Saving doctors time by automatically identifying their patients with a face recognition and getting a quick analysis and overview of their current health condition.

What it does

We have applied the latest sensor and Industrial internet technologies for measuring and quickly analysing multiple human vital signs. In addition to industry and IoT, these technologies enable significant time saving and additional security benefits for medical professionals and health care providers. Our application also utilizes face recognition technology for identifying patients.

According to a recent Harvard Medical School study, average doctor visit (face to face time with a physician) in America last about 20 minutes. Another statistics show that there are 4 doctors visit per capita per year in America. By making patient identification and basic vital signs measurement more automatic and faster, it is possible achieve significant time and cost savings and also increased security by identifying patients automatically.

How we built it

This application was built in 24 hours at the Predix Transform hackathon. Our team included 5 persons (4 nationalities: USA, Finland, Turkey and Sweden) from 3 different companies, including GE Healthcare, Top Data Science and Sandvik Coromant.

The technologies we used to build this project, included:

Java Spring boot/API/websockets Predix seed Cordova mobile app Edison board and multiple sensor, including tempa Python image recognition algorithm for face recognition Primary Predix services: UAA Postgres Time series Asset

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