation of an Internet of Things (IoT) network system for restaurant food waste management.

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          Abstract

          Catering companies around the world generate tremendous amounts of waste; those in China are no exception. The paper discusses the design, implementation, and evaluation of a sensor-based Internet of Things (IoT) network technology for improving the management of restaurant food waste (RFW) in the city of Suzhou, China. This IoT-based system encompasses the generation, collection, transportation and final disposal of RFW. The Suzhou case study comprised four steps: (1) examination of the required functionality of an IoT-enabled system in the specific context of Suzhou; (2) configuration of the system architecture, both software and hardware components, according to the identified functionality; (3) installation of the components of the IoT system at the facilities of the stakeholders across the RFW generation-collection-transportation-disposal value chain; and (4) evaluation of the performance of the entire system, based on data from three years of operation. The results show that the system had a strong impact. Positive results include: (1) better management of RFW generation, as evidenced by a 20.5% increase in RFW collected via official channels and a 207% increase in the number of RFW generators under official contract; (2) better law enforcement in response to RFW malpractice, enabled by the monitoring capabilities of the IoT system; and (3) an overall reduction in illicit RFW activities and better process optimization across the RFW value chain. Negative results include: (1) Radio-frequency identification (RFID) tags need to be renewed often due to the frequent handling of waste bins, thus increasing operating costs; (2) dynamic/automatic weight sensors had a higher degree of error than the more time-consuming static/manual weighing method; and (3) there were disagreements between the city's government agencies about how to interpret data from the IoT system, which led to some inefficiencies in management. In sum, the Suzhou IoT system enabled data-driven management of RFW and had a net positive impact for the stakeholders involved.

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          Author and article information

          Journal
          Waste Manag
          Waste management (New York, N.Y.)
          Elsevier BV
          1879-2456
          0956-053X
          Mar 2018
          : 73
          Affiliations
          [1 ] State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; Key Laboratory for Solid Waste Management and Environment Safety (Tsinghua University), Ministry of Education of China, Tsinghua University, Beijing 100084, China. Electronic address: wenzg@tsinghua.edu.cn.
          [2 ] State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China; Key Laboratory for Solid Waste Management and Environment Safety (Tsinghua University), Ministry of Education of China, Tsinghua University, Beijing 100084, China.
          [3 ] Department of Civil and Environmental Engineering, Imperial College London, London SW7 2BU, UK.
          [4 ] School of Humanities and Economic Management, China University of Geosciences, Beijing 100083, China.
          Article
          S0956-053X(17)30937-6
          10.1016/j.wasman.2017.11.054
          29242117
          cbc065bc-f15c-4319-83d2-059666e1ea4f
          History

          Internet of Things,Sensors,Restaurant food waste,RFID
          Internet of Things, Sensors, Restaurant food waste, RFID

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