Product Description:
app2bee is a native android app. I developed this app in last working place at the University of Applied Science Stuttgart, Germany. It was a kind of research work. App2bee is basically an image recognition app. Users can take image of different flowers using this app and the app can recognize those flowers using the image recogntion algorithim which is running in a remote machine. The main workflow of is like this: user takes/uploads image → draws a line around the main part of the image → sends the image to the remote image recognition server → gets back a response as a list with recognition results → selects his/her desired flowers from the list → provides some metadata (e.g. amount of flower, place, area etc.) → sends metadata along with image to the remote database server → previews his/her data in Google map.

Key Features
1. The app can recognize 50 different types of flower
2. User has to login to access the full features of the app
3. When ever an existing user log in to a new device all his/her data is automatically synchronized into his/her phone
4. User can take new image or upload image from memory card for recognition
5. If user is out of internet connection, then he can take an image and save it after providing some meta data (e.g. amount of flower, place, area etc.). The the information will be stored in SQLite. Later on when user connects with internet he can recognize the image by sending it to our image recognition server. recognition task.
6. User can see only his/her data or even all other users' data in Google Map.
7. User can reqest for new flowers to be added into our app by send an email right from the app.
8. User can see all 50 flowers that app2bee can recognize in a grid view.

Technologies
The frontend, backend and database is completey designed and developed by me. I have used Android Studio, MySQL, SQLite, REST web services, SVN and Tomcat Server to develop this app. The image recognition service is written in python which has been developed by another person.

Team
There were total 7 members in the team. I was responsible to develop the android app and enhance the image recognition algorithm. Another person was responsible to develop REST werb services. There was an external person who looked after the server machine. There were 3 student assistants who were responsible to do manual test, to develop iOS version of the app and to do different reasearch work. Professor was the team leader of this project.

The app is not yet available in the play store.