Leveraging machine vision and artificial intelligence in assisting emergency agencies

1. A system, comprising:

an interface configured to receive a data description, wherein the data description comprises a missing person description, a stolen vehicle description, and/or an Amber alert; and

a processor configured to:

create a model-based item identification job based at least in part on the data description;

determine a subset of vehicle event recorder systems of a preexisting distributed set of vehicle event recorder systems to run the model-based data identification job, wherein the subset of vehicle event recorder systems is determined based at least in part on a combination of two or more of the following: vehicle event recorder system capabilities, vehicle routes, and other jobs assigned to the vehicle event recorder system;

provide the model-based item identification job to a set of vehicle event recorder systems, wherein the model-based item identification job uses a model to identify sensor data resembling the data description, wherein the model-based item identification job includes one or more of machine vision, artificial intelligence, machine learning, deep learning, and/or a neural network, wherein the model-based item identification job is trained on vehicle type data, and wherein the vehicle type data includes one or more of vehicle type, make type, model type, and/or color type;

receive the sensor data from the subset of vehicle event recorder systems; and

store the sensor data associated with the model-based item identification job.

2. The system of claim 1 , wherein the data description comprises one or more of: a vehicle make, a vehicle model, a vehicle color, a vehicle license plate number, a vehicle license plate state, a vehicle bumper sticker, vehicle dents and/or scratches, vehicle modifications, a person age, a person height, a person weight, a person gender, a traffic backup condition, or a traffic accident description.

3. The system of claim 1 , wherein the model-based item identification job is associated with a target area or a time window.

4. The system of claim 1 , wherein the vehicle event recorder system capabilities comprise system processor power, system available memory, system camera and/or other accessory hardware.

5. The system of claim 1 , wherein the vehicle routes comprise a location of a system route limited by a target area and/or a time window.

6. The system of claim 1 , wherein the processor is further configured to determine an item identification event.

7. The system of claim 6 , wherein determining the item identification event comprises verifying the sensor data resembles the data description.

8. The system of claim 6 , wherein determining the item identification event comprises determining a time and location associated with the sensor data.

9. The system of claim 6 , wherein determining the item identification event comprises providing video data associated with the sensor data for human review.

10. The system of claim 6 , wherein determining the item identification event comprises providing still image data associated with the sensor data for human review.

11. The system of claim 1 , wherein the data description is based at least in part on the Amber alert.

12. The system of claim 11 , wherein the Amber alert is received via an automated process from an emergency organization.

13. The system of claim 11 , wherein the data description is automatically generated based at least in part on the Amber alert.

14. The system of claim 11 , wherein a target area and/or a time boundary are generated based at least in part on the Amber alert.

15. A method, comprising:

receiving a data description, wherein the data description comprises a missing person description, a stolen vehicle description, and/or an Amber alert;

creating, using a processor, a model-based item identification job based at least in part on the data description;

determining a subset of vehicle event recorder systems of a preexisting distributed set of vehicle event recorder systems to run the model-based data identification job wherein the subset of vehicle event recorder systems is determined based at least in part on a combination of two or more of the following: vehicle event recorder system capabilities, vehicle routes, and other jobs assigned to the vehicle event recorder system;

providing the model-based item identification job to a set of vehicle event recorder systems, wherein the model-based item identification job uses a model to identify sensor data resembling the data description, wherein the model-based item identification job includes one or more of machine vision, artificial intelligence, machine learning, deep learning, and/or a neural network, wherein the model-based item identification job is trained on vehicle type data, and wherein the vehicle type data includes one or more of vehicle type, make type, model type, and/or color type;

receiving the sensor data from the subset of vehicle event recorder systems; and

storing the sensor data associated with the model-based item identification job.

16. A computer program product, the computer program product being embodied in a non-transitory computer readable storage medium and comprising computer instructions for:

receiving a data description, wherein the data description comprises a missing person description, a stolen vehicle description, and/or an Amber alert;

creating a model-based item identification job based at least in part on the data description;

determining a subset of vehicle event recorder systems of a preexisting distributed set of vehicle event recorder systems to run the model-based data identification job, wherein the subset of vehicle event recorder systems is determined based at least in part on a combination of two or more of the following: vehicle event recorder system capabilities, vehicle routes, and other jobs assigned to the vehicle event recorder system;

providing the model-based item identification job to a set of vehicle event recorder systems, wherein the model-based item identification job uses a model to identify sensor data resembling the data description, wherein the model-based item identification job includes one or more of machine vision, artificial intelligence, machine learning, deep learning, and/or a neural network, wherein the model-based item identification job is trained on vehicle type data, and wherein the vehicle type data includes one or more of vehicle type, make type, model type, and/or color type;

receiving the sensor data from the set subset of vehicle event recorder systems; and

storing the sensor data associated with the model-based item identification job.

17. The system of claim 1 , wherein the other jobs comprise a mission-critical job.

18. The system of claim 1 , wherein receiving the sensor data from the subset of vehicle event recorder systems comprises:

determining whether a match is found using the sensor data; and

in response to a determination that the match is found, notifying a data submitter of a positive match.