This is sprint 6 in our project, and this week we our sprint goal is apply AI model to our appication.
Topic:
- Deploying AI Model To Our Project
- Setup Hardware Data API
Progress:
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Scrum Master
This is the sprint before the first release sprint, so some of our teammate actually have a bit pressure about the progress about it, but fortunately we had a break during the Chrismas and we have a good time on it. During the Chrismas break we had stop our development task and doing some research during which relate to the issue we met before the break.
The main task I done in this sprint is keep communicate with Lee and Illya about the format for AI model data and also how the project architecture will be working at that part.
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Backend Developer
After the testing before the Chrismas we know that the hardware data is able to sent in to the backendserver. So at this sprint I communicate with Zeyan and confirm the data format also setup the API that letting the frontend connect to.
For the issue last sprint about GDAL library , I decide to giveup using the gis system provide by it and directly use the function to calculate the distance to filter it ourself instead of using django build-in function.
And also for this week I work with Illya to help him deploy his AI regconition server to AWS.
Beside that I also build up the Login & Register Authetication System that let client able to validate the account and login.
Issues:
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Backend Developer
The issue is we didn't expect the AI model will consume a very large amount of storage when it trying to process the image, so after we deploy it to our free tier amazon server, it actually overloading our server and make our server down and unusable.