A Soft Sensor Approach for Cookware Classification and Temperature Estimation in Smart Domestic Induction Hobs

This study presents an approach to cookware classification and load identification for water temperature estimation on smart domestic induction hobs. By measuring the equivalent resistance and inductance of various cookware materials, a soft sensor model was developed to estimate real-time water temperatures with a thermistor sensor. This method eliminates the need for expensive sensors and improves the overall cost-efficiency of induction cooking systems. The classification is based on electrical parameters, with experiments conducted to validate the accuracy of the proposed method. Results demonstrate reliable temperature predictions within acceptable error margins, enabling control of water temperature in real-world environments.

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Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/isas64331.2024.10845449
Primary Topic
Food Supply Chain Traceability
Type
article
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article

A Soft Sensor Approach for Cookware Classification and Temperature Estimation in Smart Domestic Induction Hobs

M. Selçuk Arslan, Hakan Altuntaş
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Food Supply Chain Traceability
article

A Soft Sensor Approach for Cookware Classification and Temperature Estimation in Smart Domestic Induction Hobs

M. Selçuk Arslan, Hakan Altuntaş
article en

Abstract

This study presents an approach to cookware classification and load identification for water temperature estimation on smart domestic induction hobs. By measuring the equivalent resistance and inductance of various cookware materials, a soft sensor model was developed to estimate real-time water temperatures with a thermistor sensor. This method eliminates the need for expensive sensors and improves the overall cost-efficiency of induction cooking systems. The classification is based on electrical parameters, with experiments conducted to validate the accuracy of the proposed method. Results demonstrate reliable temperature predictions within acceptable error margins, enabling control of water temperature in real-world environments.

Yıldız Technical University (TR)
Openalex Percentile: Top 68%
Food Supply Chain Traceability
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