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Product Vision Statement » Historie » Revize 5

Revize 4 (Roman Kalivoda, 2021-03-30 08:45) → Revize 5/74 (Roman Kalivoda, 2021-03-30 11:15)

h1. Product Vision Statement (WIP) 

 h2. Project Goals 

 Creating an application that will will, based on weather input, predict the attendance in class. User will be able to input their own weather information information, or choose a prediction based on current weather information or prediction for future days.  

 h3. System parts & technologies 

 h4. Server (backend) part 

 There will be a server application which: 
 * will retrain prediction model when new data are available (or a new model is defined by admin), 
 * will run predictions based on client app requests and send the response once it is ready. 

 We decided that the backend will be developed in C# and .NET platform. 

 h4. Web frontend app 

 There will be a WebGL application: 
 * user will be able to specify arbitrary weather conditions (e.g. temperature, precipitation) or use an automatic weather forecast, 
 * user will be able to specify an arbitrary classroom at UWB, 
 * these input data will be made into a web request and sent to the server, 
 * The prediction result will be shown to the user when the response is received. 

 The app will be written in C# and Unity framework. 

 h4. Android app 

 There might be an android app with functionality similar to the web frontend. The app will also be developed with C# and Unity. 

 h3. Happy Day use-case 

 The user will specify a date and classroom (e.g. UC-336) for which they wish to get the prediction of attendance. It will be possible to choose to have the weather forecast data for the given day downloaded automatically or input manually. The output of the app will be a text field saying how high the attendance the model predicts (e.g. very high). 

 h2. Project Plan 


 h2. Stakeholders 

 * Development Team 
 * Project Sponsor 
 * Project Mentor 
 * Users: lecturers 
 * Users: students 

 h2. Risks 

 h3. Available data are too crude 

 Chances are that the data are not specific enough to make proper predictions for single classrooms. Hopefully, the model could be improved gradually when there is more data available. In the meantime, we could modify the app to show just the prediction for a whole building. 

 h3. Our effort estimation is grossly underestimated 

 We should define/negotiate a minimum viable product and prioritize individual features. 

 h3. We proposed an unsuitable technological stack 

 _(TBD)_