Cooking oil purity and reusability detection system using Embedded system

The reuse of cooking oil in kitchens poses significant health risks, as the oil undergoes chemical decomposition over time, releasing harmful compounds associated with heart disease and cancer. This paper presents a Cooking Oil Quality Detection System designed to monitor oil quality in real time using an ESP32 microcontroller and integrated sensors. The system employs turbidity, dielectric, DS18B20 temperature, and RGB colour sensors to provide a comprehensive assessment of the oil’s condition. Data is displayed on an OLED screen, while green, yellow, and red LEDs offer intuitive feedback on oil safety. This cost-effective, non-invasive solution enhances food safety by enabling timely decisions on oil reuse. Future enhancements include machine learning for predictive analytics and Internet of Things (IoT) integration for remote monitoring.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-09-08
DOI
https://doi.org/10.1051/e3sconf/202564803028/pdf
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
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article

Cooking oil purity and reusability detection system using Embedded system

Springer Link (Chiba Institute of Technology)
Geochemistry and Geologic Mapping
article

Cooking oil purity and reusability detection system using Embedded system

article en

Abstract

The reuse of cooking oil in kitchens poses significant health risks, as the oil undergoes chemical decomposition over time, releasing harmful compounds associated with heart disease and cancer. This paper presents a Cooking Oil Quality Detection System designed to monitor oil quality in real time using an ESP32 microcontroller and integrated sensors. The system employs turbidity, dielectric, DS18B20 temperature, and RGB colour sensors to provide a comprehensive assessment of the oil’s condition. Data is displayed on an OLED screen, while green, yellow, and red LEDs offer intuitive feedback on oil safety. This cost-effective, non-invasive solution enhances food safety by enabling timely decisions on oil reuse. Future enhancements include machine learning for predictive analytics and Internet of Things (IoT) integration for remote monitoring.

Springer Link (Chiba Institute of Technology)
Zero hunger
Openalex Percentile: Top 44%
Geochemistry and Geologic Mapping
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