Indoor Occupancy Estimation Using Advanced Support Vector Machine Learning Algorithm-Reference-Cited by-同舟云学术

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Indoor Occupancy Estimation Using Advanced Support Vector Machine Learning Algorithm

Published:2024-04-02 Issue: Volume:5 Page:1-6
ISSN:
Container-title:2024 International Conference on Science, Engineering and Business for Driving Sustainable Development Goals (SEB4SDG)
language:
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Author:

Fabunmi Elizabeth Y.¹,Oluwole Ayodele²,Oluwafemi Ilesanmi B.³,Akinsanmi Olaitan²,O. Agbolade J.⁴,Petirin Oluyemi O.¹,Obiajulu Onyemenam J.⁵,Dotun Ijagbemi⁵

Affiliation:

1. Federal Polytechnic,Department of Electrical and Electronic Engineering,Ede

2. Federal University of Oye Ekiti,Department of Electrical and Electronic Engineering,Oye-Ekiti,Nigeria

3. Ekiti State Universuty Ado Ekiti,Department of Electrical and Electronic Engineering,Ado Ekiti,Nigeria

4. Federal Polytechnic,Department of Electrical and Electronic Engineering,Ede,Osun State

5. Landmark University,Department of Electriacl and Information Engineering,Omu-Aran

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10629651/10629654/10629880.pdf?arnumber=10629880

Reference25 articles.

1. Occupancy Estimation Using Only WiFi Power Measurements

2. Human object estimation via backscattered radio frequency signal

3. People Counting Based on an IR-UWB Radar Sensor

4. Trained-once device-free crowd counting and occupancy estimation using WiFi: A Doppler spectrum based approach

5. Device-free occupant activity sensing using WiFi-enabled IoT devices for smart homes;Yang,2018

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