Artificial intelligence (AI) is empowering Intelligent Transportation Systems (ITS), to streamline traffic and reduce congestion, enhance safety, and alert about traffic violations and dangerous situations. Applying AI models enables processing of captured images and videos of traffic in real-time and high accuracy, to detect and track vehicles, pedestrians, and other objects.
Cost and efficiency are pushing the required analytics capabilities to the edge of the network, creating demand for higher edge AI processing at lower power and cost. The Hailo processors enable running advanced AI models on the edge, supporting real-time alerts and decision-making, while improving privacy and security. The ability of smart transportation systems to cover a greater area in higher resolution with fewer cameras lowers infrastructure installation and maintenance costs and increases cost-efficiency.
LPR systems use cameras and image processing algorithms to detect the vehicle in the frame, identify its license plate, extract the alphanumeric characters, and compare them against a database for identification or verification purposes.
ITS applications, especially in highways, require high accuracy at high frame rates, to handle challenging conditions, such as high speed, multiple vehicles concurrently, low lighting, varying angles, or occlusions, and still need to accurately detect license plates for accurate billing or ticketing with minimum errors.
The high AI capacity of the Hailo processors enables more advanced LPR models which can adapt to different license plate designs, including various languages, fonts, colors, and background patterns, improving the accuracy and reduce the error rate.
Furthermore, the additional AI power can enable advanced capabilities in vehicle access control systems, such as model, make and color recognition (MMCR). This information can be used for further identification or verification purposes and to enforce safety and regulatory policies more effectively and with greater accuracy.
The Hailo AI processor enables traffic management systems to gain valuable insights for optimized mobility of people and vehicles in real-time. A Hailo-powered traffic management systems:
Traffic monitoring systems based on Hailo AI Processor perform real-time and high-performance AI video analytics at the edge from a single or multiple cameras. These systems deliver accurate insights and alerts at low latency at an embedded power budget. The Hailo AI processor small form-factor, low power, and cost-effectiveness capabilities make it ideal for integration in either the traffic cameras or the edge traffic management gateways
The Hailo processors make collection of tolls or fees in roads, bridges, tunnels, or other transportation infrastructure faster and more accurate.
With the advancement of technology, applications have evolved to incorporate electronic toll collection (ETC) systems, replacing traditional manual processing. AI improves the efficiency and effectiveness by automating processes, improving accuracy and security, enabling high detection rate with high accuracy even for multiple vehicles driving at high speed and in multiple lanes. AI also enables implementation of dynamic pricing models, personalization of user experiences, and facilitation of data-driven decision-making. Tolling systems based on the Hailo AI processors perform real-time high-performance AI video analytics at the edge from a single or multiple cameras delivering accurate insights and alerts at low latency at an embedded power budget. These advancements lead to more efficient toll collection, reduced congestion, improved traffic flow, and enhanced customer satisfaction.
AI can be used in various ways to enhance the effectiveness and efficiency of law enforcement agencies. With AI, law enforcement can automate repetitive tasks, enhance human decision-making, and provide advanced analytics for better crime prevention and investigation.
Intelligent video monitoring can be applied to:
To be able to detect vehicles and read license plates or see the seatbelt or phone inside their cabin in scenarios of congestion and/or where the vehicles are moving at high speeds requires real-time (or better) analytics that run on high-resolution video. The deployment may even require more than one camera and video stream. This is the type of deployment powerful, state-of-the-art edge AI processing is meant for.
Even parking lots are getting smarter these days.
As parking spaces get scarcer and cities get more congested, smart and efficient management of shared parking slots is becoming increasingly important. Through the integration of smart sensors, cameras, and machine learning models, parking lot operators can assist users in finding a parking spot more easily and quickly, while optimizing parking space allocation and maximizing revenues.
Real-time information on parking spot availability can be used to guide drivers to vacant spaces, reducing the time and effort required to find a free parking spot, while also reducing the congestion within the parking lot and at the entry / exit point.
The use of AI-powered License Plate Recognition (LPR) technology can be further leveraged to optimize parking utilization, by enabling automatic billing, monitoring parking time and space violations, reducing the time and effort required to enter and exit the parking lot and saving on operational costs.
