A New Platform to Easily Experiment Activity Recognition Systems based on Passive RFID Tags : Experimentation with Data Mining Algorithms
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- 발행기관
- 보안공학연구지원센터(IJSH) 바로가기
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- 간행물
- International Journal of Smart Home 바로가기
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- 통권
- Vol.6 No.2 (2012.04)바로가기
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- 페이지
- pp.7-24
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- 저자
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- 언어
- 영어(ENG)
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- URL
- https://www.earticle.net/Article/A204534
※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.
원문정보
초록
- 영어
- Healthcare, due to the aging of western populations, requires new technologies to help assisting the needs of elders. The smart home paradigm is one of the promising new trends of research aiming to bring socially and economically viable solutions to this challenge. One of the most crucial problems in developing smart environment is activity recognition. It can be defined as the process of inferring, with various sensors, what the patient is doing and then, being able to predict what he might do in the future. We can find in the literature a lot of works on this theme, however the majority remain essentially theoretical. More specifically, they often work only on a particular component of the activity recognition process, for example by focusing only on the hardware (sensors) or solely on the high level recognition part, assuming that low level recognition already works. Furthermore, we noticed that most available recognition test platforms with an infrastructure, such as MavHome, are static and involve a complex set of sensors, which inevitably has a heavy cost. The work presented in this paper aims of providing solutions to these problems by proposing a way to implement from A to Z a complete recognition platform that works, is simple to use, inexpensive, sturdy and portable. This platform is based only on RFID tags and can be reuse everywhere to test various recognition algorithms, even directly at the patients’ home. We also present a first experimentation conducted with this platform using data mining recognition algorithms.
목차
Abstract
1. Introduction
2. Selecting and Modeling the Right Activities
3. Choosing the Right Set of Sensors
3.1. RFID Technology: Using Passive or Active Tags?
3.2. Which Sub-type of Passive Tags Should-we Use?
3.3. How to Attach Tags with Objects and How Many are Needed?
4. Activity Recognition based on RFID Tags
4.1. Hardware Setup
4.2. Platform Test Layout
4.3. Software Setup
4.4. Activity Recognition Using a Data Mining Approach
4.5. Activity Record
4.6. Base Frame Elaboration
4.7. Final Frame Creation
4.8. Temporal Aspect
4.9. Use of the C4.5 Algorithm on Data
5. Experiments
5.1. Used Learning Protocol
5.2. Test Protocol
5.3. Obtained Results
6. Conclusion and Perspective
Acknowledgement
References
키워드
Smart homes RFID experimental test platform recognition of activities of daily living (ADL) data mining recognition algorithm.저자
간행물 정보
발행기관
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- 발행기관명
- 보안공학연구지원센터(IJSH) [Science & Engineering Research Support Center, Republic of Korea(IJSH)]
- 설립연도
- 2006
- 분야
- 공학>컴퓨터학
- 소개
- 1. 보안공학에 대한 각종 조사 및 연구 2. 보안공학에 대한 응용기술 연구 및 발표 3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최 4. 보안공학 기술의 상호 협조 및 정보교환 5. 보안공학에 관한 표준화 사업 및 규격의 제정 6. 보안공학에 관한 산학연 협동의 증진 7. 국제적 학술 교류 및 기술 협력 8. 보안공학에 관한 논문지 발간 9. 기타 본 회 목적 달성에 필요한 사업
간행물
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- 간행물명
- International Journal of Smart Home
- 간기
- 격월간
- pISSN
- 1975-4094
- 수록기간
- 2008~2016
- 십진분류
- KDC 505 DDC 605
이 권호 내 다른 논문 / International Journal of Smart Home Vol.6 No.2
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