Smart cities employ a combination of low-power sensors and cameras as well as AI algorithms to monitor their efficiency. The use of computer Vision and related technologies is a huge benefit to governments. These technologies make it easy for city administrators to integrate and manage their assets. Computer vision is an essential part of smart city management. These are the top computer vision applications that smart cities need:
Smart Traffic, Bicycle Monitoring
An increase in urban density means that there are more cars, which can lead to more congestion, more accidents, more local air pollution, and more carbon emissions. There may also be a feeling of exhaustion, tension, and anxiety. An edge-enabled, computer vision system can capture real-time traffic conditions from existing or new street cameras and then combine this information with specially-trained machine learning algorithms.
Smart parking monitoring
Authorities can use computer vision technology to provide better services. The administration of parking spaces is the responsibility of this person. Parking lot administration is responsible for reducing congestion and traffic delays. You can detect cars coming and going from a parking spot, recognize plate numbers, record the period of parking with parking lot cameras, and even capture plates. The data can be uploaded to a single cloud-based database. This allows city officials to reduce costs when parking enforcement is being done.
Public Space Monitoring
Cities are responsible for many types of public infrastructure, including water treatment and distribution systems, electricity networks, and telephone equipment, as well as street lighting, highways, and tunnels. Still, the ineluctability of a large number of structure-related accidents can strain indeed the most well-resourced brigades, performing in a response that’s neither quick nor optimal. If a cloud-based system has instant access to all CCTV networks in the area, analyzes it, and advises on appropriate actions, city authorities will be able to make quick and effective judgments.
Smart camera applications are scalable solutions for automated visual inspections and quality control of manufacturing processes. Deep learning uses real-time item identification to improve manual inspection. Machine learning systems are more robust than traditional machine vision systems and don’t need expensive cameras or regulated settings. AI vision techniques can be used in many places and factories.
Traditional agriculture is heavily dependent on manual activities. Hand harvesting is the most common. This results in high costs and inefficiency. In recent years, high-end, intelligent harvesting devices such as picking robots and harvesting machines based on computer vision techniques have been introduced to agricultural production. This marks a new step in robotic harvesting. Harvesting operations focus on maximizing market value by ensuring product quality.
Public Health and Safety
The Covid epidemic showed that there are times when officials in municipal government must respond to unexpected and novel events. The computer vision system can assist public services (such as police stations, hospitals and water treatment facilities, and traffic management control rooms), to adapt to new legislation, notify citizens correctly, identify non-compliance clusters and take corrective action as necessary. For example, a breach of a health protocol within a public area may be noticed and analyzed. This will help to lower the risk of local residents becoming unwell.
Waste Dumping Monitoring
Littering is the greatest enemy of modern cities. The city authorities cannot maintain a near-real-time monitoring system and deterrence system. This includes the illegal disposal of garden waste, building materials, and old furniture, as well as the dangerous dumping of old batteries, used tires, and other chemicals. Street IP cameras equipped with ECV capabilities can be used to monitor potential dumping areas.
Governance & Security
Smart cities are attracting significant investment from governments for many reasons. Smart city development is driven by the ability to improve civilian safety and law enforcement. Local and federal governments can use computer Vision for smart city initiatives. Image sensors and face recognition software are useful in building a citizen database. It allows for the identification and arrest of illegal citizens, as well as the identification of injured people in case of an accident. Computer vision is used in smart cities to allow residents to live in a secure and safe environment.
Training in Medical Skill
Computer vision applications can be used to assess the proficiency level of experts learners on self-learning platforms. Simulation-based surgical teaching systems have been a boon for the medical profession. The concept of action quality assessment allows for the creation of computer systems that automatically evaluate the performance of surgical students. Individuals might get useful feedback that will aid them in their development.
Road Condition Monitoring
computer vision-based fault detection and condition evaluation are being used to monitor concrete and asphalt civil infrastructure. Pavement condition evaluation can be used to make consistent and more cost-effective decisions about pavement network maintenance. Pavement distress inspections can be done with sophisticated data-gathering equipment and/or on the ground surveys.