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

maalvarez@us.es)

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:

  1. 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

BarometerBarometer-Left side hipPerson movesAltitudeEmbedded

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