To sum up, the implementation of EYEDENTIFY is fruitful. This project has successfully implemented a mobile application which concentrates on the needs of Dementia patients.
The implementation of face recognition and memoir functions has been done smoothly by using Face recognition (DLIB). In the face recognition functions, a real-time face recognition system is realized, the user identifies their family and friends. By using the Raspberry Pi with the camera module, the photo will pass the Face recognition (DLIB) program. After face detection and matching, the results will be shown in the application. Dementia users can remember the identity of the people they are meeting. In the memoir function, both dementia users and caretaker users can upload photos. After matching faces by Face recognition (DLIB), dementia users can see the photo with the name tag of their family and friends and share the same memories with them.
The implementation of the object recognition function has been completed with Tensorflow. A function like lost and found has been created for Dementia users to find their personal belongings e.g. glasses. As Dementia users lose their belonging, they can find the last seen photo of that belonging and locate it. The last seen photo was taken by Raspberry Pi and processed by Tensorflow. Since Dementia users can find their belongings by themselves, fewer controversies with family and friends will happen.
The implementation of the GPS sharing function has been accomplished favorably with Google Map API. Both Dementia users and Caretaker users can see each other’s last seen location which brings an equal relationship.
To ensure the application remains competitive and stands the test of time, further development should be done. Both hardware and software can be upgraded to provide a better service.
In hardware development, Raspberry Pi is the core hardware of the whole system. First, the physical size of Raspberry Pi should be reduced to increase portability. The Raspberry Pi must operate with a power bank now. Both items should be combined to reduce the volume. Second, the camera in Raspberry Pi should be upgraded in order to increase the resolution of the photos. A higher resolution can increase the accuracy of the face and object recognition.
In software development, several developments should be completed in the future. First, the existing functions should be enhanced. For the object recognition functions, more items of target objects should be added. There are only four items that can be detected in the current function. Users should be able to add any belonging that they need to find to the function in the future. For the GPS sharing function, a direction feature should be built to show the fastest way to go to the current location of each user. Second, some new features should be created to boost the comprehensiveness of the mobile application. An instant messengers function can be added into the application to close the relationship as users can talk to each other at anytime and anywhere. A ‘GO-HOME’ function can be implemented into the application. As dementia patients will lose their way easily, a function shows the fastest way to go back home and notify their caretaker to ensure their safety.