Learned model generating method, learned model generating device, and learned model use device
Learned model providing system has a configuration including consent acquisition device that acquires use consent that an acquired image of visitor is to be used for generating a learned model from visitor, a plurality of cameras that image visitor, learned model generating device that generates the learned model by machine learning based on a captured image imaged by camera, server device that saves the learned model generated by learned model generating device, user side device that receives the learned model from server device, camera, and member database.
1. A method for generating a learned model by machine learning and to be performed using at least one processor based on sensing information acquired by sensing one or more sensing objects with one or more sensing devices, the method comprising:
by the processor,
acquiring, for at least one sensing object of the one or more sensing objects, use consent indicating consent for a use of the sensing information of the at least one sensing object for generating the learned model,
creating, in the sensing information of the one or more sensing objects, learning data by processing or deleting the sensing information of a sensing object of the one or more sensing objects other than the at least one sensing object for which the use consent is acquired, and
generating the learned model by machine learning using the learning data.
2. The method for generating a learned model of claim 1 ,
wherein an electronic signature is attached to the generated learned model, the electronic signature indicating that processing or deleting the sensing information is performed on the sensing object for which use consent is not acquired when creating the learning data for the generated learned model.
3. The method for generating a learned model of claim 2 ,
wherein when acquiring a notification that a verification result of the electronic signature given to the learned model is unverifiable from a learned model use device receiving the learned model, the processor performs invalidation processing on the learned model.
4. The method for generating a learned model of claim 1 ,
wherein the one or more sensing objects comprise one or more persons and the sensing information comprises one or more face images of the one or more persons, and
wherein when creating the learning data,
in order to specify a non-consent face image of a person for which the use consent is not acquired, the processor acquires a consent face image of a person for which the use consent is acquired.
5. The method for generating a learned model of claim 4 ,
wherein the consent face image is acquired by imaging a face of the person for which the use consent is acquired.
6. The method for generating a learned model of claim 4 ,
wherein the consent face image is a face image of a person whose face image is stored in a portable terminal in advance acquired from the portable terminal possessed by the person for which the use consent is acquired through near field communication.
7. The method for generating a learned model of claim 4 ,
wherein a unique identifier is given in advance to the person for which the use consent is acquired and the consent face image of the person is associated with the identifier and registered in a member database in advance, and
wherein the consent face image is acquired by searching the member database based on the identifier given to the person for which the use consent is acquired.
8. The method for generating a learned model of claim 1 ,
wherein when acquiring a notification that the learned model is used from a learned model use device receiving the learned model, the processor gives a compensation value to an entity that provided the sensing information of the at least one sensing object for which the use consent is acquired or a business operator involved in generating the learned model.
9. The method for generating a learned model of claim 8 ,
wherein the processor gives a unique identifier to the at least one sensing object for which the use consent is acquired, associates the identifier with the learned model generated by machine learning based on the sensing information of the at least one sensing object for which the use consent is acquired, and registers the identifier to a compensation database, and
wherein when acquiring a notification that the learned model is used from a learned model use device receiving the learned model, the processor searches the compensation database based on the identifier associated with the learned model to obtain the at least one sensing object for which the use consent is acquired when generating the learned model.
10. A learned model generating device that generates a learned model by machine learning based on sensing information obtained by sensing one or more sensing objects with one or more sensing devices, the learned model generating device comprising:
a communicator that performs communication between at least one processor and the one or more sensing devices,
wherein the at least one processor
acquires, for at least one sensing object of the one or more sensing objects, use consent indicating consent for a use of the sensing information of the at least one sensing object for generating the learned model, and
creates, in the sensing information of the one or more sensing objects, learning data by processing or deleting the sensing information of a sensing object of the one or more sensing objects other than the at least one sensing object for which the use consent is acquired.
11. A learned model generating device that generates a learned model by machine learning based on sensing information obtained by sensing one or more sensing objects with one or more sensing devices, wherein use consent is acquired from at least one sensing object of the one or more sensing objects, the use consent indicating consent for a use of the sensing information of the at least one sensing object for generating the learned model,
the learned model generating device comprising:
a communicator that performs communication between at least one processor and the one or more sensing devices,
wherein the at least one processor
generates the learned model by machine learning using learning data created by processing or deleting the sensing information of a sensing object of the one or more sensing objects other than the at least one sensing object from which use consent for generating of the learned model is acquired.
12. The learned model generating device of claim 11 ,
wherein an electronic signature is attached to the generated learned model, the electronic signature indicating that processing or deleting the sensing information is performed on the sensing object from which use consent is not acquired when creating the learning data for the generated learned model.
13. A learned model use device that uses the learned model provided from the learned model generating device of claim 12 , the learned model use device comprising:
at least one processor
verifies the electronic signature given to the learned model, and
in a case where a verification result of the electronic signature is acceptable, configures an analysis engine using the learned model to execute analysis processing.