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Welcome to the StrawberryFields wiki!
We will assume for simplicity that we have:
- one hectare field, 100 m x 100 m.
- There are 100 lines, length of 100 m.
Coordinates for the weather information are
- 64°17'12.0"N 27°37'19.7"E
- 64.286670, 27.622125
Data analytics related to strawberry growing. We get actual weather data, crops potential and amount of picked berries per day.
Prediction analytics software: predict amount of strawberries to be picked following few days. Crops available for different purposes are dependent on many things. We will consider following: Weather data, daily minimum and maximum values from which we calculate thermal sum from.
- rule of thumb: there is a correlation between total crops for row per day and thermal sum.
- winter conditions: hard winter meaning less crops following summer. Daily picking volume: how much is picked and from which rows.
- reduces volume for next days.
- rule of thumb, row must rest 3 days before picked again.
- if picked more from row that is actual prediction, that might mean that less to pick later. Age of the row
- 1- year old row produces nothing. 2 years old produce lot less crops than 3 years old row.
Spoiling crops alert analytics: next continuous 4 days rain will spoil the crops if, if crops ready when rain starts. mark the lines that need to be picked on rain start day. Lines that have rested 2 or more days need to be picked.
When customer reserves picking time, we need to know if there is crops available. we can suggest to customer possible picking times to reserve from. we see parking space availability. We can show to customer where to pick from. We can record picked harvest when customer comes to pay for us. we can see picking report.
Customer data must be anonyme. Technical specifications
Student groups or pairs or individual students doing development with some elementary courses related to programming.
Making software possible to implement: more detailed features
Test data generation (all these to folder \testDataGeneration)
- weather data generation. Group 1 responsibility
- crops data generation group 3 responsibility
- picking volume generation Group 2 responsibility
- Parameters for test programs using json
Per per day crops prediction (all these to folder \perDayCropsPrediction).
- calculate total crops potential / lines.
- Predicting given days crops: use the curve.
- predicting given days crops by calculating how much of the given day has been sold already.
- Predicting next picking day for a line
Data inflow (all these to folder \dataInflow)
- Customers reservation data group 4 responsibility
- past harvesting data per row group 5 responsibility
- knowledge on partial harvesting, only part of row picked.
- weatherdata
- Prediction data from FMI, group 2 responsibility (2nd grade level)
- Actualized weatherdata from FMI, group 3 responsibility (2nd grade level)
- Possibility to upload strawberry crop data of last season and get back estimation formula for next year.
Farming automation ( many possibilities for data analytics, all these to folder \farmingOperations)
- Irrigation volume prediction (volume depends on weather information, wind, heat, sunshine...)
- Fertilization with irrigation (the concentration depends on irrigation volume)
- Plant protection (depends on pest, disease, weather actual, weather predicted, crops season start, observations)
unit tests in folder (\unittests)
Sprint starting 8.4 ending 14.8.
finalizing following
weather data generation group 1
crops data generation group 3
this scrum taks.
Actualized weatherdata from SOME weather provider, group 3 responsibility
group 1 (Tan, David, individual tasks from this area) responsibility for 2'nd grade level: parameters for relevant scrum 1 parts of the project. json file, with jaql query language.
group 4 Hien prediction data openweathermap city wise predictions. saving to database.