Rapid growth in the Internet of Things (IoT), digitization, analytics, and big data has dramatically changed the operations and strategies in the development of the future of transportation. Improper traffic management systems have resulted in rising congestion and accidents across urban locations. The emergence of smart solutions like video analytics software is assisting cities, pedestrians, and transit agencies to address these growing concerns.
Traffic analytics plays a critical role in analyzing the insights into daily traffic activities that can help in curbing congestion by optimizing routes. ARC recently published a worldwide research on Smart Traffic Management Systems and the industry is poised for a solid growth in next 5-years.
Connecting Traffic Management System (signals and Command centers) with a GIS-enabled digital road map of the city is a key to smooth traffic management. Analytics software get data from the Traffic Management System or edge enabled cameras, connecting it in real-time with GIS mapping and parking management data provides information to the driver, thus help reducing congestion. Also, information from these systems can be projected in real-time on digital screens installed on the freeways on local streets, guiding drivers to available parking slots and streets. This not only helps reduce congestion but also saves time and fuel, thus reducing emission levels and making the environment cleaner and better to live.
Video analytics software can be pre-installed on the central server at the central monitoring station, or it can be built into the edge directly into the cameras that capture real-time images and video of the road, or the combination of both. This software operates on the concept of moving objects (vehicles or pedestrians) and pattern recognition and generation. In the case of moving objects, cameras identify the movement of cars or pedestrians in motion. It assists in detecting traffic violations, over speeding, signal jumping etc. While pattern recognition algorithm enables cameras to recognize the object within a frame. This helps in vehicle identification, pedestrian crossing etc. The data collected from these cameras is processed by analytics software to generate alerts and to enable route optimization.
Key functionalities of Video Analytics Software
Vehicle and Pedestrian Crossing: Software assist in differentiating between pedestrians and vehicles. It ensures pedestrian safety and in real-time counts the total number of vehicles and pedestrians on the road at a specific period of time. This data can be later leveraged for other smart city initiatives.
Vehicle classification: Video captured identifies the type of vehicle (Truck, Bus, Car, Bike etc.) that has passed from that road.
Automatic License Plate Number Recognition: This feature reads and records license plate data the in the database. It Is used for toll recognition, traffic control or to detect suspicious activities etc.
Incident detection: Video surveillance with analytics detects any unwanted incidents or accidents on the freeways or roads, which can be used as an evidence by police or insurance companies. It also detects if any vehicles are parked non-designated parking zones or detect vehicles driving in a wrong direction or wrong lanes.
Smart cities have been implementing innovative traffic management systems. However, it is the use of data from different sources in real-time and immediate data processing enables quick decision-making, which is the key to a successful traffic management in cities. It is of utmost importance to leverage a large amount of data to ensure a smart living experience.