Earticle

초록

영어

Occupancy-based heating control is effective in reducing heating energy by preventing unnecessary heating during unoccupied period. Various technologies on detecting human occupancy have been developed using complicated machine learning algorithm and stochastic methodologies. This study aims at deriving low-cost and simple algorithm of occupancy inference that can be implemented to residential buildings. The core concept of the algorithm is to combine the occupancy probabilities based on indoor CO2 concentration and PIR(passive infrared) signals. The probability was estimated by applying different levels of decrement ratio depending on CO2 concentration change rate and aggregated PIR signals. The developed algorithm was validated by comparing the inference results with the occupancy schedule in a real residential building. The results showed that the inference algorithm can achieve the accuracy of 75~99%, which would be successfully implemented to the control of residential heating systems.

목차

Abstract
1. 서론
1.1 연구배경 및 목적
1.2 연구범위 및 방법
2. 재실 추정 알고리즘
2.1 재실 추정 개념
2.2 재실 추정 알고리즘
3. 재실 추정 알고리즘 적용
3.1 적용대상 주거 건물
3.2 재실 추정 결과
4. 결론
REFERENCES

저자

• 이규남 [ Rhee, Kyu-Nam | 부경대학교 건축공학과 조교수, 공학박사 ]
• 정근주 [ Jung, Gun-Joo | 부경대학교 건축공학과 교수, 공학박사 ] Corresponding author

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