Current - Issue
Original Article
AI-Based Multi-Parameter Food Spoilage Prediction System
Ravada Sharon Fragrance1
Marla Sai Shivani2
Choudari harish3
Peesa Kusuma Lakshmi Samyuktha4
Caleb Joseph Fernandez5
Gade Suryadeep6
1 Assistant Professor, Department Of ECE, Dr. Lankapalli Bullayya College of Engineering, Andhra Pradesh, India. 2 3 4 5 6 Department of ECE, Dr. Lankapalli Bullayya College of Engineering, Andhra University, Andhra Pradesh, India.
Published Online: July-August 2026
Pages: 78-82
Cite this article
↗ https://www.doi.org/10.59256/ijsreat.20260604008
References
1. S. Kumar, R. Sharma, and A. Singh, “IoT-Based Food Freshness Monitoring System Using Gas Sensors,” International Journal of
Engineering Research & Technology (IJERT), vol. 9, no. 5, pp. 120–125, 2020.
2. M. Patel and J. Shah, “Food Spoilage Detection Using Machine Learning Techniques,” International Journal of Advanced Research in
Computer Science (IJARCS), vol. 10, no. 3, pp. 45–50, 2019.
3. P. Verma, P. Gupta, and S. Mehta, “Smart Food Monitoring System Using IoT and Sensor Fusion,” IEEE Access, vol. 8, pp. 123456–
123465, 2020.
4. J. Brown and K. Davis, “Application of Random Forest Algorithm in Food Quality Prediction,” Journal of Food Engineering, vol. 256,
pp. 45–53, 2019.
5. J. Han, M. Kamber, and J. Pei, Data Mining: Concepts and Techniques, 3rd ed. Burlington, MA, USA: Morgan Kaufmann, 2012.
6. L. Breiman, “Random Forests,” Machine Learning, vol. 45, no. 1, pp. 5–32, 2001.
7. Food and Agriculture Organization (FAO), The State of Food and Agriculture 2019: Moving Forward on Food Loss and Waste
Reduction. Rome, Italy: FAO, 2019.
8. World Health Organization (WHO), Food Safety: Key Facts, Geneva, Switzerland: WHO, 2022.
9. Espressif Systems, ESP32 Series Datasheet, Shanghai, China, 2023.
10. Scikit-learn Developers, “Scikit-learn: Machine Learning in Python,” 2024.
11. Adafruit Industries, DHT22 Temperature and Humidity Sensor Technical Documentation, New York, NY, USA, 2023.
12. SparkFun Electronics, HX711 Load Cell Amplifier Hookup Guide, Boulder, CO, USA, 2023.
13. Components101, MQ135 Air Quality Gas Sensor – Technical Specifications, 2023.
14. Maxim Integrated, DS18B20 Programmable Resolution 1-Wire Digital Thermometer Datasheet, San Jose, CA, USA, 2022.
Engineering Research & Technology (IJERT), vol. 9, no. 5, pp. 120–125, 2020.
2. M. Patel and J. Shah, “Food Spoilage Detection Using Machine Learning Techniques,” International Journal of Advanced Research in
Computer Science (IJARCS), vol. 10, no. 3, pp. 45–50, 2019.
3. P. Verma, P. Gupta, and S. Mehta, “Smart Food Monitoring System Using IoT and Sensor Fusion,” IEEE Access, vol. 8, pp. 123456–
123465, 2020.
4. J. Brown and K. Davis, “Application of Random Forest Algorithm in Food Quality Prediction,” Journal of Food Engineering, vol. 256,
pp. 45–53, 2019.
5. J. Han, M. Kamber, and J. Pei, Data Mining: Concepts and Techniques, 3rd ed. Burlington, MA, USA: Morgan Kaufmann, 2012.
6. L. Breiman, “Random Forests,” Machine Learning, vol. 45, no. 1, pp. 5–32, 2001.
7. Food and Agriculture Organization (FAO), The State of Food and Agriculture 2019: Moving Forward on Food Loss and Waste
Reduction. Rome, Italy: FAO, 2019.
8. World Health Organization (WHO), Food Safety: Key Facts, Geneva, Switzerland: WHO, 2022.
9. Espressif Systems, ESP32 Series Datasheet, Shanghai, China, 2023.
10. Scikit-learn Developers, “Scikit-learn: Machine Learning in Python,” 2024.
11. Adafruit Industries, DHT22 Temperature and Humidity Sensor Technical Documentation, New York, NY, USA, 2023.
12. SparkFun Electronics, HX711 Load Cell Amplifier Hookup Guide, Boulder, CO, USA, 2023.
13. Components101, MQ135 Air Quality Gas Sensor – Technical Specifications, 2023.
14. Maxim Integrated, DS18B20 Programmable Resolution 1-Wire Digital Thermometer Datasheet, San Jose, CA, USA, 2022.
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