Basket based sorting method for activity recognition in smart environments
- Resource Type
- Conference
- Authors
- Zhong, Zhenzhe; Fan, Zhong; Cao, Fengming
- Source
- 2018 IEEE 4th World Forum on Internet of Things (WF-IoT) Internet of Things (WF-IoT), 2018 IEEE 4th World Forum on. :161-166 Feb, 2018
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Engineering Profession
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Transportation
Sorting
Correlation
Activity recognition
Training data
Floors
Smart homes
Hidden Markov models
- Language
Activity recognition in smart environments is an important technology for assisted living and e-health. Recently there are growing interests in applying machine learning algorithms to activity recognition tasks. One of the main problems with previous work is that concurrent activities of multiple targets may fail the sensor event based prediction if no proper preprocessing method is used. To address this problem, this paper proposes a new basket based sorting method for multiple target classification in a sensor based smart environment, which can significantly improve activity recognition accuracy in real-time monitoring. The proposed structure and method can be plugged into different machine learning models to achieve good activity recognition performance.