Combining multiple different data sets for more insights
Read more at
https://sensative.com/iot_use_cases/combining-multiple-different-data-sets-for-more-insights/
By combining multiple data sets from different sources, you can learn a lot, even if the data sets themselves are pretty small. This is something to consider when you plan to install IoT sensors.
In this case, from one of Sensative’s school projects, we combine five different sources to gain insights into how this classroom should be used. This would be difficult to understand if using, for instance, just a temperature sensor
Optimize usage of a classroom from an indoor climate and air quality point of view
Desk sensors:
The sensor solution located at each desk provides the following measurements.
- Relative Humidity: Units: %
- Temperature: Units: Celsius
- Light: Units: Lux
- Motion: Units: Number of motion counts
- Occupancy: Units: 0 = Unoccupied 1 = Pending (Entering or leaving) 2 = Occupied
CO2 sensor:
- Relative Humidity: Units: %
- Temperature: Units: Celsius
- Light: Units: Lux
- Motion: Units: Number of motion counts
- CO2: Units: ppm
Sound sensor:
- Relative Humidity: Units: %
- Temperature: Units: Celsius
- Light: Units: Lux
- Motion: Units: Number of motion counts
- Sound: Units: dB
- The temperature and humidity of the classroom build up during the week.
- The classroom needs the weekend to be unoccupied in order for the temperature and humidity to go back to normal levels.
- The facility can’t currently be used during the weekend without causing more build-up unless some changes are made to the ventilation system.
Municipality
Operations
Better Customer Experience, Better Quality, Smarter Product or Service
Experimenter
Discovery, Prediction, Optimization
Decision Tree, Machine Learning
Sensor Data