In highly populated cities and towns, the simple task of parking your car can soon become a nightmare, causing people to be late for plans and out of pocket from using fuel to drive circles around car parks hoping a space will appear.

Inefficient parking solutions catalyse air pollution, too, so the question we should ask is how can we improve our cities through technology to create efficient, greener spaces for the community.

Computer vision is one smart solution that is revolutionising traffic and road infrastructure, and one area contained within this which has become primed for computer vision technology in recent years is parking.

This article will showcase the potential of computer vision for parking, looking over the details of how it works and what use cases it can thrive in. But first, let’s take a quick refresher on computer vision technology.

What is computer vision?

Computer vision is a field of artificial intelligence that enables machines to interpret and understand visual information from the world including images, CCTV footage, and other visual data.

It involves the development of algorithmic models to analyse and extract meaningful insights from images or videos. Through this, computers can recognise objects, detect patterns, and make decisions based on visual data. Applications of computer vision range from facial recognition and autonomous vehicles to medical image analysis and augmented reality.

In simple terms, computer vision basically replicates a human viewing an image and reporting on what’s going on. Having a person doing this, such is the case with security watching a wall of CCTV feeds, means you’re limited to two eyes, they can’t see everything at once. With computer vision, however, millions of images and video feeds can be interpreted almost instantaneously.

Understanding how computer vision works

Here is a simple process to illustrate how computer vision works:

1. Image input

The process begins with capturing or inputting images or video frames into a computer system. These visuals could come from cameras, sensors, or other imaging devices. The feed could be live or historical.

2. Feature extraction and representation

Computer vision algorithms analyse the images to extract relevant features or data points. This involves identifying patterns, shapes, colours, and textures within the visual data. The extracted features are then represented in a format that the computer can understand and process.

3. Machine learning and recognition

The extracted features are fed into machine learning models, which have been trained on vast datasets to recognise and classify objects or patterns. This training enables the system to make decisions about the content of the images, such as identifying objects, detecting anomalies, or recognising faces.

4. Decision and output

Based on the analysis and recognition, the computer vision system generates an output or takes specific actions depending on rules. This could include labelling objects, tracking movements, making decisions for autonomous systems, or providing insights based on visual information.

Applying computer vision to parking

Using computer vision for parking, also known as smart parking, can revolutionise urban mobility by optimising the utilisation of a given space. Of the many upshots, this can reduce traffic congestion and enhance overall parking efficiency.

Through real-time monitoring and analysis of parking areas, computer vision technology can streamline the parking experience for the driver, providing them with accurate information on available spaces, minimising search times, and contributing to a more sustainable and user-friendly urban environment.

For businesses or city planners, computer vision can help them identify blindspots in their infrastructure. Maybe certain areas of congestion, or parking bays with minimal use, or a particular area prone to longer wait times, for example.

With the aid of IoT sensors and CCTV footage for video analytics, the presence or absence of vehicles can easily be detected without the need for manual checks. This information can then be transmitted and analysed, automatically identifying occupancy insights to detail, to use one example, the number of free parking spaces in a given area.

Why does parking need to be improved?

Parking is a key part of business infrastructure, especially in places like business parks, transport hubs and shopping centres.

Circling for parking is responsible for approximately 30% of urban traffic congestion, a huge contributor to CO2 emissions.

The benefits of utilising computer vision for parking

Computer vision does more than simply speed up the time it takes to find a parking space for the user. For businesses and urban planner, here are some of the benefits:

  • Enables predictive maintenance for charging points - Computer vision continuously analyses visual data from cameras or sensors to detect early signs of wear, damage, or potential malfunctions. This proactive approach allows for timely intervention, reducing downtime and ensuring the reliability of charging infrastructure for electric vehicles.
  • Heightens security - Computer vision can easily provide secure access control with automated entry authorisation and efficient monitoring of vehicles within a parking facility.
  • Access important data insights without second guessing - Understand key trends, duration, peak usage times, analytics on charging points, the demographics of visitors, and more. This information tells you what drivers need from your parking facility. For example, an increase in EV charging point usage shows you that more people in the local area have opted for an electric vehicle and therefore perhaps another charging point is now necessary. Maintain visibility into how this data changes and feed this information into your strategy to improve resource allocation and enhance overall efficiency.
  • Increase revenue - Utilising computer vision in parking enhances opportunities for revenue generation by allowing parking facility managers to optimise space utilisation and minimise expenses tied to manual monitoring and upkeep, leading to increased operational efficiency and financial gains. If drivers know for sure they’ll get a space, they’ll choose your parking facility over another one.
  • No need for additional hardware costs - By connecting the footage from your existing CCTV camera to a video analytics platform, your cameras double up as sensors. Opting for a video analytics tool that uses computer vision technology gives you fast access to valuable data.

What industries could use computer vision for parking?

Commercial and corporate offices

Office complexes can implement smart parking solutions to optimise employee parking, track usage, streamline access, and enhance the overall workplace experience by making it easier to enter and leave.

Entertainment venues

Theme parks, stadiums, and concert venues can benefit from improved traffic management, reduced wait times, and enhanced security in parking areas. If the parking is expected to be full, drivers can know before chancing their arm and potentially being late for the event.


Computer vision for parking can streamline airport parking operations, providing travellers with real-time information and optimising parking resource utilisation.


Hospitals and healthcare facilities can use computer vision for parking to ensure smooth traffic flow, efficient patient drop-offs, and enhanced security in parking areas.


Retailers can improve customer experiences by providing real-time parking information, reducing search times, and optimising traffic flow in parking lots.


Universities and schools can enhance campus parking management, reduce congestion, and improve the overall commuting experience for students, staff, and visitors.

Business parks

Business parks can identify underutilised space with smart parking sensors, which could then be repurposed.

What can computer vision for parking achieve?

Fyma connects computer vision to parking to reduce congestion and gather vital analytics about parking trends. This can result in a 30% reduction in the time it takes to park, boosting the visitor experience.

Fyma in action

ParkPlaza used the Fyma platform to drive revenue from their parking and improve each driver’s experience. They benefited from accessing all the key analytics from one place and the result they achieved was an 18% boost in space utilisation and a 30% decrease in parking search times, resulting in savings of over $2 million in one year. This shows us the capability of computer vision for parking – it’s a rewarding opportunity that shouldn't be missed by businesses.

Final thoughts

In conclusion, computer vision is an impactful technology that opens new avenues for businesses with parking facilities to enhance revenue, user experiences, and operational efficiency.

It's a core component of smart cities and demonstrates how technology can be used to improve our daily lives and enrich our communities. Those frustrations we face by the simple act of parking at our desired destination can be eradicated when we apply computer vision technology, and for businesses and urban planners, they can benefit from digestible data that really makes a difference.

Don’t just take our word for it, try Fyma today to see how your parking facility can be improved.