Machine Learning Enabled Food Contamination Detection Using RFID and Internet of Things System

نویسندگان

چکیده

This paper presents an approach based on radio frequency identification (RFID) and machine learning for contamination sensing of food items drinks such as soft drinks, alcohol, baby formula milk, etc. We employ sticker-type inkjet printed ultra-high-frequency (UHF) RFID tags experimentation. The tag antenna was mounted pure well contaminated products with known contaminant quantity. received signal strength indicator (RSSI), the phase backscattered from item, are measured using Tagformance Pro setup. used a machine-learning algorithm XGBoost further training model improving accuracy sensing, which is about 90%. Therefore, this research study paves way ubiquitous contamination/content technologies that can enlighten their users health concerns safety food.

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ژورنال

عنوان ژورنال: Journal of Sensor and Actuator Networks

سال: 2021

ISSN: ['2224-2708']

DOI: https://doi.org/10.3390/jsan10040063