Emerging Technologies for Sustainable Smart City
Smart city is emerging as a new alternative to solve various urban issues such as urban aging, traffic congestion, energy shortage, environmental pollution, and crime. Smart city is the key to discovering converged new industries that will dominate the 4th industrial revolution through data, network, and artificial intelligence (AI). Recently, there has been an increase in the number of attempts to solve urban problems using network technology both domestically and internationally. The smart city platform is emerging as an innovative growth engine centered on energy, transportation, and security by utilizing information and communication technology (ICT) such as AI, big data, 5G, and network. According to a UN report, population growth in urban areas is expected to reach 66% by 2050, with 70% of the world’s resources consumed in cities.
Deployments of Smart City Applications
The idea of deployment applications in smart cities is closely linked to several concepts of communication technology (ICT), that is, the mass adoption of interconnected physical objects, devices, and so on. It can be considered a system of systems when deploying intelligent city applications consisting of several interconnected objects. The simplification of the system involves the diffusion of sensor technologies that allow identifying objects, collecting data and communication resources, and facilitating data distribution, information processing, computational analysis, and connection systems to improve and save urban functions and resources for the improvement of environmental performance. Therefore, in digitalization, a new digital layer is placed between the conceptualization of the infrastructure of the city and the layer of service of the city.
Smart city governance: In the case of smart governance, the government is transparent in its actions if they are active participants in its decision making. Using emerging technologies, the city’s functionality can be effectively delivered to citizens through a well-connected governance system.
Smart mobility: Promoting sustainable urban mobility is a hallmark of smart cities. One of the main goals of smart cities is to provide innovative transport services through smart traffic management. It allows for safer and smarter decisions on how to use the transport network by providing the required information to users. For instance, to facilitate services such as surveillance, traffic control, car navigation, parking guidance, etc., various technologies can be applied to improve traffic management.
Smart utility: Smart streetlights are considered to be applications that help reduce energy consumption and which can work depending on the traffic and weather conditions. This can enablethe smart city to create a sustainable eco-friendly ecosystem.
A social service system can be set up to handle people’s complaints in everyday life, personal management of social affairs, requests for assistance, and various other aspects to cover the management of the city and the functioning of the market. A single integrated system is needed to provide a platform for facilitating these services.
Smart living: The current health system is faced with significant challenges in the provision of low- cost, quality health services. With an increase in the elderly population, these challenges are compounded, which translates into a chronic horde of diseases as well as greater demand for health services. In some cities, too, getting a proper healthcare service is difficult due to the lack of limited resources. Because of these aspects, it is necessary to evolve the current health system into an intelligent health system. Smart health is defined by a concept that involves several technologies and entities, which include various portable devices, sensors, ICT, and many other devices . Smart healthcare includes several different components: intelligent hospitals, emerging in-body sensors, and intelligent response to emergencies. Different technologies are used for its operation in smart hospitals, including cloud computing, ICT information technologies, advanced data analysis techniques, and smartphone applications. From several smart city hospitals or several hospitals, offices can access patient data in real time, allowing the test data to be shared among several physicians, technicians, and nurses; thus leading to real-time decision-making about patients’ health conditions and corresponding medications.
Smart environment: Smart services are considered to be capable of providing real-time information about environmental pollution in cities by monitoring environmental changes. Citizens and governments may be aware of the adverse effect of changing their behavior in relation to public services, such as gas, electricity, and water.
Integrated Technologies in Smart City Network Security
This section describes edge computing, Blockchain, AI, software-defined networking, and big data analytics technologies implemented in a smart city environment and explains the data problems and solutions that occur in a smart city.
Smart cities require applications that provide real-time services to its citizens, which is challenging to achieve when IoT nodes connected directly with the cloud layer result in data traffic bottleneck. The landscape of smart mobility is expanding – incorporating new ways of using data to help us get around. The fast and effective use of data helps to make mobility of all types cleaner, safer, and more enjoyable. However, the existing paradigm of cloud computing lacks the real time and offline capabilities, to ensure that mobility users have a safe, seamless experience. Edge Computing is a critical tool to curb high cloud costs, improve user experience, ensure real time response rates, and protect personal data amidst increasing regulatory standards. Ensure Offline-capability and Reliability: Whenever you are on the move, at some point you will not have an Internet connection. Many mobility use cases require offline capability – for example, while on the move, in underground garages, or in remote areas. Sync Data and Save Costs: Edge Computing has many benefits, but many projects need to access part of their data in a central location, i.e. via the cloud or an on-premise server. With this technology, you choose what parts of your data to synchronize and when, giving you reliable access to the data you need, while keeping networking and cloud costs down as projects scale. Improve Sustainability with Edge Computing: The number of IoT and Mobile devices is growing – imagine if we made use of these devices for storing and processing data, rather than sending all of our data to data centers. Not only does this improve energy efficiency (by reducing the burden on overtaxed data centers), it also produces inherently more sustainable computing architectures, encouraging the use and processing of data, reducing the amount of inoperative data stored in data centers
AI is often dubbed as the technology that justifies the term smart in smart city. AI is commonly used to provide solutions such as voice and facial recognition, provision of security to networks from foreign intrusion, device profiling for authentication, analytics to optimize IoT device performance in a smart city, etc. Cognitive science is recognized as the next frontier for AI where smart applications can provide personalized solutions based on human brain-like thinking. Human traits, such as brain activity, emotions, spatial-temporal data, gestures, etc., are used as features to train machines to think and behave like human beings. Experts suggested the use of combining brain activity such as perceptual and rational thinking with Deep Reinforcement learning algorithms. Applications can be used to detect and analyze objects the way humans do. Traditional machine learning methods suffer from limitations, i.e.,they cannot recognize new objects apart from the ones they have been trained to identify. Cognitive computing-based AI allows a mapping relation to be established between the figure of the object and logical definition of the object.AI based ITMS is already implemented in Jammu. Jammu ITMS is a technology that employs artificial intelligence to assess traffic in real time. When implemented it is likely to change the traffic scenario in the city. As of now violations are getting auto detected. Next real time traffic information will be passed to commuters. The human interface in road management will be reduced and traffic signals will operate automatically during the day depending on traffic volume and average speed on the road. As part of ITMS, high resolution video cameras is installed for a traffic pattern analysis. Once the detailed project report is readied, and the system’s is implemented traffic police hope to see the changes on the ground by next year.
Big Data Analytics
Smart cities generate enormous amounts of data, so they can be used to serve its citizens more efficiently. Big data offers smart cities the means of obtaining insights from the data collected from various IoT devices spread throughout the city. This data is used to provide valuable insights that are used to optimize the performance of machines in smart city domains such as energy, industrial IoT, homes, buildings, etc. Experts proposed a helpful 4-tier model for big data analysis in urban planning. Data is extracted from IoT devices in smart city domains such as automobile networks, smart parking, weather, pollution, surveillance, etc., to allow authorities to make intelligent decisions that are implemented in real time. In recent days, MongoDB is a new and popularly used database. It is a document based, non relational database provider. Although it is 100 times faster than the traditional database but it is early to say that it will broadly replace the traditional RDBMS. But it may be very useful in term to gain performance and scalability. A Relational database has a typical schema design that shows number of tables and the relationship between these tables, while in MongoDB there is no concept of relationship.
MongoDB is schema less. It is a document database in which one collection holds different documents.
There may be difference between number of fields, content and size of the document from one to other.
Structure of a single object is clear in MongoDB.
There are no complex joins in MongoDB.
MongoDB provides the facility of deep query because it supports a powerful dynamic query on documents.
It is very easy to scale.
It uses internal memory for storing working sets and this is the reason of its fast access.
Distinctive features of MongoDB
Easy to use
Extremely faster than RDBMS
Where MongoDB should be used
Big and complex data
Mobile and social infrastructure
Content management and delivery
User data management
Extremely faster than RDBMS