AI enabled: a novel IoT-based fake currency detection using millimeter wave (mmWave) sensor

Niaz, Fahim; Zhang, Jian; Khalid, Muhammad; Qureshi, Kashif Naseer; Zheng, Yang; Younas, Muhammad; Imran, Naveed

doi:10.1007/s00607-024-01300-2

Computing

2024

DOI: 10.1007/s00607-024-01300-2

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AI enabled: a novel IoT-based fake currency detection using millimeter wave (mmWave) sensor

Fahim Niaz,

Jian Zhang,

Muhammad Khalid

et al.

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mm-CUR: A Novel Ubiquitous, Contact-free, and Location-aware Counterfeit Currency Detection in Bundles Using Millimeter-Wave Sensor

Niaz,

Zhang,

Zheng

et al. 2024

ACM Trans. Sen. Netw.

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Target material sensing in non-invasive and ubiquitous contexts plays an important role in various applications. Recently, a few wireless sensing systems have been proposed for material identification. In this article, we introduce mm-CUR, A Novel Ubiquitous, Contact-free, and Location-aware Counterfeit Currency Detection in Bundles using a Millimeter-Wave Sensor. This system eliminates the need for individual note inspection and pinpoints the location of counterfeit notes within the bundle. We use Frequency Modulated Continuous Wave (FMCW) radar sensors to classify different counterfeit currency bundles on a tabletop setup. To extract informative features for currency detection from FMCW signals, we construct a Radio Frequency Snapshot (RFS) and build signal scalogram representations that capture the distinct patterns of currency received from different currency bundles. We refine the RFS by eliminating multi-path interference, and noise cancellation and apply high pass filters for mitigating the smearing effect with the continuous wavelet transform (CWT). To broaden the usage of mm-CUR, we built a transferable learning model that yields robust detection results in different scenarios. The classification results demonstrated that the proposed counterfeit currency detection system can detect counterfeit notes in 100-note bundles with an accuracy greater than 93%. Compared to the standard CNN and DNN methods, the proposed mm-CUR model showed superior performance in distinguishing each bundle data, even for a limited-size dataset.

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mm-CUR: A Novel Ubiquitous, Contact-free, and Location-aware Counterfeit Currency Detection in Bundles Using Millimeter-Wave Sensor

Niaz,

Zhang,

Zheng

et al. 2024

ACM Trans. Sen. Netw.

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show abstract

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AI enabled: a novel IoT-based fake currency detection using millimeter wave (mmWave) sensor

Cited by 1 publication

References 34 publications

mm-CUR: A Novel Ubiquitous, Contact-free, and Location-aware Counterfeit Currency Detection in Bundles Using Millimeter-Wave Sensor

mm-CUR: A Novel Ubiquitous, Contact-free, and Location-aware Counterfeit Currency Detection in Bundles Using Millimeter-Wave Sensor

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