For years, the digitization of urban parking has been closely linked to the installation of IoT sensors. These technologies have enabled cities around the world to begin to understand what is happening on their streets: occupancy, turnover or non-compliance, laying the foundations for a smart parking model.
However, as management needs evolve, especially in complex or high-density environments, so do the solutions. Today, the focus is not only on detecting vacancies, but also on improving analysis and response capabilities through more advanced technologies.
The evolution of smart parking with artificial vision and cameras
In this context, Urbiotica expanded its portfolio in 2021 by incorporating detection solutions based on cameras with artificial intelligence, with the aim of complementing its sensor technology and responding to new scenarios. This development reinforces the role of artificial vision in projects where coverage and scalability are decisive.
Since then, these solutions have been deployed in multiple projects and cities, consolidating themselves as an efficient alternative in those environments where coverage, cost or installation complexity make the use of cameras more appropriate.
In addition, the solution has evolved significantly over the years, incorporating improvements in accuracy, adaptability and management capabilities. This has allowed it to expand its use cases and consolidate its role in intelligent parking and parking AI projects.
Artificial intelligence and cameras in parking lots: more demanding management
Cities no longer just need to know whether a space is free or occupied. It is increasingly important to have reliable real-time information to act on turnover, non-compliance and efficient use of space.
The challenge now is to:
- Manage high-turnover areas, such as loading and unloading
- Monitoring unbounded spaces or spaces with complex geometries
- Optimize investment in large-scale projects
- Obtain richer data for parking usage analysis.
- Integrating all information into intelligent parking management platforms in the cloud
In many of these cases, the choice of technology depends on the type of environment and the objectives of the project. Not all areas require the same level of control or the same infrastructure.
In this sense, in certain scenarios, especially those with a high density of parking spaces or greater automation requirements, camera-based solutions with artificial intelligence are a particularly efficient fit. Artificial intelligence thus expands the possibilities of intelligent parking.
U-Spot VISIO
Different environments, different needs
Not all intelligent parking projects respond to the same logic. Each environment has different needs and requires a different balance between coverage, control, cost and speed of deployment.
In the urban environment, cities need tools to manage public space efficiently, especially in critical areas such as loading and unloading. In this context, urban mobility requires solutions capable of acting with precision and in real time.
On the other hand, in off-street environments, such as supermarkets or shopping malls, the main objective is to maximize the availability of parking spaces and improve the user experience. Here, artificial intelligence makes it possible to optimize parking usage.
In high-density parking environments, where a single camera can cover several dozen parking spaces, machine vision-based solutions are particularly competitive in terms of cost. This capability makes cameras a very effective solution in high-density projects.
This makes it possible to tackle large-scale projects with lighter infrastructure and shorter deployment times, while maintaining a high level of control over the use of the parking lot.
Solution: Operational efficiency through machine vision
Camera and artificial intelligence-based solutions are already part of numerous smart parking projects in operation, especially in environments where operational efficiency and scalability are key.
Detection of parking spaces with cameras and artificial intelligence
In this context, solutions such as U-Spot VISIO make it possible to detect the occupancy of multiple parking spaces by analyzing images, without the need to act on each of them. This approach reduces the complexity of deployment and reinforces the potential of parking AI.
It is a consolidated solution, deployed in several real projects, which has proven its ability to adapt to different environments and provide reliable information on parking usage. The combination of cameras, software and artificial intelligence facilitates more accurate parking management.
- Optimization of investment per monitored seat
- Coverage of multiple seats with a single infrastructure
- High accuracy in rotation detection and analysis
- Detailed information in real time
- GDPR compliance
- Integration with existing platforms
Moreover, since it is a solution based on artificial intelligence in the cloud, it can evolve without intervening in the infrastructure. This reinforces the value of artificial vision applied to scalable projects.
Real projects: two environments, one goal
Street management: L’Hospitalet de Llobregat
In L’Hospitalet, the challenge was to improve the management of loading and unloading zones, a key element for economic activity. In this context, machine vision can provide greater control over public space.
Urbiotica implemented one of the largest deployments of intelligent management through the installation of more than 400 cameras. This project demonstrates how artificial intelligence applied to parking lots can be applied in complex urban environments.
- Real-time monitoring
- Automatic detection of non-compliance
- Increased turnover
- Operational optimization through alerts
You can see more details in this case of intelligent management of loading and unloading zones in L’Hospitalet de Llobregat.
Off-street environment: Lidl
In the case of Lidl, the objective was to optimize parking usage in supermarkets with high turnover. Here, camera-based technology enables improved availability and user experience.
Lidl has digitized its parking lot using cameras connected to the U-Admin platform to detect parking spaces in real time. This case shows how machine vision also brings value in commercial environments.
- Real-time occupancy
- Increased availability of seats
- Reduction of search time
- Operational optimization
You can find more information in this case of smart parking in supermarkets.
An evolution that is already a reality
The incorporation of camera-based solutions is marking a turning point in intelligent parking. More and more projects are integrating machine vision to respond more accurately to real needs.
Especially in environments where cost optimization and speed of deployment are key, artificial intelligence applied to parking is consolidating as a strategic option. Urbiotica currently monitors nearly 3,000 parking spaces using cameras.
This growth reflects a technological evolution and a greater capacity to adapt to different environments. Adaptability is key in this type of solution. In practice, many projects are evolving towards hybrid models where sensors and cameras are combined. All integrated into a single platform for unified, flexible and results-oriented management within the intelligent management ecosystem.
Product Manager at Urbiotica
Leads the definition and evolution of Urbiotica’s product solutions, ensuring that technological innovation translates into real value propositions for the market. Actively participates in the development and implementation of projects, providing a technical and strategic perspective that guarantees the reliability and impact of each solution in both urban and private environments. His work contributes to strengthening Urbiotica’s leadership in the field of smart parking and connected mobility.
