OMNIQ Deploys AI-Based SeeDOT Systems for Vehicle Monitoring in Southern U.S. State

OMNIQ Corp. (“OMNIQ” or “the Company”), a provider of Supply Chain and Artificial Intelligence (AI)-based solutions, today announced that its image-processing division HTS has begun deploying SeeDOT™️ systems, OMNIQ’s solution for automating vehicle monitoring at weigh and safety stations, for an order received from a Southern U.S. state. 

The SeeDOT™️ systems, which will replace old equipment, are powered by OMNIQ’s proprietary AI-based, deep-learning neural network algorithm (“SeeNN™️”). Three of 14 SeeDOT™️ systems comprising the order have now been successfully completed, with the installation of new sensors, illumination units, and AI-based algorithm software.

OMNIQ’s SeeDOT™️ systems automatically monitor commercial motor vehicles (CMV) entering and exiting controlled areas, such as weigh-in-motion stations along highways, ports of entry and border crossings, secure parking facilities for trucking, and other sensitive installations. This cutting-edge solution provides an automated and accurate means to capture, collect, and read Department of Transportation (DOT) numbers on the cabs of CMVs for vehicle and owner identification, pre-screening, inspection, and enforcement/compliance monitoring. In addition to DOT numbers and images, SeeDOT™️ systems also capture license plate numbers and images, as well as overview images of the vehicles.

“As the need for accuracy and automation is growing, the installation of SeeDOT™️ systems at three weigh stations in the state has resulted in dramatically improved performance,” said Shai Lustgarten, President and CEO of OMNIQ. “Our SeeNN™️ neural network engine drives the efficient and accurate retrieval of relevant information from state and federal vehicle databases, allowing state agencies and enforcement officers to quickly access inspection and safety records, license compliance, HazMat registration, freight paperwork and overweight permits, among others. Importantly, the real-time identification of commercial vehicles allows state officers to focus their attention on high-risk vehicles, while allowing others to cross the station without the need to stop, enabling faster flow of traffic, reducing wait times, and improving productivity and safety.”

Using sensors, advanced video analytics, and OMNIQ’s SeeNN™️ neural network engine, SeeDOT™️ systems extract relevant data, which are then used to determine, based on a vehicle’s records and weight, if a vehicle is flagged for inspection by state highway officers or signaled to return to the highway after passing registration, inspection records, and compliance tests. This method replaces random checks by dispatching only high-risk vehicles to the checkpoint.

DOT numbers are printed in various sizes and qualities, creating major challenges to read the information under varying conditions during day and night. To overcome these challenges, advanced image processing techniques and specialized hardware are needed to provide high-quality readings in a great variety of formats and colors. OMNIQ’s SeeNN™️ engine has been tested on tens of thousands of truck images, validating its accuracy in reading license plate and DOT numbers. Sensors used in these systems are capable of handling CMVs traveling at up to 50 miles per hour without degradation in performance.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this news story?

Leave your feedback
Your comment type

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.