Building Occupancy Detection using Machine Learning-based Approaches: Evaluation and Comparison-Reference-Cited by-同舟云学术

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Building Occupancy Detection using Machine Learning-based Approaches: Evaluation and Comparison

Published:2022-10-17 Issue: Volume: Page:
ISSN:
Container-title:IECON 2022 – 48th Annual Conference of the IEEE Industrial Electronics Society
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Author:

Kanthila Chinmayi¹,Boodi Abhinandana²,Beddiar Karim¹,Amirat Yassine³,Benbouzid Mohamed¹

Affiliation:

1. University of Brest,UMR CNRS 6027 IRDL,Brest,France

2. CESI LINEACT,Brest,France

3. L@bISEN,ISEN Yncréa Ouest,Brest,France

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9968313/9968303/09968768.pdf?arnumber=9968768

Reference26 articles.

1. Integrated sensor data processing for occupancy detection in residential buildings

2. Measuring and monitoring occupancy with an RFID based system for demand-driven HVAC operations

3. Contextual occupancy detection for smart office by pattern recognition of electricity consumption data

4. Accurate occupancy detection of an office room from light, temperature, humidity and CO 2 measurements using statistical learning models

5. LSTM-based Office Occupancy Detection Using Smart plug Data

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Optimizing Comfort and Energy Efficiency: The Impact of Model Accuracy on Multi-Objective MPC;2024 6th Global Power, Energy and Communication Conference (GPECOM);2024-06-04

2. Occupancy Prediction in Buildings Using Cascaded LSTM Model;IECON 2023- 49th Annual Conference of the IEEE Industrial Electronics Society;2023-10-16

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