Sensor Fusion and Convolutional Neural Networks for Indoor Occupancy Prediction Using Multiple Low-Cost Low-Resolution Heat Sensor Data

Sensor Fusion and Convolutional Neural Networks for Indoor Occupancy Prediction Using Multiple Low-Cost Low-Resolution Heat Sensor Data

Indoor occupancy prediction is a prerequisite for the management of energy consumption, security, health, and other systems in smart buildings. Previous studies have shown that buildings that automatize their heating, lighting, air conditioning, and ventilation systems through considering the occupa...

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Bibliographic Details
Main Authors: Simon Arvidsson, Marcus Gullstrand, Beril Sirmacek, Maria Riveiro
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Sensors
Subjects:
heat sensors
multi-sensor
sensor fusion
occupancy prediction
machine learning
artificial intelligence (AI)
Online Access:https://www.mdpi.com/1424-8220/21/4/1036

Internet

https://www.mdpi.com/1424-8220/21/4/1036

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