Mobile Application for Neural Network Analysis of Human Functional State
With the development of biometrics in general, the use of biometric face recognition technologies will gradually penetrate into the field of retail payments and other areas of the mass market, and will become widespread in the trade sector and in transport. Moreover, it is obvious that in retail, progress will not stop with simple recognition of the customer's face. The next step is emotion recognition. This technology is already working and is used, in particular, in the automotive industry. So, modern video surveillance systems with integrated analytics of emotions can determine that a person is falling asleep while driving or that he is aggressive, and the on-board computer intervenes accordingly in driving a car - wakes the person up or blocks control. The relevance of the topic of this article is due to the lack of a publicly available module for quickly detecting faces and eyes in high-resolution videos. In this work the client-server application to determine the functional state of a person is developed. Due to the development of technology, nowadays we can easily take high-resolution photos with our smartphones and use most of the gadget's sensors. Eye photos and light sensor measurements are sent from the client to the server, which uses a neural network to determine the functional state of the object under examination. During the software testing process the program have not produced erroneous results.
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