문화기술의 융합 (The Journal of the Convergence on Culture Technology)

  • 제9권6호
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  • Pages.1065-1071
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  • 2023
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  • 2384-0358(pISSN)
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  • 2384-0366(eISSN)
국제문화기술진흥원 (The International Promotion Agency of Culture Technology)
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다중센서를 활용한 LSTM 기반 재실자 행동 분류 모델 개발

Using multi-sensor for Development of Multiple Occupants' Activities Classification Model Based on LSTM

  • 박진수 (한국전자기술연구원 스마트가전혁신지원센터) ;
  • 양철승 (한국전자기술연구원 스마트가전혁신지원센터) ;
  • 김경호 (단국대학교 전자전기공학부)
  • 투고 : 2023.10.02
  • 심사 : 2023.11.10
  • 발행 : 2023.11.30
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초록

본 논문에서는 주거지 내의 재실자의 행동을 분류하기 위한 LSTM 모델을 개발하는 연구에 대해 다룬다. 다중센서의 구성은 실내 공기질을 측정하는 IAQ(Indoor air quality) 센서, 재실감지 및 위치를 추적하는 UWB 레이더, 재실자의 생체정보를 측정하기 위한 Piezo 센서로 구성되며 실제 주거환경과 유사한 실험환경을 구축하여 외출, 재실, 요리, 청소, 운동, 수면 등의 재실자 행동 데이터를 수집한다. 수집한 데이터를 이상치와 결측치를 전처리 후 LSTM 모델을 사용하여 재실자 행동 분류 모델의 정확도, 민감도, 특이도, 그리고 T1스코어를 계산 후 평가한다.

In this paper discuss with research developing an LSTM model for classifying the behavior of occupants within a residence. The multi-sensor consists of an IAQ (Indoor Air Quality) sensor that measures indoor air quality, a UWB radar that tracks occupancy detection and location, and a Piezo sensor to measure occupants' biometric information, and collects occupant behavior data such as going out, staying, cooking, cleaning, exercise, and sleep by constructed an experimental environment similar to the actual residential environment. After the data with removed outliers and missing, the LSTM model is used to calculate accuracy, sensitivity, specificity of the occupant behavior classification model, T1 score.

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과제정보

이 논문은 국토교통부의 국토교통기술사업화지원사업의 연구비지원에 의해 수행되었음 [과제명 : 비접촉 생체정보 측정기능이 포함된 스마트 디퓨저 기반 거주자 맞춤형 Home-HAS(Health, Air, Safety) 서비스 개발][과제번호 : 23TBIP-C161696-03]

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