Multi-tiered transportation identification system
A system for identifying an aspect of interest on a vehicle that includes a local AI system that can analyze sensor data from an on-site sensor to make an attempt to identify the aspect of interest according to first criterion. The aspect of interest can be information printed on the vehicle and/or on a seal of the vehicle. If the local AI system is unable to identify and validate the information on the first effort, it can consult with a central/global AI system that can leverage its own database and other local systems at other locations for subsequent attempts at identifying and validating the aspects of interest.
1. A method of training a networked system to identify an aspect of a target, comprising:
using a first sensor to derive first sensor data from an environment having the target;
using a local AI system executed by at least one processor to analyze the first sensor data to make a first effort to identify the aspect of the target;
determining whether the first effort satisfies a first criterion; and
in the event that the first effort fails to satisfy the first criterion:
providing at least some of the first sensor data as an input to a global AI system; and
using the global AI system executed by at least one second processor to make a second effort to identify the aspect of the target using at least one of the first criterion or a second criterion;
in the event that the second effort fails to satisfy the at least one of the first criterion or the second criterion, utilizing the global AI system to instruct a second sensor to provide second sensor data with respect to the target, wherein the step of utilizing the global AI system to instruct the second sensor comprises instructing an actuator system to direct a movement of the second sensor; and
using the global AI system to make a third effort to identify the aspect of the target.
2. The method of claim 1 , wherein the actuator system comprises a flying drone.
3. The method of claim 1 , wherein the second sensor comprises a camera coupled to a flying drone.
4. The method of claim 1 , further comprising: in the event that the second effort satisfies the second criterion, providing information to the local AI system to assist the local AI system in a future identification of the aspect of the target.
5. The method of claim 1 , wherein the target is a seal, and the aspect is a sequence of digits displayed on the seal.
6. The method of claim 1 , wherein the target comprises a seal affixed to a motor vehicle.
7. The method of claim 6 , wherein the motor vehicle is moving while the local AI system is making the first effort to identify the aspect of the target.
8. The method of claim 1 , wherein at least one of the first and second criterion comprises a reliability criterion.
9. The method of claim 1 , wherein at least one of the first and second criterion comprises an accuracy criterion.
10. The method of claim 1 , wherein the environment at least partially obscures the target.