Smart cities are constantly developing and will continue to play an important role in humanity’s present and future. Cities continue to be multi-hubs of business, technology, and culture, but also major drivers of pollution and inequality, generating 80 percent of global GDP and creating more than 70 percent of yearly global carbon emissions. Promoting and sustaining economic development, prosperity, and equity is a critical goal as well as a serious task.
However, in order to attract and expand investments in urban infrastructure, respective authorities will need to highlight smart city digitization.
To continually monitor the efficiency of the city, smart cities utilize a combination of low-power sensors, cameras, and AI algorithms. The usage of computer vision and other similar technologies benefits governments considerably. These technologies make it simple for city managers to integrate and manage assets.
What is Computer Vision?
Computer vision is among the branches of artificial intelligence that concentrates on developing and utilizing digital systems to process, analyze, and interpret visual data, allowing computers to comprehend the visual world. For instance, it involves understanding and interpreting images pixel-by-pixel. To collect multi-dimensional data, computer vision projects convert digital visual input into clear descriptions. Furthermore, in order to facilitate decision-making, this data is translated into computer-understandable language. This area of artificial intelligence’s major goal is to teach computers how to get data from pixels.
Computer Vision in Smart Cities
Smart city solutions have become available during the last 20 years because of advancements on the Internet of Things (IoT), Artificial Intelligence (AI), Deep Learning, and Cloud Computing. They provide enormous promise to address societal, pandemic, and infrastructure-related problems.
Computer vision is an innovative technology, but it really lights up when used in practical applications, such as the case of a smart city. The term “smart city” refers to a city that uses modern technologies to operate efficiently. Cities can automatically extract data from videos and images and use this knowledge to better comprehend the visual world. Furthermore, it is employed to keep an eye on many things and provide real-time information and data to urban residents and places.
It has numerous uses in city management, ranging from the controversial subject of generating facial recognition surveillance devices to assisting in the preservation of infrastructure like bridges, tunnels, and highways. When used appropriately, computer vision can offer visibility into whatever it is you want to observe more carefully, which can have a significantly better societal influence.
Computer Vision Applications in Smart Cities
Computer vision is vital in smart city management because it serves as the city’s “eyes.” Some of the most important computer vision applications for smart cities are as follows:
Smart Traffic and Bicycle Monitoring
Increased vehicles typically equal more traffic congestion, longer travel times, accidents, local air pollution, and carbon emissions, not to mention a general sense of tiredness, tension, and worry. An edge-enabled computer vision system may use new or existing street cameras to capture a real-time image of traffic conditions, which is then correlated with particularly trained machine learning algorithms.
Intelligent Parking Monitoring
The use of computer vision technology can assist authorities in providing improved services, such as car park administration. Drivers hunting for available parking spaces account for a significant share of daily traffic delays and emissions in a crowded metropolis. Using parking lot AI cameras, it is possible to identify vehicles entering or exiting a parking place, recognize plate numbers automatically, and record the parking duration. All the information presented above may be transferred into a single, cloud-based database, allowing local officials to save money on parking enforcement.
Monitoring of Public Space
Cities are responsible for public infrastructure such as water treatment and distribution systems, electrical networks, telephone equipment, street lighting, roads, tunnels, and bridges. The certainty of a significant number of infrastructure-related incidents, on the other hand, can put even the best-resourced teams under strain, resulting in a response that is neither swift nor optimum. City officials, on the other hand, will be able to make effective and efficient decisions more quickly if a cloud-based system has access to footage from all local CCTV networks, analyses it, and automatically advises on appropriate measures.
Smart camera applications in smart factories provide a scalable solution for automated visual inspection and quality control of production processes and assembly lines. Deep learning uses real-time item detection in this scenario to outperform time-consuming manual inspection. Machine learning technologies are more robust than traditional machine vision systems, and they do not need expensive specialized cameras or controlled settings. As a consequence, AI vision technologies might be applied in a wide range of settings and factories.
Public Safety and Health
As the Covid outbreak illustrated, there are times when municipal officials must respond to completely unexpected and novel circumstances. Computer vision systems can assist public services (such as police stations, hospitals, water treatment facilities, and traffic management control rooms) in adapting to changing regulations, correctly notifying citizens, identifying clusters of noncompliance, and taking appropriate corrective action. A violation of a health protocol, for example, in a public place, may be detected, analyzed, and managed more promptly and precisely, minimizing the risk of runaway dangers to the local population.
Governance and safety
Governments are investing heavily in smart cities for a variety of reasons. A primary motivator of smart city development is the opportunity to improve law enforcement and civilian safety. Local or federal governments can employ computer vision for smart city efforts to achieve this goal. Image sensors and facial recognition software are used to help develop a citizen database. It makes identifying and apprehending an illegal citizen easier, as well as knowing the identity of injured persons in the case of an accident. The use of computer vision in smart cities enables residents to live in a safe and secure environment.
Medical Skill Development
Computer vision applications are used in self-learning platforms to assess expert learners’ ability. The introduction of simulation-based surgical teaching systems, for example, has benefitted surgical education. Furthermore, the notion of action quality evaluation enables the creation of computer systems that automatically evaluate the performance of surgical students. As a consequence, individuals may acquire helpful feedback information that may aid in their skill development.
Future and Possibilities
According to statistics by international organizations, cities currently hold more than half of the world’s population and will hold more than two thirds by 2050. Different resources, including the environment, traffic, security, and administration, can be managed with the use of smart technologies. In other words, an AI infrastructure enables the creation of a sustainable smart city for its citizens. The environment, energy, transportation, and security are just a few of the industries where AI technologies and resources are used.
It is clear from the above that the deployment of computer vision systems may considerably enhance public services as well as the lives of inhabitants and visitors in our cities. These technologies minimize monitoring expenses while enabling for reliable predictive analysis and considerably quicker decision-making, either by conducting visual data processing solely on a cloud based IoT platform or with complementing edge AI capabilities (ECVs).
The potential for artificial intelligence to enhance people’s quality of life is huge. At various moments, we’ve seen how technology can assist cities in becoming smarter, faster, and smarter. Furthermore, the formation of such infrastructure needs a clear political framework.
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