Abstract:  Current material identification methods are mainly based on X-ray technology, ultrasound technology and radio frequency technology. However, X-ray technology relies on special equipment to transmit high frequency signals and is highly radioactive; ultrasonic technology equipment is bulky and inconvenient to carry; and RF(Radio Frequency) technology mainly relies on costly RFID(Radio Frequency Identification Devices). In order to meet the daily use in home and office scenarios, MateFi system for material identification is proposed based on WiFi(Wireless Fidelity), aiming to establish a new theoretical model to describe more specifically the attenuation state of electromagnetic waves as they penetrate different materials. The theoretical model is used to build a more robust and accurate material recognition system by combining material characteristics with machine learning techniques. The performance of the MateFi system is tested and validated in real-life scenarios. The experiments show that MateFi can recognise six different materials: wood, cardboard, nickel, thin wood, iron and titanium, with an average recognition accuracy of 96. 70% , demonstrating the system’s ability to identify materials accurately. 

Key words: channel status information (CSI)')">

channel status information (CSI), wireless fidelity(WiFi), material identification, randomness