Therefore, in this paper, an occupancy detection algorithm with an average accuracy of about 89% was developed using a smart plug that can be used in daily life ...

Therefore, in this paper, an occupancy detection algorithm with an average accuracy of about 89% was developed using a smart plug that can be used in daily life ...

[31] proposed an occupancy detection model based on an LSTM architecture by using the energy consumption data collected from smart plugs to identify occupant ...

Inproceedings,. LSTM-based Office Occupancy Detection Using Smart plug Data. S. Park, K ...

Sep 1, 2024 · Occupancy prediction based on a minimum sensing strategy by identifying the most significant features using a comprehensive set of sensor data ...

Mar 10, 2024 · Buildings 183 (2019): 195-208. [21] Park, Seunghyeon, et al. "Lstm-based office occupancy detection. using smart plug data." 2021 International ...

Jan 25, 2024 · This study aims to develop a cost-effective occupancy detection model using machine learning algorithms based on individual plug load data. The ...

Abstract. Plug load management systems are touted as promising solutions to reduce the rising energy consumption of plug loads in commercial buildings through ...

[21] introduced an occupancy detection model based on Long Short-Term Memory (LSTM) architecture. They utilized energy consumption data obtained from smart ...

Feb 7, 2023 · In this work, we provide a smart home occupancy prediction technique based on environmental variables such as CO2, noise, and relative ...