Solutions based on Artificial Intelligence for Smart Cities

Thanks to the current technological developments, there's solutions for cities than recognize and analyze, using Artificial Intelligence, images captured by cameras. It's difficult to know everything that can be achieved with this technology because it's constantly changing. 

For this reason, we share below the main functionalities and applications of the latest Smart cities solutions from Neural Labs, company specialist in the sector with more than 20 years experience and headquarters in Barcelona (Spain).

APPLICATIONS OF NEURAL LABS SOLUTIONS FOR CITIES ACCORDING TO THEIR AREA

• Mobility:
  • Statistics and metrics for the mobility department.
• Traffic management:
  • Sanctions for traffic infractions proposals.
• Security:
  • Uninsured vehicles detection.
  • Stolen or searched by the police vehicles detection.
  • Vehicles with no technical inspection detection.
  • Vehicles in terrorist search detection.
  • Vehicles without license plate detection.
  • Forensic investigation.
  • Loitering detection.
  • Cloned/ illegal license plates detection.

DETECTED AND ANALYZED ACTORS

• Passenger cars.
• Motorcycles.
• Vans.
• Trucks.
• Buses.
• People.
• Scooters.
• Bicycles.
• Sea containers.

DETECTED VEHICLES ATTRIBUTES

• License plate.
• Vehicle type (Motorcycle, passenger car, van, truck, bus, etc.).
• Make.
• Color.
• Country.
• Speed.
• Lane.
• Traffic direction.

TRAFFIC INFRACTIONS DETECTED

• Vehicles running a red light.
• Vehicles that do not stop at the STOP sign.
• Wrong turn.
• Illegal Stop.
• Vehicles at a restricted area where they are not allowed (Low Emission Zones, pedestrian zones, city center…)
• Instant vehicle speed.
• Average vehicle speed (Section control).
• Wrong way.
• Blocked intersection.
• Lane changes.
• Dangerous overtaking.
• Opposing lane invasion.
• Pedestrians improper crossing.
• Ignoring Zebra crossings.
• Scooters at sidewalk.
• Bicycles outside their lane.
• More traffic infractions detection can be programmed.

DETECTED EVENTS (AUTOMATIC INCIDENT DETECTION)

• Pedestrians on the road.
• Animals on the road.
• Level of traffic (moving, heavy or stopped).
• Abnormally fast or slow vehicles
• Queue lengths (at tolls, traffic lights, etc.).
• Fallen or abandoned objects on the road.
• Area occupation (taxi stands, etc.).
• Before mentioned traffic infractions.
• More traffic events detection can be programmed.

COUNTING OPTIONS FOR MOBILITY DATA GATHERING

• Actor classification (person, motorcycle, passenger car, etc.).
• Camera or area.
• Timeframe (days, weeks, months, hours, or minutes).
• Concrete actions:
  • Vehicles circulating in each direction.
  • Vehicles turning to one side or the other in concrete spots.

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