How will Computer Vision aid Authorities in Managing Smart Cities?
Computer vision enables improved infrastructure and effective governance across smart cities.
Computer vision is a technology that enables the computer to analyze, see, and understand digital images and videos so that insightful information can be extracted to perform various processes. Like biological vision systems, computer vision performs all tasks by automating and simulating the elements of human vision using sensors, and machine learning algorithms. The global market size of computer vision is expected to grow from US$ 10.9 billion in 2019 to US$17.4 billion by 2024, at a CAGR of 7.8% during the forecast period.
Due to its robust system interface, it is readily leveraged across the industry. From healthcare institutes to manufacturing units, computer vision is driving the pace of innovation. In the digital era, the concept of smart cities is gaining momentum. This implies adopting technological innovations such as AI-driven tools, smart cameras, and IoT devices, amongst others, for advanced infrastructure and development policies across the cities. As smart cities aim to succeed with a digital future, integration of computer vision ensures effective transportation and governance module.
Improved Traffic and Infrastructure
Traffic congestion is amongst the major challenge which hinders effective management across smart cities. With an increase in population and the surge in automobiles, peak hours, especially mornings and evenings, become distressing for the commuters due to traffic. Additionally, a major challenge is posed to the traffic management system for monitoring and management of traffic. Even with high-end cameras and traffic management tools, managing the traffic becomes a taxing task. Incorporating computer vision across smart cameras enables traffic control rooms to identify areas that are posed with heavy traffic routinely. It also aids in identifying the silos within traffic management.
For instance, scarcity in road infrastructure often leads to an increase in congestion in different areas. Often, local authorities ignore this issue, which leads to an escalation in accidents and traffic congestion. Integrating computer vision tools in smart CCTV cameras supports the local authorities in identifying areas with a dearth of infrastructure and deploying solutions for effective traffic management. Through this, the accretion in pedestrian and vehicle accidents will also be controlled.
Cost-effective Electricity Solution
The incorporation of computer vision also helps in monitoring electricity consumption across buildings and streets. In smart cities, most buildings and street lamps are equipped with IoT-enabled smart lights. The electricity consumption depends on climate change and season. By integrating computer vision tools, will automatically turn off the lights, when humans are not present in the vicinity of the streetlights and the building.
Maintaining Law and Order
An increase in the crime rate has added to the concerns of effective governance in smart cities. An increase in crime not imbibes a lack of trust in local authorities, but also make the citizens live in constant fear.
For effective law and order and security, measures must be taken before the crime takes place. By incorporating computer vision in smart city devices will enable swift alertness of authorities during unfortunate incidents.
For example, in riots, sexual harassment, or gang fights, the smart city devices enabled with computer vision can sense heavy human activity and alert the local patrolling officers regarding the unpleasant incidents.
Maintaining Citizen database
Additionally, as computer vision is trained with image recognition, citizens’ database can be created and maintained. This database will include demographics of the citizens, their health records, and criminal history, and can be stored in the cloud, for easy access across all the departments. For example, during an accident, the healthcare authorities can access the concerned individual’s demographics and blood type to reach out to individuals with similar blood type for blood transfusions.