Abstract
This paper presents a work on human activity recognition (HAR) using motion sensors embedded in a smart phone in building environments. Our HAR system recognizes general human activities including walking, going-upstairs, going-downstairs, running, and motionless, using statistical and orientation features from signals of motion sensors and a hierarchical Support Vector Machine classifier. Upon activity recognition, our system also generates energy expenditures of the recognized physical activities: energy expenditures are computed based on Metabolic Equivalents (METS) values, step count, distance, speed, and duration of activities. By testing our system in building environments, we have obtained an average recognition rate of 98.26% with physically consumed energy information. With the presented system, different building designs and environments can be evaluated in terms of energy consumptions of residents for their physical activities.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
