How IoT and Computer Vision Revolutionize Parkings

Traffic congestion, crowdedness, air pollution and other problems of large cities are the reason we seek efficient solutions that could improve the quality of life. With the lack of parking lots in overcrowded places, you must have at one point come across an issue to find a vacant slot in the city center during business hours. The average search time could take from 10 to 20 minutes, not to mention extra liters of gas.

However, one project that could save all these problems, including the drivers' time, is combining the Computer Vision and Internet of Things (IoT) to create intelligent parking solutions.

Here is the list of topics we will discuss in this article:

  1. How Does Computer Vision Work?
  2. Current Use Cases of Computer Vision
  3. How Can Computer Vision and 5G Enhance IoT?
  4. Computer Vision and IoT in Smart Parking Systems
  5. How Can Smart Parking Systems Enhance Urban Infrastructure?

How Does Computer Vision Work?

Computer vision represents a field of artificial intelligence that trains computers to understand and interpret the visual world. Machines can accurately identify objects, classify them, and then react to what they "see." For this, they use digital images from cameras, videos, and deep learning models.

This process involves three steps:

  1. Acquiring an Image: Images, even large sets, can be obtained in real-time through photos, video, or 3D technology for analysis.
  2. Processing the Image: They assemble visual images by dividing them into subcomponents. Then, using filtering and a series of actions through deep learning models, they piece together the parts of the picture. Developers prepare the models beforehand by pre-identified images, so the recognition process is accurate.
  3. Understanding the Image: The last step is the interpretative one, where they identify or classify an object. With the use of an X, Y coordinate system, these models create a bounding box and recognize everything inside of it.

Current Use Cases of Computer Vision

Use cases of computer vision technology are very versatile. Some applications happen behind the scenes, while others are more visible. You have most likely already used products or services enhanced by this innovation. Here we mention some of the industries they are active in.

Autonomous Vehicles

Autnomous car sensor systems

According to the World Health Organization, more than 1.25 million people die each year due to traffic incidents. Self-driving cars were developed using computer vision technology to bring these numbers down and improve transportation for people. Companies use multiple cameras, radar, lidar, and ultrasonic sensors to acquire images from the environment. Hence, their autonomous cars can detect objects, lane markings, signals, and traffic signs to drive safely.

Computer Vision in Healthcare

In healthcare, computer vision technology helps medical professionals accurately determine illnesses or conditions that may save patients' lives. It does so by eliminating inaccurate diagnoses and incorrect treatments. With computer vision, new diagnostic methods allow analyzing X-rays, mammography, and other scans, so doctors can identify the problems earlier.

Facial Recognition Technology

computer vision and face recognition technology

Facial recognition is useful for police work, payment portals, security checkpoints, and many other applications. Cyber attacks and advanced hacking tools are on the rise today, so companies can benefit from both secure and fast technology.

Computer Vision in Agriculture

Computer vision allows farmers to adopt more efficient growth methods, increase yields, and eventually increase profit. For example, there is a semi-autonomous combine harvester that can find the optimal route through the crops and even analyze grain quality as it gets harvested.

How Can Computer Vision and 5G Enhance IoT?

Computer vision is giving rise to revolutionary leaps in IoT innovations and applications when combined with advanced data analytics and artificial intelligence. It is present in everyday products, from cell phone cameras that can automatically set focus on people to game consoles that recognize your gestures.

The ability to automatically detect and classify predefined patterns in real-world situations represents a huge market opportunity with hundreds of use cases. Even the smallest enhancement, such as a live face filters app, greatly affects our everyday lives. The app scans your face using face recognition, reads facial features, and adds AR content to it. It is a simple but engaging and fun experience.

The quality in performance of any IoT depends on how quickly it can communicate with other IoT devices, smartphones, or software. With 5G, data-transfer speeds will increase significantly, and networks will have more stable connections. This is extremely important for any IoT, but especially for connected devices like security cameras, locks, and other monitoring systems that depend on real-time updates. Furthermore, it will bring a 90% reduction in power consumption, guaranteeing up to 10 years of battery life in low-powered IoT devices.

Computer Vision and IoT in Smart Parking Systems

IoT and smart cities concept

Smart cities mostly use IoT technology for parking issues. It consists of installed sensors that can determine the location of empty parking spaces. All the IoT data is then transmitted, collected, and analyzed in real-time in a cloud server. As a result of this process, people can have access to a map of available spaces.

Each IoT sensor is installed in the parking space surface. If the vehicle is occupying the area, the sensor can identify the distance to its undercarriage. However, they alone cannot scan license plates, so the government is obliged to use cameras and parking meters.

This is where computer vision comes in. Governments can use video surveillance cameras or install ones on light poles that will use computer vision to mark parking spots with no parking meters. These cameras are able to identify the cars that are parked and measure the parking duration. They use automatic number-plate recognition technology that is based on optical character recognition. With this data, the inventory of all available spaces can be updated in real-time using computer vision. Therefore, drivers can use their mobile app to allocate or guide them to a vacant parking spot. It is especially useful for disabled drivers.

By scanning license plates and a car model, computer vision systems identify drivers and track how long each car has spent in a parking spot. This information allows parking systems to process payments automatically. A solution like this could also detect violations and solve crimes, such as car thefts.

Parking systems can also implement dynamic prices with computer vision. This means adjusting parking rates according to specific time slots, days, or events. It can increase parking-related revenues and reduce congestion by allowing drivers to use nearby parking spots that may cost less.

How Can Smart Parking Systems Enhance Urban Infrastructure?

intelligent parking systems

When you implement smart parking systems, they start collecting massive amounts of data about parking availability, the number of cars, and general parking inflow. This information can help city planners make adequate upgrades to existing urban infrastructure to tackle future traffic and parking demand. For example, it can help in deciding on new locations that need more parking spots.

These solutions can become even more advanced by using blockchain in parking systems. Combining it with computer vision, analysts can create a secure database of all available parking spaces and implement payments in cryptocurrencies.

In order to better prepare themselves for a sudden influx of traffic and demand for parking, cities can mandate every parking space owner to implement smart parking solutions. With each parking lot business sharing data with local municipalities, they can dig deep to ascertain hourly demand each day.


In this post, we had a concise introduction to computer vision and how it is becoming a critical component of many connected IoT devices and applications. Most of all, we focused on their imminent revolutionizing impact on smart parking systems.

To make sure you got it all covered, below is the summary of the mentioned topics:

  • Computer vision is a field of artificial intelligence that enables computers to see, identify, and process the visual world in a way that surpasses human visual abilities.
  • They can recognize objects in the picture by comparing them to pre-identified images stored in their memory.
  • Computer vision has a versatile use and can be found in many industries, such as healthcare, self-driven cars, facial recognition technology, and agriculture.
  • It's a huge marketing opportunity that is enhancing IoT innovations and applications in several aspects.
  • 5G improves IoT by providing more stable and faster network connections. This is crucial for some IoT devices like security cameras, locks, and other monitoring systems that depend on real-time updates.
  • IoT technology uses sensors to determine the location of empty parking spaces, collect data, and form maps for users to find available parking lots quickly.
  • Computer vision can monitor parking spots with connected cameras. They use automatic number-plate recognition technology to scan license plates and identify which cars are parked and how long.
  • Parking systems can automatically process payments based on the time they parked the car.
  • The information collected by the connected cameras can help in upgrading urban infrastructure, for example, deciding on locations that need more parking spots.

With these two solutions, people can develop a competitive business model affordable for both city councils and car owners. It certainly offers more benefits compared to the existing products.


Michael Yurushkin

Founder of BroutonLab, PhD