Making assembly line in supply chain robust and secure using UHF RFID

This paper presents a block-chain enabled inkjet-printed ultrahigh frequency radiofrequency identification (UHF RFID) system for the supply chain management, traceability and authentication of hard to tag bottled consumer products containing fluids such as water, oil, juice, and wine. In this context, we propose a novel low-cost, compact inkjet-printed UHF RFID tag antenna design for liquid bottles, with 2.5 m read range improvement over existing designs along with robust performance on different liquid bottle products. The tag antenna is based on a nested slot-based configuration that achieves good impedance matching around high permittivity surfaces. The tag was designed and optimized using the characteristic mode analysis. Moreover, the proposed RFID tag was commercially tested for tagging and billing of liquid bottle products in a conveyer belt and smart refrigerator for automatic billing applications. With the help of block-chain based product tracking and a mobile application, we demonstrate a real-time, secure and smart supply chain process in which items can be monitored using the proposed RFID technology. We believe the standalone system presented in this paper can be deployed to create smart contracts that benefit both the suppliers and consumers through the development of trust. Furthermore, the proposed system will paves the way towards authentic and contact-less delivery of food, drinks and medicine in recent Corona virus pandemic

Big data analytics for 5G networks: utilities, frameworks, challenges and opportunities

In order to meet the challenges of ambitious capacity, user experience, and resource efficiency gains, the next‐generation cellular networks need to leverage end‐to‐end user and network behavior intelligence. This intelligence can be gathered from the mobile network big data which includes the massive telemetric data about network health and status as well as data about user whereabouts, preferences, context, and mobility patterns. As a result, exploitation of big data on wireless cellular network is emerging as an indispensable approach for harnessing intelligence in future wireless communication networks. In this article, we first identify and classify the big data that can be gathered from different layers and ends of a wireless cellular network. We then discuss several new utilities of the big data that can bridge the existing gaps to meet 5G requirements. After that we summarize the existing literature on data analytics for cellular network performance. We present different platforms and two different frameworks to implement big data analytic‐based solutions in 5G and beyond and compare their pros and cons. We then discuss how key performance indicators (KPIs)‐based data collection may not suffice in 5G. Through an exemplary study, we show how to unleash the full potential hidden within the big data, granularity of low‐level performance indicators, and how context is essential. Finally, we highlight the opportunities that can be availed from big data in cellular network and the challenges therein