Artificial Intelligence Retrofitting for Smart City Strategies in the Context of India's Growing Population

Introduction

With substantial developments in fields like the Internet of Things (IoT), automation, machine learning, robotics, and much other advanced analytics deployed for various purposes, the artificial intelligence (AI) explosion significantly impacts practically every part of our lives. It has transformed traditional systems into cognitive computing by merging information and communication technologies (Chawla et al., 2022). AI applications are increasingly being applied in a broad spectrum of industries contributing to advancements in instant information delivery, decision-making, research extension, and reliable data repositories (Shivaprakash et al., 2022). Over the past century, the global population has drastically expanded, and urbanization increased to 57% worldwide in 2022. Reportedly, India is the second largest metropolis after China, with extreme urbanization covering about 35% of the population, growing by 2.1% annually. By 2030, it is anticipated to rise to 40% and create 75% GDP of India through cities (Statista, 2023). Cities have transformed over the past few decades. They have become the driving force of social, environmental, and economic advancement through comprehensive and integrated strategy and the source of citizens' hope and opportunity (Mitra & Mehta, 2011). Many policymakers, professionals, and academicians believe that advanced urban innovations will usher in human evolution due to the current technological revolution (Tomitsch & Haeusler, 2015). Some of the wealthy countries have already surpassed this urbanization rate. For instance, over 80% of people in the UK live in metropolitan regions (Cowley et al., 2018). It needs the involvement of many organizations, incorporating sustainable growth, ICT infrastructure support, green economy, and multi-stakeholder alliances on diverse scales to successfully convert an urban area into a smart city (Kaluarachchi, 2022).

The inception of “smart cities” has gained popularity due to the constantly changing situation surrounding the administration and management of emerging technological powers as it is being challenged to reinvent itself and try out new perspectives concerning innovation and how it might be utilized to serve the general welfare since both technologies and societies change drastically (Angelidou, 2016). Developing “smart cities” involves initiatives and programs that encourage urban innovation and the thorough integration of ICT. The smart city concept incorporates basic infrastructure, ICT innovations, socialization, intellectual capital, and cultural connections to establish an eco-friendly environment. The “Smart Cities Mission” was enacted in 2015 by the Indian government to promote economic progression and raise living standards in 100 chosen cities. The “Ministry of Housing and Urban Affairs”, responsible for the accountability of the “Smart Cities Mission”, has received 61,905 crores from the national government. The program deliberately sought to initiate this by empowering the community’s development and incorporating technology to offer innovative measures for residents (Praharaj et al., 2018).

Many nations, including Japan, the European Union, the United States, and others, have realized that a smart city project successfully solves the approaching difficulties because it encompasses human ecology (Harnal et al., 2022). This transformation is observed through the report of Philips lighting and SmartCitiesWorld, where the Barcelona government retained 378 crores by integrating IoT services and technologies into its smart city projects and achieved 324.64 crores through smart auto parking. According to the Smart City Index 2021, 118 cities listed worldwide adopt smart city strategies. In the drive towards pervasive computing, Singapore is viewed as a trendsetter. With the aid of sensing devices, robots, and other cyber-physical technologies, emerging IoT solutions are applied to create smart cities for resource management, environmental monitoring, smart logistics operations, and smart farming. The resultant output is utilized to create approaches for smart cities by transferring all the statistical data to the server for interpretation (Wang et al., 2021).