Integration of IoT based routing process for food supply chain management in sustainable smart cities. (January 2022)

• Record Type: Journal Article
• Authors: Nagarajan, Senthil Murugan; Deverajan, Ganesh Gopal; Chatterjee, Puspita; Alnumay, Waleed; Muthukumaran, V.
• Is Part Of: Sustainable cities and society. Volume 76(2022)
• Publication Date: 2022-01
• Subjects: Internet of Things (IoT) -- Food supply chain -- Ant Colony Route Optimization -- Cloud computation -- Sustainable cities; Sustainable urban development -- Periodicals; Sustainable buildings -- Periodicals; Urban ecology (Sociology) -- Periodicals; 307.76
• DOI: 10.1016/j.scs.2021.103448
• Languages: English
• ISSNs: 2210-6707

Abstract

Highlights: Proposed IoT based Dynamic Food Supply Chain Network for Smart Cities. Proposed IoT based Food Supply with Dynamic Vehicle Routing (IFSCDVR) using Bee Colony algorithm. Proposed DPSTT for efficient tracing and tracking of food product. Real-time analysis of food supply chain management in smart cities. Abstract: The rapid growth of population in metropolitan areas has put incremental pressure on urban cities. The centric strategy towards smart cities are expected to cover solution for metropolitan life and ecological environment. One of the significant application areas of IoT in smart cities is the food industry. IoT systems help to monitor, analyze, and manage the real-time food industry in smart cities. In this research, we proposed an IoT based Dynamic Food Supply Chain for Smart Cities which not only ensures the food quality but also provides intelligent vehicle routing as well as tracing sources of contamination in FCM. Furthermore, a smart sensor data collection strategy based on IoT is utilized which would improve the efficiency and accuracy of the supply chain network with the minimized size of dataset and vehicle routing algorithm is introduced and tracing the contamination sources of infected food in the markets. Our proposed model is evaluated with the comprehensive evaluation and used various performance metrics such as tracing accuracy, delay, execution time, and traveling time. The results show that the proposed system outperforms when compared with existing approach.