Enhancing context awareness with activity recognition and radio fingerprinting

Within context-aware computing, there is a growing interest in linking localization technologies with activity recognition in a cooperative way. Existing research works in this field face two main difficulties: lack of accuracy in their solutions and/or sophisticated hardware requirements. To avoid these issues, we present a light-weight, low-cost and high-accuracy system for localization and activity recognition, based on a smart phone and a single off-the-shelf wireless accelerometer attached to the waist. We process the accelerometer signal with the wavelet transform to precisely recognize different activities and obtain the velocity of the gait in real time. Additionally, we leverage the capabilities of the smart phone to accurately estimate locations making use of a multimode approach for radio fingerprinting. Eventually, we combine location information with activity recognition, observing a 9% improvement in the accuracy with which some activities are recognized.