Today's computer vision systems are suitable for many industries, from manufacturing to retail to finance. They help companies improve AI technology.
Computer vision combines cameras, edge or cloud resources, software, and artificial intelligence (AI) to empower systems to recognize and identify objects. Computer vision systems are valuable in a wide range of environments and can recognize objects and people quickly, analyze demographics and much more.
AI opens up new possibilities by helping to create more sustainable cities, oversee urban infrastructure and improve public services for both residents and communities. This revolution is based on the ability to collect data from billions of sensors and other IoT devices. While the most obvious field of application of AI in Smart cities is security, it's far from the only one that can benefit from computer vision technology. Smart cities have been at the heart of a real debate and the movement is very real.
The future and possibilities
Cities concentrate more than half of the world's population and more than two thirds by 2050, according to reports by international organizations. Smart technologies can help manage different resources such as environment, traffic, security and administration. In other words, an AI infrastructure makes it possible to make the smart city a sustainable solution for the inhabitants. AI resources and tools have an application in various fields such as the environment, energy, transport, or security.
The use of machine learning in the smart city makes it possible above all to control pollution by detecting, for example, CO2 emissions. Other air pollution prediction tools can inform authorities on decisions about reducing pollutant use.
Setting up an urban infrastructure made up of AI-powered robots allows a smart city to improve waste management . This ranges from sorting and recycling waste, to cleaning the areas concerned (lakes, rivers, etc.
Some cities use a fleet of vehicles like buses or garbage trucks that scan the streets using cameras and sensors. This makes it possible to create a 3D map of the city. This information can be used for maintenance improvements, parking, etc.
For traffic, the AI infrastructure in a smart city is mainly based on computer vision . This means the city is leveraging visual data to manage traffic. The simplest way is, for example, to place cameras in the city to identify areas of congestion in order to reduce traffic and accidents.
Another way to harness AI in smart cities is also through security. To do this, authorities use public data to identify criminals and monitor suspicious behavior.
Camera systems can also be used to implement suicide prevention systems in public spaces by analyzing visual features like typical body language movements and recognizing unusual behavior. CCTV cameras with deep learning smart city applications can be used for assessing crisis behaviors at suicide hotspots such as bus stations. The main goal is the development of automated detection systems for early intervention that can potentially save lives.
A smart world also includes the smart use of our most precious resource - water. In modern processing plants, not only water, but also large amounts of data are processed. Our smart water solutions use this information and help improve water supply, disposal and use. Connecting and evaluating different data enables safe and efficient monitoring and control of complex and critical infrastructure based on events.
Self-optimization of buildings are part of a smart city. Smart buildings are an important aspect of smart cities. If they are intelligently networked and integrated into the overall concept, buildings can contribute to the development of an efficient, stable and profitable urban concept.
In summary, a smart city is a city that knows how to structure itself to ensure sustainable urban, economic, social and environmental development, to offer its users a high quality of life, with wise management of natural resources. Artificial intelligence has enormous potential to improve people's quality of life. We've seen how it can help cities become smarter, faster and smarter at different points. Also, the development of such an infrastructure requires a well-defined political framework.
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