Product Vision Statement » Historie » Verze 7
Alex Konig, 2021-04-03 18:50
1 | 1 | Roman Kalivoda | h1. Product Vision Statement (WIP) |
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3 | h2. Project Goals |
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5 | 5 | Roman Kalivoda | Creating an application that will based on weather input, predict the attendance in class. User will be able to input their own weather information or choose a prediction based on current weather information or prediction for future days. |
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7 | 6 | Alex Konig | Can be useful for teachers when planning for activities that require higher attendance. For example if the teacher wants to give their students a pop quiz about their current knowledge from lectures, to get a better idea of the class' general understanding it would be good to have as many answers as possible. This app would enable to predict the attendance for a class, and therefore to decide if it is worth it to plan a 30min window in the lecture for a quiz or to rather plan something else. |
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9 | It could also be useful for students to decide how early to get to class to get the best seats. Many classrooms only have limited number of plugs, and sice a lot of students write notes in their notebooks the steats near these plugs are highly valuable. This app would enable the students to look how at how populated the building will be and decide if coming early to the lecture will be necessary to get those good seats. |
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11 | h3. User input |
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12 | 7 | Alex Konig | |
13 | 6 | Alex Konig | Time + building (can be specified as classroom number, however the computation will be done only on building level) |
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15 | h3. Output |
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16 | Based on building |
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19 | 5 | Roman Kalivoda | h3. System parts & technologies |
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21 | h4. Server (backend) part |
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23 | There will be a server application which: |
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24 | * will retrain prediction model when new data are available (or a new model is defined by admin), |
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25 | * will run predictions based on client app requests and send the response once it is ready. |
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27 | We decided that the backend will be developed in C# and .NET platform. |
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29 | h4. Web frontend app |
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31 | There will be a WebGL application: |
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32 | * user will be able to specify arbitrary weather conditions (e.g. temperature, precipitation) or use an automatic weather forecast, |
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33 | * user will be able to specify an arbitrary classroom at UWB, |
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34 | * these input data will be made into a web request and sent to the server, |
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35 | * The prediction result will be shown to the user when the response is received. |
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37 | The app will be written in C# and Unity framework. |
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39 | h4. Android app |
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41 | There might be an android app with functionality similar to the web frontend. The app will also be developed with C# and Unity. |
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42 | 1 | Roman Kalivoda | |
43 | 3 | Eliška Mourycová | h3. Happy Day use-case |
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45 | 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). |
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47 | 1 | Roman Kalivoda | h2. Project Plan |
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50 | h2. Stakeholders |
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52 | * Development Team |
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53 | * Project Sponsor |
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54 | * Project Mentor |
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55 | * Users: lecturers |
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56 | * Users: students |
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58 | h2. Risks |
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60 | h3. Available data are too crude |
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61 | 4 | Roman Kalivoda | |
62 | 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. |
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64 | h3. Our effort estimation is grossly underestimated |
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66 | We should define/negotiate a minimum viable product and prioritize individual features. |
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68 | h3. We proposed an unsuitable technological stack |
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70 | _(TBD)_ |