|
Action Logger Opensource Project
Motivation
- To recognize various human activities using multimodal sensors in a Smartphone for providing personalized services.
- To provide activity recognition core engine for developing smartphone applications utilizing activity information such as fitness, tracking or behavior monitor.
- To utilize the cutting edge technology for processing sensor raw data from accelerometer and GPS sensor.
Goals
- Our goal is to recognize 5 different activities which are stay, walking, jogging, taking a bus and subway using accelerometer and GPS sensors in Smartphone.
- Also provide 3 applications - Fitness Tracking, Human Black Box and Pedometer - based on action logger core engine.
Features
- Utilizing raw sensor data from accelerometer and GPS sensor in a Smartphone.
- Recognizing 5 different activities - Standing Still, Walking, Jogging, Talking a bus and Subway.
- Calculating consumed calorie of each activities using METs index.
- Providing activity recognition core engine as Java library for developing smartphone application utilizing human's activity information.
- 3 example applications using action logger core engine are provided.
- Novel feature extraction algorithms using SVM(Signal Vector Magnitude) and FFT are utilized for processing accelerometer data.
- Classification algorithm using GMM(Gaussian Mixture Model) is utilized for training and classification phase.
Uniqueness
- Action Logger utilizes only sensors embedded in a Smartphone - Acceleormeter and GPS.
- Collecting, Storing and Processing gathered sensor data are handled on Smartphone platform.
- Calculation of calorie consumption of each activities precisely.
- The core engine is released as open source for smartphone application developers.
|
