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The rampant and sudden outbreak of the SARS-CoV-2 coronavirus also called COVID-19 and its uncontrollable spread have led to a global crisis. COVID-19 is a highly contagious disease and the only way to fight with it is to follow social distancing and Non-Pharmaceutical Interventions (NPIs). Moreover, this virus is increasing exponentially day-by-day and a huge amount of data from this disease is also generated at the fast pace. So, there is a need to store, manage, and analyze this huge amount of data efficiently to get meaningful insights from it, which further helps medical professionals to tackle this global pandemic situation. Moreover, this data is to be passed through an open channel, i.e., the Internet, which opens the doors for the intruders to perform some malicious activities. Blockchain (BC) emerges as a technology that can manage the data in an efficient, transparent manner and also preserve the privacy of all the stakeholders. It can also aid in transaction authorization and verification in the supply chain or payments. Motivated by these facts, in this paper, we present a comprehensive review on the adoption of BC to tackle COVID-19 situations. We also present a case study on BC-based digital vaccine passports and analyzed its complexity. Finally, we analyzed the research challenges and future directions in this emerging area.

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The COVID-19 pandemic is rapidly spreading across the globe and infected millions of people that take hundreds of thousands of lives. Over the years, the role of Artificial intelligence (AI) has been on the rise as its algorithms are getting more and more accurate and it is thought that its role in strengthening the existing healthcare system will be the most profound. Moreover, the pandemic brought an opportunity to showcase AI and healthcare integration potentials as the current infrastructure worldwide is overwhelmed and crumbling. Due to AI's flexibility and adaptability, it can be used as a tool to tackle COVID-19. Motivated by these facts, in this paper, we surveyed how the AI techniques can handle the COVID-19 pandemic situation and present the merits and demerits of these techniques. This paper presents a comprehensive end-to-end review of all the AI-techniques that can be used to tackle all areas of the pandemic. Further, we systematically discuss the issues of the COVID-19, and based on the literature review, we suggest their potential countermeasures using AI techniques. In the end, we analyze various open research issues and challenges associated with integrating the AI techniques in the COVID-19.

This paper describes the design and development of a non-intrusive inertial speed sensor that can be reliably used to replace a conventional optical or hall effect-based speedometer on any kind of ground vehicle. The design allows for simple assembly-disassembly from tyre rims. The sensor design and data flow are explained. Algorithms and filters for pre-processing and processing the data are detailed. Comparison with a real optical encoder proves the accuracy of the proposed sensor. Finally, it is shown that factor graph-based localization is possible with the developed sensor.

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