Using edge computing technology can improve traffic safety in real-time as it enables faster decision making.
FREMONT, CA: Taking one-way streets makes the travel longer and has the potential for driving with excess speed. To avoid a more extended trip, the public does not prefer one-way streets and takes a shorter route without considering the impending danger. However, the internet of things (IoT) based sensing system can be utilized to determine the traffic patterns and measure the number of cars driving the wrong way. The results were astonishing when it discovered a count that no one expected. This data can help improving traffic safety and outcomes for drivers and pedestrians. Eventually installing new signage can help to reduce the count but not eliminate it. In order to improve traffic safety and to address the challenges mentioned above, Las Vegas is using the sensor-based system on its streets.
The city uses new infrared cameras and LIDAR-based sensors to track movements down the street without identifying the individual who is driving or walking or pedaling. If the accident count is predicted, then measures to boost safety can be taken. NTT Sensors, using LIDAR, a laser-based system not only detects collision but also near misses by measuring distance and is often used in autonomous vehicle tests. A contradictory study revealed that when accidents took place in a one-way street, many drivers were driving in the wrong way. Using edge analytics tool is a suitable means to monitor one-way traffic.
The NTT sensors use Dell’s edge computing software to compute the data at the network edge. It collects audio information to determine cars’ location and receives metadata from the sensors and stores it in a central database. When other systems take time to send the data back to the core, analyze it, again sending back, edge computing allows faster decision making and improves traffic safety in real-time.
Edge computing is suitable for autonomous vehicles. With edge computing technology, data can be transmitted to the autonomous vehicle so that the vehicle is provided with the information before it gets to the intersection.