Putting MMR to practice

September 25, 2018

Asura MMR, the make and model recognition video analytics expansion of ARU is available since early September, so its time to look at some practical uses of this new, exciting technology.

Detailed vehicle information for ITS

Intelligent Transportation Systems rely on massive amount of data to analyse to make traffic predictions leading ultimately to increased road safety. These systems rely on statistics so its easy to understand that the more input data, the better the analysis and thereby the quality of the predictions. Many tools aim to provide relevant data, however visual data collection of traffic is usually narrowed down to license plate information, vehicle counting and some more redundant data. So unfortunately the data obtained this way will not be of too much use for the original purpose that is accident prediction and prevention. The good news is that make, model and the color information of the vehicles can extend these datasets contributing to safer road networks and smarter traffic coordination.

Fraud prevention for tolling operations

Make, model and category based vehicle recognition is a great add-on for tolling operations allowing more effective fraud detection. Manual checking and erroneous fines are responsible for a considerable portion of operation costs. LPR and MMR combined is arguably one of the best solutions for vehicle fingerprinting that enhances recognition accuracy. The possibilities offered by MMR+LPR compared to classical vehicle fingerprinting* considering road toll operations are similar, but much more effective. MMR&LPR information provide an instant fingerprint with maximal accuracy, identifying all known visual data about the vehicles allowing to register one car per license plate thereby aiding fraud prevention efforts with a close to 100% vehicle identification.

*vehicle fingerprinting

More details for customer profiling

Commercial application of the information obtained via MMR+LPR in parking operations will provide a significant amount of extra data to analyze. Identified customer patterns and the automatized parking process all contribute to further enhancing the customer experience. Let’s take a shopping mall, hotel, or restaurant. Knowing the brand of the vehicles will add a new perspective to analyze the target audience and ultimately help in serving them better. You as a service provider will draw valuable conclusions by analysing the data of vehicles of usual guests to help in determining whether your service is over- or underpriced.

Law enforcement – witnessing perfected

Perhaps one of the most implicit uses of LPR+MMR is aiding witnessing in law enforcement. Vehicle recognition is a great tool for identifying participants of a car accident or traffic offense even in case of incomplete witness testimonies or insufficient (license plate) information. Proper, automatized database management as in the case of ARU will also make it easy to track back events or security breaches by filtering them across multiple attributes like time, place, images or even vehicle specifics like brand or model.

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