What is Computer Vision in Transportation?
Fleet management platforms enable companies to monitor and manage fleets of five or more vehicles while improving safety and reducing operating costs. Now, computer vision (CV) technology is being applied as part of advanced driver assistance systems (ADAS) to provide real-time alerting and analysis of data captured by dash cameras. It also creates actionable events as shown in the illustration below.
Figure 1: A Functional Overview of Computer Vision in Fleet Management
Fleet management uses a variety of components to implement safety and monitoring via CV:
Dash cameras: Continuously captures video of the inside and outside of the vehicle, however only video related to interesting events is stored to conserve space. Some events, like an impact, trigger CV techniques to extract information from the videos.
Advanced driver assistance systems: Helps drivers avoid accidents by providing audible and visual alerts to real-time events and uses image processing extensively.
Live streaming: Enables real-time monitoring by continuously streaming to the cloud, where techniques like sentiment analysis are used to annotate footage of interest and determine positive, negative, or neutral sentiment for each moment.
Actions: Responds to events like sudden braking by applying CV-powered video analysis to take appropriate action, for example making sure the driver is unharmed. Personnel monitoring the streaming video footage can telephone drivers to check on them. Video can also be used for more mundane maintenance, such as to determine if a vehicle needs cleaning, or if there is a cracked windshield.
Enabling CV-driven solutions are connected dash cameras that provide a 360-degree field of view both inside and outside the vehicle and can stream over radio-area networks (RAN) such as 4G LTE or 5G. Also required: vehicle access via API or specialized hardware plugged into an on-board diagnostics (OBD) port and able to communicate via a RAN.