TY - GEN
T1 - Enhancing Occupancy Detection Through IoT
T2 - 15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024
AU - Davrazos, Gregory
AU - Raftopoulos, George
AU - Panagiotakopoulos, Theodor
AU - Kotsiantis, Sotiris
AU - Kameas, Achilles
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This study presents a comprehensive comparative analysis of classifier performance for enhancing occupancy detection in Internet of Things (IoT) environments. Occupancy detection is a crucial aspect in various applications such as smart buildings, energy management, and security systems. Leveraging IoT data, we evaluate the effectiveness of different classifiers in accurately detecting occupancy. Through experimentation and analysis, we identify the strengths and limitations of various classifiers, providing insights into their suitability for real-world deployment. Our findings offer valuable guidance for selecting the most suitable classifier for occupancy detection tasks in IoT environments, ultimately contributing to improved efficiency and effectiveness in IoT-based systems.
AB - This study presents a comprehensive comparative analysis of classifier performance for enhancing occupancy detection in Internet of Things (IoT) environments. Occupancy detection is a crucial aspect in various applications such as smart buildings, energy management, and security systems. Leveraging IoT data, we evaluate the effectiveness of different classifiers in accurately detecting occupancy. Through experimentation and analysis, we identify the strengths and limitations of various classifiers, providing insights into their suitability for real-world deployment. Our findings offer valuable guidance for selecting the most suitable classifier for occupancy detection tasks in IoT environments, ultimately contributing to improved efficiency and effectiveness in IoT-based systems.
KW - AutoML
KW - In-door Occupancy
KW - Internet of Things
KW - Interpretable Machine Learning
KW - PyCaret
UR - http://www.scopus.com/inward/record.url?scp=85215801943&partnerID=8YFLogxK
U2 - 10.1109/IISA62523.2024.10786627
DO - 10.1109/IISA62523.2024.10786627
M3 - Conference contribution
AN - SCOPUS:85215801943
T3 - 15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024
BT - 15th International Conference on Information, Intelligence, Systems and Applications, IISA 2024
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 17 July 2024 through 20 July 2024
ER -