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Hardware Accelerated Image Processing on an FPGA-SoC Based Vision System for Closed Loop Monitoring and Additive Manufacturing Process Control Read chapter Read first chapter

2019 | OriginalPaper | Chapter

A Dynamic Convergence Algorithm for Thermal Comfort Modelling

Authors : Asimina Dimara, Christos Timplalexis, Stelios Krinidis, Dimitrios Tzovaras

Published in: Computer Vision Systems

Publisher: Springer International Publishing

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Abstract

This paper attempts to utilize experimental results in order to correlate clothing insulation and metabolic rate with indoor temperature. Inferring clothing insulation and metabolic rate values from ASHRAE standards is an alternative that totally ignores environmental conditions that actually affect human clothing and activity. In this work, comfort feedback regarding occupants’ thermal sensation is utilized by an algorithm that predicts clothing insulation and metabolic rate values. The analysis of those values reveals certain patterns that lead to the formulation of two non-linear equations between clothing – indoor temperature and metabolic rate – indoor temperature. The formulation of the equations is based on the experimental results derived from the thermal comfort feedback provided by actual building occupants. On trial tests are presented and conclusions regarding the method’s effectiveness and limitations are drawn.

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previous chapter Occupancy Inference Through Energy Consumption Data: A Smart Home Experiment
next chapter Thermal Comfort Metabolic Rate and Clothing Inference
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Metadata
Title
A Dynamic Convergence Algorithm for Thermal Comfort Modelling
Authors
Asimina Dimara
Christos Timplalexis
Stelios Krinidis
Dimitrios Tzovaras
Copyright Year
2019
Book
Computer Vision Systems

Print ISBN: 978-3-030-34994-3

Electronic ISBN: 978-3-030-34995-0

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-34995-0_62

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