Three AI smart city trials start in Rome

Three AI smart city trials start in Rome

Technology News |
By Nick Flaherty

Three smart city trials with Envision are set to start in Rome, Italy, to cut transport pollution and accidents at pedestrian crossings.

The main aim of the trials is to evaluate and deliver a smart parking system using the IMX500 AI-enhanced image sensor from Sony to reduce pollution and gridlock from drivers looking for a parking space. Instead, drivers will be alerted via a smartphone app before being directed to the free parking space closest to their destination.

The trials also include a study of smart city systems that will optimise capacity and increase the use of its public transport network by implementing smart bus shelters, counting those getting on and off each bus to identify overloading and ensure better provisioning of buses and lower costs.

An alert system at pedestrian crossings will also be progressively activated to alert drivers when pedestrians are crossing, using low-latency smart lighting on the road to make them more visible with the aim of reducing the city’s accidents on pedestrian crossings.

The trials are set to start in June and alongside Sony and Envision includes the TTM Group (DP Control) which is responsible for installing the IMX500 image sensor in the camera units (above). European lighting and WiFi specialist Citelum is leading the project and responsible for the installation of the cameras on traffic lights, managing the maintenance service of traffic light systems and traffic regulation in the city.

Having the AI function embedded in the image sensor allows the city to reduce the bandwidth required, to scale it easily using existing networks, and to cut power and communication costs. It also allows citizens’ privacy concerns to be addressed. The configuration of the IMX500 in the trials allows the extraction of real time metadata related to information of a free parking space, the presence of a pedestrian about to cross a street, or the number of people getting on and off a bus. No images are stored, or leave the sensor, in line with privacy requirements.

“This is a clear and concrete example where Sony’s smart vision solution can serve our customer’s purpose while respecting people’s privacy,” said Antonio Avitabile, Managing Director of Corporate Alliance and Investment at Sony.

The average distance between pedestrians and vehicles is a key metric used to measure pedestrian safety. The trial is aiming to deliver a quantitative analysis of this and prevent pedestrian accidents through signalling mechanisms installed at the crossings.

Working with camera supplier Envision, the project trained a neural network to identify available parking spaces as well as the number of people waiting at the bus stops, entering / leaving the bus and waiting to cross or crossing the road.

Every camera has two sensors looking over the roads around and the parking spaces. The sensors send real-time data elaborated by neural networks on the exact location of a free space, the pedestrians’ presence and the number of people queuing at bus shelters.

The exact location of the free parking space data is streamed in real time through the smart tip. The data is then immediately processed by the sensor integrated in the smart tip, using neural networks, and the sent to Envision’s cloud software platform. The coordinates of the free parking space’s location are overlaid in real-time on a map that is displayed on a mobile device used by the driver who is heading towards the area.

Pedestrians’ presence is measured and compared across different locations. The neural network system detects pedestrians at the zebra crossing and a lighting signal is sent to the drivers to alert them.

Data of queue length and people getting on and off the bus are processed by the sensor in the smart tip through the neural network and sent to the Envision software platform which aggregates them and make them available to personnel managing the public bus network in order to enhance the planning and scheduling of the bus transportation network. A “crowded” figure of merit is provided to signal when the bus is running at over capacity to avoid overcrowded buses, better manage the transportation network and improve citizens’ journey experience.

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