Indoor Occupancy Estimation Based on Synergy of Physical Modeling, Environmental Data Fusion, and Machine Learning Frameworks-Reference-Cited by-同舟云学术

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Indoor Occupancy Estimation Based on Synergy of Physical Modeling, Environmental Data Fusion, and Machine Learning Frameworks

Published:2024-06-03 Issue: Volume: Page:1-5
ISSN:
Container-title:2024 11th International Conference on Electrical, Electronic and Computing Engineering (IcETRAN)
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Author:

Popović Ivan¹^ORCID,Krčmar Igor²,Rakić Aleksandar³^ORCID

Affiliation:

1. University of Belgrade - School of Electrical Engineering,Dept. of Electronics,Belgrade,Serbia

2. University of Banja Luka - Faculty of Electrical Engineering,Dept. of Control Systems,Banja Luka,Bosnia and Herzegovina

3. University of Belgrade - School of Electrical Engineering,Dept. of Signals and Systems,Belgrade,Serbia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10645074/10645075/10645119.pdf?arnumber=10645119

Reference11 articles.

1. Occupancy Detection via Environmental Sensing

2. A Non-Intrusive Approach for Indoor Occupancy Detection in Smart Environments

3. Eyelight: Light-and-Shadow-Based Occupancy Estimation and Room Activity Recognition

4. Non-intrusive occupancy detection methods and models;Tyhurst,2019

5. A Machine Learning Approach to Indoor Occupancy Detection Using Non-Intrusive Environmental Sensor Data

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