Paper Info
Title
Smart Lifelogging: Recognizing Human Activities Using Phasor
Abstract
This paper introduces a new idea for sensor data analytics, named PHASOR, that can recognize and stream individual human activities online. The proposed sensor concept can be utilized to solve some emerging problems in smartcity domain such as health care, urban mobility, or security by creating a lifelog of human activities. PHASOR is created from three 'components': ID, model, and Sensor. The first component is to identify which sensor is used to monitor which object (e.g., group of users, individual users, type of smartphone). The second component decides suitable classifiers for human activities recognition. The last one includes two types: (1) physical sensors that utilize embedded sensors in smartphones to recognize human activities, (2) human factors that uses human interaction to personally increase the accuracy of the detection. The advantage of PHASOR is the error signal is inversely proportional to its lifetime, which is well-suited for lifelogging applications. The proposed concept is evaluated and compared to de-facto datasets as well as state-of-the-art of Human Activity Recognition (HAR) using smartphones, confirming that applying PHASOR can improves the accuracy of HAR.
Year
DOI
Venue
2017
10.5220/0006320907610768
ICPRAM: PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION APPLICATIONS AND METHODS
Keywords
Field
DocType
Lifelog, Human Activity Recognition, Smartphones, Embedded Sensors, Smart-City, Heterogeneous Sensory Data Analytics
Data mining,Lifelog,Activity recognition,Data analysis,Computer science,Phasor,Human interaction,Human–computer interaction,Phone,Error signal,Artificial intelligence,Machine learning
Conference
Citations 
PageRank 
References 
1
0.43
3
Authors
4
Name
Order
Citations
PageRank
Minh-son Dao19321.42
Duc-Tien Dang-Nguyen219029.44
Michael Riegler325150.56
Cathal Gurrin41031139.37