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Detail
Conference Paper
HaaS(Human Activity Analytics as a Service) Using Sensor Data of Smart Devices
- Authors
- Eunjung Kwon, Hyunho Park, Sungwon Byon, Eui-Suk Jung, Yong-Tae Lee
- Issue Date
- 2018-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2018, pp.1500-1502
- Language
- English
- Type
- Conference Paper
- Project Code
- 18HR1800, Platform Development of Multi-log based Multi-Modal Data Convergence Analysis and Situational Response, Lee Yong Tae
- Abstract
- recognizing human activities with sensor data of smart device is challenging task due to issues, such as data privacy, lack of dataset size, and appropriate preprocessing techniques to eliminating noise of time-series data. In this paper, we present a human activity recognition analytical models using time-series formed sensor data of smart devices such as smartphone and wearable devices. In order to understand user's activities within an environment existing various devices, it needs to collect data generated in that specific environment and analyze it with guaranteeing high performance and accuracy for classifier.This paper makes two specific contributions: first, we present a novel system architecture for recognizing human activities. This architecture comprises of a data collection protocol, which carries sensor data of smartphones and wearable devices into a server platform; second, we show experiment results comparing with three kinds of analytical models and describe its meaning.
- KSP Keywords
- Analytical model, Data Collection, Experiment results, High performance, Human activity recognition(HAR), Preprocessing techniques, Smart devices, System architecture, Time series data, Wearable device, data privacy