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One of the simple, yet significantly complete definitions of smart cities is the one given by Eduadro Paes (2013), which goes like this: “Smart Cities are those who manage their resources efficiently. Traffic, public services, and disaster response should be operated intelligently to minimize costs, reduce carbon emissions and increase performance.”
The last decade has seen many technologies, meant for smart cities (2022). In the past two decades, smart city solutions have emerged, enabled by technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), Deep Learning, and Cloud Computing. They offer vast potential to address infrastructural, societal, and pandemic challenges. With smart technologies, communities can improve energy distribution, streamline trash collection, decrease traffic congestion, improve air quality, and more with help from smart, connected sensing systems (Tay & Mourad, 2020; Thoumi & Haraty, 2022).
The Cities represent a composite structure of social and economic entities and the center of data, employment and trade, and significant foundations of authority. In 2030, India expects 40% of the entire population to house in cities, and thus will subsidize above 70% of the nation’s GDP. Therefore, cities require the necessary equipment for social and physical infrastructure to deliver quality life and economic prospects to the urban population reasonably and sustainably (Arasteh, 2016).
In today’s scenario, Cities are turning into money-spinners of data by producing huge quantities through video cameras, traffic control systems, sensors, vehicles, smart meters, mobile phones, and IoT devices. Moreover, the historic data is already gathered in manual form or in automated forms for enabling supervised learning. The developing technologies, such as Artificial Intelligence (AI), Machine learning (ML), and Deep learning (DL), can reform the challenges related to the exponential data growth due to smart cities. AI and ML devise the potential to turn vast data into a meaningful form and practice the learned intelligence for improving the performance, and optimization of the operational resources and their cost factors, enabling proactive citizen arrangement, consequently creating cities liveable and efficient. With the capability to connect with older data handling systems, AI has the power to produce much-desired insights for the functioning of smart cities (Peñalvo et al., 2022; Samir et al., 2019; Taleb & Abbas, 2022). Therefore, with the help of resources urbanized by Smart Cities Operation and the composite changing aspects of the urban environment, smart cities stand to assistance by AI Implementation. AI has several applications, from sustaining an improved atmosphere to improving transport for the public along with management of all the safety parameters. Nowadays, even the Government is enthusiastically assisting the deployment of AI-driven services to produce smarter cities. Some of the applications where AI is already used are highlighted below: