|
Test Case Title |
TC7.9 - CreateHourlyAvgTrendPerDay.R |
|
Goal |
TBD |
|
Prerequisites |
Using a PC with a web browser. You need credentials to access to the Node-Red application. The following functionalities are available only for specific Snap4city users with specific privileges. |
|
Expected successful result |
TBD |
|
Steps |
|
It’s possible to compute the hourly average trend per day of the week, starting from the current date and time, for a chosen period in days, using the function “hourlyAverageTrend”.
Function Parameters:
- city (It's possible to choose a city among Helsinki, Antwerp, Florence)
- sensorCategory (For each city is possible to choose the category of sensors)
- days (It's possible to choose the period in days. For example, days=30)
If the chosen city is "Helsinki", it’s possible to select a sensorCategory between "Noise_level_sensor" and "Weather_sensor". For each category, all numeric measures are considered.
If the chosen city is "Antwerp", the only sensorCategory to select is "Weather_sensor" and all numeric measures are considered.
If the chosen city is "Florence", it’s possible to select a sensorCategory between "CarPark" (that includes 13 of the main car parks in Florence/trend of the free parking lots), "Road Sensors" (that includes 18 sample road sensors/all measures trend), "Weather_Sensors" (that includes a single sample sensor "SensoreViaBolognese"/all measures trend). For each category, all numeric measures are considered.
The last saved trend can be get using the GetLastSavedValues.R script, using the function "GetLastSavedValues" and the function parameter city, and sensorCategory.
Example: GetLastSavedValues (“Helsinki”, “Noise_level_sensor”)
get: GetLastSavedValues.R https://www.snap4city.org/download/video/GetLastSavedValues.R
get: CreateHourlyAvgTrendPerDay.R https://www.snap4city.org/download/video/CreateHourlyAvgTrendPerDay.R
