Service execution based on Context 

Philo-CA Features

By predicting the user's desired services at certain situation with context awareness technology, the user's situation can be recognized more accurately, therefore it can pinpoint the exact timing for a certain service execution. It improves the context awareness as well as response timing, able to provide high quality services.


Philo-CA Structure


1. Sensor input data collection

Determining the types of sensors available on user's smart device and generating sensor information vectors by collecting the outputs of the sensors at specific time intervals or events.


2. Situation prediction

Predicts the probability of a certain situation among predetermined K number of situations from the time series of sensor information vectors.

3. Prediction of Service Execution point

Predict the probability that the user wants a specific service from the time series of the sensor information vector, and if the value exceeds a certain threshold, determines that the specific service is executed.

4. Service Execution Situation Table

Saves the number of times the service is provided in a specific situation as a table and uses it for future service inference.

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Philo-CA Uses

- Smart device context awareness-based application recommendation

- IFTTT services