Effector: Energy Efficient Mobility Classification and State Based Route Creation

Mobility analysis of users with or without location determination using accelerometer sensor embedded within the user smartphone is energy efficient and provides real-time contextual information. The accelerometer measurements for mobility analysis of human beings presents its own challenges as users carry their smartphones differently and these measurements are dependent on body placement of the mobile phones. On demand remote data exchange for analysis and processing of measurements plays a key role in mobility state analysis using accelerometer sensor which is less energy efficient has higher network costs and is not real time. This method presents an energy efficient novel framework capable of identifying mobility state of the user and creating route maps based upon a probabilistic algorithm that neutralizes the effect of different smartphone on body placements and orientations to allow human movements to be more accurately and energy efficiently identified. In addition it tracks the location of the user and creates routes based on the mobility states. The use of embedded smartphone accelerometer and GPS without need for referencing historical data and accelerometer noise filtering is capable of identifying human mobility states in real time with a time constraint of 2 seconds based on which user paths can be generated. The method achieves an overall average high classification accuracy and saves energy to a great extent when compared to exsisting GPS only usage for route creations.