1.2.1 Bhubaneswar City

In India, Bhubaneswar has the best infrastructural setup of smart city project. It is the city where center of economic and having more religious importance in Eastern part of India. Consistently, this city has proved its efficiency in assessment among top smart city around the globe. It plays vital role in digital communication with advanced technologies. Figure 1.1 shows the Bhubaneswar smart city structure. This project included with construction engineering and green and park areas with road and development accessibility and slum accommodation.

1.2.2 Smart City in Pune

Vision of smart city in Pune is to redesign its streets and roads and its equal for all people. Pune Smart City overview is shown in Figure 1.2. Design of the city is based upon the universal accessibility for the elderly and physically challenged and increased focus on the pedestrians, modern world infrastructure through the creation of appropriate arrangements for underground utilities [3]. Allocation is mainly to motorized traffic, continuous excavation of roads, and weak pedestrian crossing for layout facilities.

1.3.1 Funding Process by Government

Over 5 years, the central government has allocated Rs 48,000 crore to the mission. That amounts to an average of Rs 96 crore per city per year, maybe enough in many cities to create a sewage drain. An equivalent amount would have to be contributed by the states and urban local bodies of amount 96 crore. The city administration had to raise the remainder of the necessary financing through a host of sources-public-private partnerships, grants, resource monetization, and the likes. While renowned planners have created the smart city ideas, with the financial arrangements planned out in advance, most urban local authorities are struggling to raise the funds needed. While several bodies have raised concerns that the financing of the central government is insufficient, the government itself is not sympathetic [5, 6] and funds raised by government of India as shown in Figure 1.3. That any of the 30 cities will have no trouble collecting funds because they have A++ credit scores.

Pune is an smart example that has successfully launched a municipal bond, documenting its own process and replicating the success of the other cities.

The source of funds may vary in different countries; the sources of the smart city projects are provided by government and the private organizations; they are state government and the urban local bodies and central government. Public-private partnership organizations, convergence with the other government mission resources, and also load providers are all contributing in this mission progress. Analysts think that national transformative projects such as the Smart Cities Mission will take time to implement in a vast country like India. The mission is also suffering from the lack of urban planners.

1.4.1 Physical Infrastructure-Based

Digital innovations, in terms of physical technology, a smart city, transform into improved public facilities for people and better resource use while reducing environmental impacts. A city that integrates physical infrastructure, IT infrastructure, social infrastructure, and business infrastructure with a view to exploiting the city’s collective intellect. Technologies for embedded sensing allow data collection and analysis in real time [7]. This data is then presented to infrastructure companies as meaningful and accurate information, allowing them to make more sophisticated decisions [8]. AI learning is introduced in the infrastructure-based architectural-based systems which have more result in the accuracy and the beneficial purposes. For a deeper understanding of the usage of resources, AI may use accurate, robust, and practical knowledge obtained and processed by smart infrastructure. A change in urban planning and development leads to a more efficient and secure infrastructure that is better tailored to the needs of people. The data collection are carried through the process by the collecting the individual responses.

1.4.2 Social Infrastructure-Based

The standardization position involves many facets of the smart city’s architecture, organization, and functioning. Indian national smart city has principles that govern the unified criteria for radically new possibilities of centralized urban process management. The article describes the social infrastructure roles and tasks of single-industry cities, which should be taken into account in the introduction of the smart city framework. The Figure 1.4 shows the physical infrastructure workflow. The selected fields of operation set out in the smart city concept are closely linked to the growth of single-industry social infrastructure [8–10]. The dynamic system of social engineering that lead to enhancement of quality of life through the use of innovative decision-making technology through the economic and the eco-friendly of the life systems.

This entire infrastructure aims system of objects essential for the promotion of human activity, communications, as well as businesses, organizations, and organizations, delivering social and household services to the community, management bodies, and workers whose operations are structured to meet the social needs of people in conjunction with the quality of life indicators created [11]. Certain areas should be covered in the social engineering process like the electricity supply with the higher energy and sustainable solid waste management robust connectivity and digitalization.

1.4.3 Urban Mobility

Mobility system encompasses a variety of operating technology used for the purpose of transportation system and also in management system, including the payment facilities, monitoring remote display devices which are used to track and maintain the traffic conditions along transport routes [12].

1.4.4 Solid Waste Management System

This scheme allows for the systematic storage of sewage in well-designed sewers that are delivered to the Sewage Treatment Plant (STP) to be handled there in such a manner that the effluent follows the parameters specified by India’s Central Pollution Control Board. For horticulture, road-side drainage, road sweeping, and irrigation, the treated water can be recycled.

1.4.5 Economical-Based Infrastructure

Innovation-driven and university-supported economy focuses on cutting-edge innovation, not just for technology, industry, and business but also for architecture, planning, growth, and the cultural heritage. Cities are a prosperous location, but their prosperity depends on their population size and other factors. In the last two decades, urban India has developed at an exponential pace [14]. An optimistic estimation of India’s population growth indicates that the total population is projected to hit around 1.5 billion by 2031, with an increased urban population of about 600 million, or about 40%, by 2031.

India has the large economic growth development in the world. Unfortunately, economic data is not calculated for urban agglomerations, but rather for the district administrative unit, which has no association with the border of urban agglomerations. In India, the extent of urbanization of the different states and union territories varies widely. The increased population base of cities resulted in higher demand for manufacturing goods and commodities. This was the case of cities and towns which grew in Europe in the 19th century in the industrial belts and regions. More often, a polycentric, nature-based and people-friendly urban structure was invented when center city regions became congested with growing population and increasing industrial emissions [14, 15].

1.4.6 Infrastructure-Based Development

Spending on infrastructure is crucial not only for the development of India and for sustaining the region’s fight against poverty but also for laying the foundation for stronger future economic growth. The 11th Plan emphasized the importance of investment in infrastructure to achieve a sustainable and inclusive increase in GDP of 9% to 10% over the next decade. The growth of infrastructure is a core focus of the 11th Five Year Plan of the Government of India (2007–2012). In 2010, the nation initiated 94 new projects and saw an investment of US$71.9 billion in 2010, a rise of 85% from 2009. The investment is the highest amount witnessed by any developed nation in the entire 1990–2010 period in any given year [16]. In 2010, India alone accounted for 43% of the overall expenditure in private ventures in developing countries.

1.4.7 Water Supply System

The consistency of the groups of organic surface and groundwater, known as raw water, will also not fulfil the quality requirements of domestic and industrial consumers. In such cases, water treatment is required prior to its use. Water, typically via a network of storage tanks and drains, can be collected and circulated throughout the metropolitan environment until handled. Figure 1.5 shows the water supply chain in city structure.

1.4.8 Sewage Networking

The concentrations of municipal sewers and their amounts of pollutants differ over a typical day of a typical week and over the course of a year. The conditions of flow may differ from free surface to supercharged flow, from constant to turbulent flow [18], and from static to non-uniform flow that varies rapidly or gradually.

1.5.1 Availability and Ideal Consumption of Resources

An equal and responsible distribution of services, including water and power, will be a smart city is most prominent feature one, which often requires access to proper sanitation and the disposal of solid waste. In order to ensure availability for future generations, smart cities must ensure proximity to services while placing a focus on the conscientious consumption of natural resources.

1.5.2 Anticipating Future Demand

India has becoming the most populated country around the world in the near decade. So, urbanization is expected to grow to 50% by 2030. Therefore, urban planning agencies need to consider potential demands to control and track the use of energy in today’s society. In industry and workplaces, we witness routine sanitization campaigns, daily sweeping in households, and intensified handwashing. It is estimated that a family of five needs 100 to 200 liters of water per day just to wash their hands. This would result in the development of about 200 liters of wastewater each day that would raise water demand and waste water generation from human habitation by 20% to 25%.

The aim of the architecture is to provide numerous APIs as well as visual web services with public smart city information via data [13]. In this particular instance, the system design can make it easy to transmit sensor data to a back-end system and be incorporated into the “standard” city monitoring system.

1.5.3 Transporting Networks to Facilitate

Multiple major companies, such as OLA, Uber, and the car manufacturers, are increasingly developing autonomous vehicles. For self-parking vehicles, the Indian Department of Transportation has just paved the way. This are projected to be on the market and generally available as early as 2020, likely with significant market shares. More users in the city nowadays are using the private transport more than the public transportation such that it has some effects in the public transportation and lead to more pollution around the economical city [16]. They should encourage the public mode of transportation to others and to help the environment.

It is possible that traffic control in a smart city would be drastically different. Future methods would be collaborative, unlike the individual driver-focused current solution, where the aim is to maximize flow in a road system. This could include a drop in waiting times for traffic lights and average delay, a decrease in mean cumulative travel time, or an increase in overall highway productivity. Traffic management now also uses traffic light networks that track road traffic with timers and sensors [17]. Efforts are being made to develop software that can forecast traffic flows, a smart trip simulation system built on the neural network that can simulate speed profile conditions with a high degree of accuracy at various sensor locations.

1.5.4 Control Centers for Governing the City

Recognizing these threats and prospects, the government of India initiated the 100 Smart Cities Mission in June 2015. Almost 100 smart cities have been established since the mission was launched and cities have begun to implement public infrastructure and ICT initiatives according to mission guidelines. Cities have conceptualized projects that enable them to do more, increase their organizational effectiveness, and provide residents with timely and reliable services.

1.5.5 Integrated Command and Control Center

The Integrated Command and Control Center (ICCC) serves as the “Nerve Center” for Operations Administration, Day-to-Day Exception, and Crisis Management. It also provides insights through the analysis of diverse aggregated data sets to produce information for better planning and policy making. The ICCC is intended to aggregate information through various applications and sensors distributed across the region and then provide actionable information with sufficient representation for decision-making. Although few cities have begun implementing ICCC with necessary software, networks, and sensors under the Smart Cities Mission, they are at different stages of maturity as far as informed decision-making is concerned [19]. As these ICCCs are introduced, it is imperative to assess the sophistication of productivity using a common methodology across the world ensuring that improvements made by cities can provide sufficient benefits for cities and people in the future.

While few cities have begun to deploy ICCCs with the necessary software, networks, and sensors under the Smart Cities Mission, they are at different stages when it comes to informed decision-making. As these ICCCs are introduced, it is imperative to assess the sophistication of productivity using a common methodology across the world ensuring that improvements made by cities can provide sufficient benefits for cities and people in the future. The purpose of this evaluation system is to provide communities with a do-it-yourself toolkit to measure the maturity and efficacy of the Centralized Command and Control Center in municipal operations management, day-to-day emergency management, crisis management, preparation, and policy-making.

It is envisaged that the ICCCs would be the brain of metropolitan service, exception handling, and crisis management [19, 20]. Figure 1.6 shows the smart city control flow for command and control centers. Sensors and edge devices can collect and produce real-time data from different services such as water, waste management, electricity, accessibility, the urban environment, education, health, and safety.

The ICCC used to the following:

1. Enhanced understanding of circumstances by providing information through sensor deployment across the city for civic officials through urban functions.
2. Standardizing urban response protocol by developing modern protocols for repeated incidents, complaints, and requirement scenarios.
3. Strengthen cooperation inside and beyond various agencies local urban bodies and municipal authorities.
4. Institutionalization of daily activities decision-making guided by evidence and in the case of a crises around the city level—from the owners to the city managers.
5. Engaging on-site service workers in dealing with social concerns and residents’ complaints.

1.7.1 Fundings

Web-based market models match the trends described above. These findings suggest that the open pattern “conquers” web-based models, though there are still unbundling instances. Except in web-based situations, contemporary business models remain and the city acts as a direct information and service provider to its residents and businesses, on the other side, published on different smart city market models. While market models are not to be followed in public institutions (i.e., Masdar and Gdansk) [24], even in these ways the municipality uses smart cities to draw tourists, inhabitants, and investment. These studies also named members to two contemporary business model classes:

1. E-Service market model.
2. Openness in ownership of the private enterprise and the ICT network.

A specific provider (or stakeholder groups) was treated as provided in each service category. The network owner creates value for people and businesses. A significant result of this assignment process is the appointment of business model trends in cases that have no relevant network-related business models. This is fair because all of these municipal types need different resources (networks and grids, sensors, etc.). The unbundled trend is still in effect even though these facilities are leased for service provision. When the IoT is used as the main resource that results in the IoT market models involved, circumstances change [24, 25]. In the above-mentioned situations, though, cities have still not capitalized IoT, which helps start-ups and other vendors to build value.

1.8.1 Smart Medical Care

This approach aim, however, is focused on the individual experiences of professionals and/or neighborhood associations, to recognize the health concerns of the whole community. The value of such an approach is both cheap and constant, but it lacks the rigors of more rigorous quantitative methods and less likely to detect latent challenges within the group. In comparison, the practice of formal group consensus methods will address this role more thoroughly and rigorously in order to create consensus strategies so as to avoid narrowing the number of possible problems to consider, as is the tendency of various quantitative approaches.

Using data, however, the data must be extrapolitanized from wide region information in order to recognize urban health issues. The validity of the method ultimately relies on the amount of burden the wide region has taken on the society [21]. By using secondary data, such as vital statistics and census data, more comprehensive research is difficult for the practice as general problems are established.

Tendency, though to rely on some health conditions, may miss a significant issue merely because it was not part of the dataset. For example, an epidemiological analysis of diastolic blood pressure within the population may produce advanced data on distribution, correlates, and hypertension determinants. At the cost of a larger data collection, though, the information in the hypertension set is collected. The use of these data to classify the health issues of the population may also make it easier for the profession to ignore some (maybe more critical) problems of health.

1.8.2 Smart Safety for The IT

A smart public safety infrastructure is being built to provide the public with a better atmosphere for ordinary people. This system is complicated, distributed over all campuses of the University. It consists of a smart cameras tracking system, a backroom system with workflow engine and a smart-phone device within the context of a collaboration concept. The intelligent cameras are deployed and this last year the smartphone device and the back-office device with acceptable results are used. The smartphone app is the user entry point for documenting many problems pertaining to security and campus management which are instantly forwarded to the responsibilities team when they are taken directly in the event of security or join an integrated working flow engine when running the campus [21]. This paper reveals the framework for achieving a more intelligent climate for public protection, specifics of operation, and statistical evidence obtained by the system.

1.8.3 IoT Communication Interface With ML

The preparation and preparing of information for such interactions is a critical activity. To respond to this issue, various types of data processing, such as edge analytics, stream analysis, and database IoT analysis, must be applied [22]. Computing frameworks play an vital role in connecting the server with neighboring computer structures and frameworks that depend on the location and the processing server where the data is processed. Architecture is basically classified into several categories for the networking and filter data for data centers.

Edge Computing: This approach to computation allows data to initially be stored on edge computers. Edge devices cannot be linked continuously to the network, so a backup of the master data/reference data is required for offline processing.

Cloud Computing: This approach and the design has high latency and high load balance, which means that this architecture is not ideal for the processing of IoT data since it can work for other processing at high speeds.

There are several other type of cloud computing services like Iaas, Paas, and Saas. These are equipped with the data transmission via API or several other SDK kit for the user interface.

1.8.4 Machine Learning Algorithms

ML allows a computer to automatically learn and grow (without directly being programmed). Overall, ML algorithms can be classified as being (i) managed, (ii) unmonitored, and (iii) evolutionary computation. In reinforcement methods, a description is associated with each input value, while input values remain unlabeled in unsupervised learning. Learning algorithm implements a reinforcement-based mechanism in which the goal is to choose the set of environmental activities that optimize the overall benefit. There are some several types of machine learning algorithms, namely, SVM (Support Vector Machine). For both classification and regression queries [33], SVMs are valid, but they are widely used for the former. A binary SVM performs a binary division, generating a hyperplane such that it is possible to classify input values into two groups.

For applications with a restricted number of stakeholders, SVMs are highly important. The system relies on numerous voice recording sensors to track the voices of patients such as handheld computers, voice recorders, and smartphones. To differentiate between the characteristics of good and unsafe consumers at a higher accuracy rate, SVM is then added to the data (on a cloud-based server). Storage processing method in the machine learning branched into cloud storage and processing and edge storage and processing.

1.8.5 Smart Community

The entire SCM program is supervised by an Apex governance system which consists of many national committees at state and city level. The SCM is a three-level governance structure. A special purpose vehicle (SPV) is used for executing the mission on a city scale. The SPV manages the funding, executes the programs, and administers and reviews them. The company is headed by a full-time CEO and has nominated on the board by the Federal Government, the State Government and ULB (Urban Development Ministry, 2015) [26]. The SC schemes are carried out by joint ventures, subsidiaries, PPP, etc. In addition, the cities have used a convergence process to support the SC initiative. These structures of convergence allow the cities to receive funds from other successful missions such as Digital India, Housing for everyone, production of national patrimony skills, and the Missions of Swachh Bharat, for the creation and development of a number of intelligent cities initiatives.

Countries and clever communities are regarded as a catalyst to boost city citizens’ quality of life. However, due to insufficient evidence, in particular from developed countries, current awareness of the risks that could hamper the progress of smart city projects remains minimal. A rare incentive is the new SCM in India.

Examine the risk type, possibility, and consequences on adoption of smart city projects, including risk definition data in the submitted smart city proposals for the Area Projects (ABD) (small scale) and Pancake Projects (large scale) [24]. We have used (quantitative and qualitative) theme modeling for risk classification, followed by risk effect analysis for priority assessment and a keyword co-occurrence network.

1.12.1 Stakeholder Benefits

A policy with consistent advantages assigned to particular stakeholders is a success indicator that can be visible in the ongoing input obtained from stakeholders, showing the smart city components’ level of fulfilment or dissatisfaction. For strategies which are formed on the basis of specific needs, a observable effect is more probable. For ordinary people and for senior leadership who need to be on board with the strategy, particular plans can be very complicated. It is necessary to spend the extra time putting in the strategies that both political officials and people can clearly grasp in detail.

1.12.2 Urban Integration

In most cities worldwide, the incorporation of technology within the public sphere is an evolving theme. It is important to enhance the quality of life for residents to have an urban planning aspect within the Smart City Strategy.

We have also seen examples of the accelerated introduction of technologies in our cities and no concern about the effect on customer care or the experience of people [30]. There are also innovations which have not been prepared for or have not been integrated with other agencies. This may look “cool” for some of the more technically focused persons; it will reflect and depict for others.

The community’s picture of chaos: As part of policy growth, attention should be given to implementation guidance. The implementation of the Smart City Strategy as an organized initiative within the urban master plan phase is one solution. This strategy means that, at the highest level, the discussion about technology and the built environment takes place. Strategies seek to describe a wide range of programmers and projects with longer horizons in time for distribution. Some are more fundamental; others are beyond some. With the pace of technological transition, by the time they are finished, even short-term programmers that fund efforts will look different. Spending too much time on the strategy’s technological specifics can just make it seem obsolete in a limited timeframe [30]. The strongest implementations of technologies are those that offer societal advantages, are not physically distracting in the public domain, and are applied with a long-term view.

1.12.3 Future Scope of City Innovations

In our modern world, many cities are facing big obstacles, such as a rising population, a shortage of physical and social resources, environmental, and regulatory standards, diminishing tax bases and budgets, and higher prices. They need to learn how to recognize innovative and intelligent ways of handling urban life’s complexities and challenges ranging from congestion, overcrowding, and urban sprawl to insufficient infrastructure, high unemployment, resource utilization, conservation of the environment, and increasing crime rates.

Cost efficiencies, resilient networks, and an increased local environment result from the use of smart city technology [31]. When it comes to designing the cities of the future, “smart cities” is the new term. To bring a new brand and distinctive appeal to the lifestyle, smart cities are supposed to be the cornerstone to balancing a prosperous future with sustained economic development and job production.

Cloud-based output and storage face common obstacles to smart city applications. For example, the complexities of cloud-based smart grids include cost-effective provisioning without replacing ageing infrastructure and stable integration of modern capabilities with existing networks [33]. Although the ML has both added advantage and disadvantages, it leads to the deep learning process which enhances development in the technologies like the data visualization in real-time modern world.

Development accomplished by cities is tied to their desire to holistically solve urbanization-based problems and related social, environmental, and economic issues, while at the same time making the most of potential opportunities [30]. It is possible to interpret the smart city idea as a paradigm for incorporating this vision of advanced and modern urbanization. In future, vision is the urban center of the future, making sustainable, safe, eco-friendly, and competitive as all buildings are designed, built, and controlled using new, manufactured materials, sensors, electronics, and networks integrated with computerized systems consisting of databases, surveillance, and de-connected networks.

1.12.4 Conclusion

To make civic processes more cost-effective and environmentally competitive, smart cities make use of digital technologies. By turning streetlights on only when a road is in service, sensors installed in buildings and grid networks will help communities embrace green technologies and conserve electricity [32]. Sensors, smart cards, and digital cameras feed real-time data into advanced control systems, and better infrastructure and analytical technologies will enable decision-making. Rapid urbanization has contributed to extreme road jams as large numbers of citizens choose to enter cities by vehicle. As a result, air pollution has been a major challenge for cities. Development in smart cities has led to the introduction of creative integrated transport networks designed to satisfy the needs of residents. For starters, able to implement real-time mobility systems, smart travel passes, shared car trips, smart vehicles (driverless cars), and personal rapid transit.

One of the largest smart city projects currently taking place is the India Smart Cities Competition, a contest where 100 cities can receive funds from the Ministry of Urban Development and Bloomberg Philanthropies. Competition is meant to promote more innovation from municipal officers and their partners, as well as more involvement from people, in the development of smart city plans [31, 32]. As several critics find out that critical needs such as drinking water and sanitation need to be resolved, this problem has been scrutinized.

Using technologies and data improves resistance to urban problems, through greater efficiencies, and using creativity and industry introduces these fantastic opportunities for our communities. Those with good leadership and productive public-private collaborations working with community participation are the cities positioned to build on these possibilities.