Cyber-Physical Systems and Smart Cities in India: Opportunities, Issues, and Challenges

A large section of the population around the globe is migrating towards urban settlements. Nations are working toward smart city projects to provide a better wellbeing for the inhabitants. Cyber-physical systems are at the core of the smart city setups. They are used in almost every system component within a smart city ecosystem. This paper attempts to discuss the key components and issues involved in transforming conventional cities into smart cities with a special focus on cyber-physical systems in the Indian context. The paper primarily focuses on the infrastructural facilities and technical knowhow to smartly convert classical cities that were built haphazardly due to overpopulation and ill planning into smart cities. It further discusses cyber-physical systems as a core component of smart city setups, highlighting the related security issues. The opportunities for businesses, governments, inhabitants, and other stakeholders in a smart city ecosystem in the Indian context are also discussed. Finally, it highlights the issues and challenges concerning technical, financial, and other social and infrastructural bottlenecks in the way of realizing smart city concepts along with future research directions

T-CHAT educational framework for teaching cyber-physical system engineering

Cyber-physical systems (CPS) are increasingly used in manufacturing, transportation, health, and other industries. To develop these complex interdisciplinary systems, highly qualified CPS engineers are required who possess sound engineering knowledge and excellent transferable skills. Academic institutions offer a range of modules and curricula to teach CPS engineering. However, the literature reports a gap between expectations of industry and competencies of CPS graduates. To close this gap, this paper introduces and describes a holistic educational framework (T-CHAT) for teaching CPS engineering at the module level. To evaluate this framework, two use cases were analysed by conducting self-perception surveys and semi-structured interviews with students. Descriptive statistics and t-tests were calculated for the survey data. Interviews were coded and analysed using a General Inductive Approach. The analysis results were discussed by the comparison of the T-CHAT implementations in these two use cases