The ever-increasing demand for reduced latency, security, and mobility support requires data to be generated at the nearest source, that is, the retail store. This streamlining needs faster connectivity, better edge computing infrastructure, a secure environment and well-designed architecture. Edge computing has emerged as the solution to every issue occurring due to the Internet of Everything (IoE). The enormous data transmission and a large number of interconnected devices generate major challenges in the implementation. Implementation of edge computing at the point of data generation, such as brick-and-mortar stores, warehouses, and IoT devices, physical stores are leveraging the advantages of broadening the life expectancy of the store and competing with online stores on equal footing. This paper explores various opportunities and challenges of integrating edge computing to achieve optimized operational efficiency, enhance customer experience, and minimize data handling costs. The standards for illuminating the major objectives of the paper are to list factors to improve customer experience by implementing various edge computing and AI solutions in a retail store environment. The major conclusions drawn from the implementation of edge computing in retail stores for personalization and customization, data security, reduced latency, cost reduction, and sustainability inferences can be found. The authors found that with the fourth-generation to fifth-generation technological enhancements in the retail industry, edge computing has significantly improved inventory management by efficient space management based on the demand–supply requirements. This has led to reduced costs and improved service levels. Human resource requirements for skill enhancement and training also play a crucial part. Edge computing implementations will have a direct connection with SDGs. SDG-9 of Industry, Innovation, and Infrastructure will be addressed by optimizing the supply chain and reducing energy consumption. SDG-13, being the most crucial one to adhere to, will have a positive impact on all fronts of energy consumption, waste reduction and improved efficiency. The list of opportunities and challenges explored here is not exhaustive, and further research can throw light on many such kinds.

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Edge Computing for Smart Retail: Enhancing Customer Experience, Efficiency, and Sustainability

  • Shweta Vyas,
  • Yamini Ghanghorkar,
  • Chanakya Kumar,
  • Indrajit Ghosal

摘要

The ever-increasing demand for reduced latency, security, and mobility support requires data to be generated at the nearest source, that is, the retail store. This streamlining needs faster connectivity, better edge computing infrastructure, a secure environment and well-designed architecture. Edge computing has emerged as the solution to every issue occurring due to the Internet of Everything (IoE). The enormous data transmission and a large number of interconnected devices generate major challenges in the implementation. Implementation of edge computing at the point of data generation, such as brick-and-mortar stores, warehouses, and IoT devices, physical stores are leveraging the advantages of broadening the life expectancy of the store and competing with online stores on equal footing. This paper explores various opportunities and challenges of integrating edge computing to achieve optimized operational efficiency, enhance customer experience, and minimize data handling costs. The standards for illuminating the major objectives of the paper are to list factors to improve customer experience by implementing various edge computing and AI solutions in a retail store environment. The major conclusions drawn from the implementation of edge computing in retail stores for personalization and customization, data security, reduced latency, cost reduction, and sustainability inferences can be found. The authors found that with the fourth-generation to fifth-generation technological enhancements in the retail industry, edge computing has significantly improved inventory management by efficient space management based on the demand–supply requirements. This has led to reduced costs and improved service levels. Human resource requirements for skill enhancement and training also play a crucial part. Edge computing implementations will have a direct connection with SDGs. SDG-9 of Industry, Innovation, and Infrastructure will be addressed by optimizing the supply chain and reducing energy consumption. SDG-13, being the most crucial one to adhere to, will have a positive impact on all fronts of energy consumption, waste reduction and improved efficiency. The list of opportunities and challenges explored here is not exhaustive, and further research can throw light on many such kinds.