Using Raspberry Pi we collected data from air sensors during the degradation of food quality over a period of time. Those data were evaluated with the help of TensorFlow and the model was converted to TensorFlow Lite and used inside the Raspberry for inference. To make it handy we paired the single board computer with a mobile device (android) to show final and readable information to people.
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💬 Assess food quality using Raspberry Pi and TensorFlow Lite for people with loss of smell”
With the help of a Raspberry Pi we collected data from air sensors during the degradation of food quality over a period of time. Those data were evaluated with the help of TensorFlow and the model was converted to TensorFlow Lite and used inside the Raspberry for inference. To make it handy we paired the single board computer with a mobile device (android) to show final and readable information to people.
◾ Georgios Soloupis
I'am a Pharmacist turned Android developer engineer and ML GDE with a demonstrated history of working in the program development industry the past 7 years.
◾ Konstantinos Michelis
Freelancer Android Developer - Full-time engineer at Hellenic Air Force but working part-time on personal projects in Android since 2016.
Github | LinkedIn
◾ Akis Vlissidis
IT Applications Manager/Folli Follie Group
Thursday, June 23, 2022
4:00 PM – 5:00 PM (UTC)
| 4:00 PM | Welcome |
| 4:10 PM | Presentation |
| 5:00 PM | Closing & Networking |
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