Security issues and challenges in cloud of things-based applications for industrial automation.

Due to the COVID-19 outbreak, industries have gained a thrust on contactless processing for computing technologies and industrial automation. Cloud of Things (CoT) is one of the emerging computing technologies for such applications. CoT combines the most emerging cloud computing and the Internet of Things. The development in industrial automation made them highly interdependent because the cloud computing works like a backbone in IoT technology. This supports the data storage, analytics, processing, commercial application development, deployment, and security compliances. Now amalgamation of cloud technologies with IoT is making utilities more useful, smart, service-oriented, and secure application for sustainable development of industrial processes. As the pandemic has increased access to computing utilities remotely, cyber-attacks have been increased exponentially. This paper reviews the CoT's contribution to industrial automation and the various security features provided by different tools and applications used for the circular economy. The in-depth analysis of security threats, availability of different features corresponding the security issues in traditional and non-traditional CoT platforms used in industrial automation have been analysed. The security issues and challenges faced by IIoT and AIoT in industrial automation have also been addressed.

Cloud of Things in Crowd Engineering: A Tile-Map-Based Method for Intelligent Monitoring of Outdoor Crowd Density.

Managing citizen and community safety is one of the most essential services that future cities will require. Crowd analysis and monitoring are also a high priority in the current COVID-19 pandemic scenario, especially because large-scale gatherings can significantly increase the risk of infection transmission. However, crowd tracking presents several complex technical challenges, including accurate people counting and privacy preservation. In this study, using a tile-map-based method, a new intelligent method is proposed which is integrated with the cloud of things and data analytics to provide intelligent monitoring of outdoor crowd density. The proposed system can detect and intelligently analyze the pattern of crowd activity to implement contingency plans, reducing accidents, ensuring public safety, and establishing a smart city. The experimental results demonstrate the feasibility of the proposed model in detecting crowd density status in real-time. It can effectively assist with crowd management tasks such as monitoring, guiding, and managing crowds to ensure safety. In addition, the proposed algorithm provides acceptable performance.