| 大会名称 |
| 2021年 総合大会 |
| 大会コ－ド |
| 2021G |
| 開催年 |
|
2021
|
| 発行日 |
|
2021-02-23
|
| セッション番号 |
|
BS-7
|
| セッション名 |
|
AI technologies and their applications for future network systems and services
|
| 講演日 |
|
2021/3/9
|
| 講演場所(会議室等) |
|
Meeting 30
|
| 講演番号 |
|
BS-7-7
|
| タイトル |
|
A Room Occupancy Detection Using WiFi Signals for Building Energy Management Systems
|
| 著者名 |
|
◎Tasha A. Fahira, Masaki Bandai,
|
| キーワード |
|
Smart Building, Localization, Building Energy Management System, IoT
|
| 抄録 |
|
Building Energy Management (BEM) systems have been implemented to manage the increasing energy demand. Understanding the number of occupants and usage behavior can improve the energy efficiency in buildings. Therefore, occupancy detection has been integrated into BEM systems to improve its performance. In this paper, we propose a WiFi-based room occupancy detection system for BEM applications by expanding an indoor localization method. Through evaluation using the data obtained in a real building, we confirm the effectiveness of the proposed method and consider the future extension of the system.
|
| 本文pdf |
|
PDF download
|
