AMEVA
University of Seville
Name of the competing system: Activity recognition system using non‐intrusive devices through a complementary technique based on discrete methods
Name and email of the responsible person: Miguel Ángel Álvarez de la Concepción
Date and place: 11/07/2013, Valencia, Spain
Data sources
For each datasource the following table is fulfilled:
Name | Acceleration |
Description of the information measured | Sensor acceleration provided by a triaxial accelerometer from a mobile phone |
Units | Acceleration (m/s2) |
Example values | 1.56, 9.8, 9.31 |
Frequency of generated data in operation | Acceleration 50ms |
Name | Barometer |
Description of the information measured | Barometer from a mobile phone |
Units | Altitude (m) |
Example values | 2.14, 1200.4, 5.81 |
Frequency of generated data in operation | Altitude is generated every 50ms. |
DataSets
After, for instance, 30 minutes operation the competitor generates the following data sets:
- An array of arrays that include: [activity, statistical values], every 3 sec.
Files:
- A file containing these samples in .xls format.
Devices used during benchmark
Device name | Type | Position in LLab (x,y,z) in meters | Position in user | Input | Output | Communication means to your system |
Acceleromter (Mobile phone with Android operative system) | Accelerometer | - | Left side hip | Person moves | Acceleration X,Y,Z[0G, 20G] | Embedded |
| Barometer | Barometer | - | Left side hip | Person moves | Altitude | Embedded |