Facilitating Contactless and Automated Retail Services via Edge Technologies

The retail industry is characterized by its dynamic nature and emphasis on customer satisfaction, constantly seeking to enhance the shopping journey. In an effort to balance operational efficiency and profit margins, retailers are adopting innovative and advanced technologies like edge computing. This is key in transforming retail to support real-time contactless and automated services. 


Smart kiosks, cameras, point-of-sale systems, and sensors provide significant performance benefits and minimize latency, essential for automated retail services. These technologies allow retailers to generate reports and alerts, optimizing predictive models and analytics throughout the enterprise. However, deploying these devices introduces challenges in management post-deployment, particularly about connectivity and security concerns.

The effectiveness of edge computing depends on the implementation of automation tools, such as the NearbyOne. 

How do retailers use edge technologies?


Contactless Checkout: Retailers implement edge technologies to offer a cashier-less checkout experience. This system uses computer vision, artificial intelligence, and machine learning to track items as customers select them, enabling automatic billing through mobile applications for a fast and touchless purchasing process.

Inventory Management: Edge devices capture sensor data, providing retailers with a comprehensive view of their inventory. This real-time insight helps minimize stock shortages and optimize decision-making. Additionally, it enables the delivery of personalized offers and discounts based on inventory levels, to further improve the in-store experience.

Smart Vending Machines: Retailers are adopting smart vending machines and self-service kiosks that use IoT and edge computing to operate autonomously. These devices enhance the shopping experience by offering interactive and AI-driven purchasing options, contributing significantly to retailers’ strategies for customer satisfaction.

Fraud Detection: Fraud prevention uses predictive analytics to identify patterns indicative of fraudulent activities, such as shoplifting and internal theft. Smart cameras with edge computing capabilities proactively monitor suspicious behavior, improving loss prevention efforts.

    Challenges in adopting edge technologies for retail stores




    The widespread deployment of edge devices, especially in areas with limited connectivity, introduces significant security risks. These devices handle sensitive biometric and customer data, making them targets for security breaches. The lack of comprehensive monitoring for large-scale deployments can weaken network security.



    Automated retail solutions are subject to dynamic demands, necessitating a flexible system architecture. Without constant monitoring, it becomes difficult for retailers to adjust resource allocation effectively and respond to changes and activities throughout the business.



    Post-deployment, the edge infrastructure, network, and applications require careful orchestration to achieve optimal performance and efficiency. Some of the operational issues include challenges in data synchronization and network connectivity optimization.

    VALUE-ADDED solution

    Revolutionize edge retail solutions with NearbyOne

    Stakeholders responsible for retail solutions using edge technologies must consider orchestration tools to streamline the management of edge devices for advanced security. NearbyOne offers a single pane of glass feature for customers to provision and allocate resources and also fully manage the lifecycle of their edge nodes as a service.

    Through collaboration with Nearby Computing, you can unlock the full potential of your digital transformation. With the help of NearbyOne, we offer organizations the ability to leverage cross-domain orchestration designed for speed, performance, and availability, catering to the demands of latency-sensitive, data-intensive, and mission-critical applications.

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