Boonyarit Kumkhet

Dr. Boonyarit Kumkhet

orcid

Research Focus & Metrics

Academic Career Length

1Year (2026-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 January 2026 in IEEE Access
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Journal Article
Open access
Nisit PukrongtaNisit Pukrongta
Nisit Pukrongta
BKBoonyarit Kumkhet
Boonyarit Kumkhet
PSPubet Sangmahamad
Pubet Sangmahamad
VPVirote Pirajnanchai
Virote Pirajnanchai

20 September 2026 in Electronics
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Journal Article
Open access
PDF file
BKBoonyarit Kumkhet
Boonyarit Kumkhet
TPtanaporn pechrkool
tanaporn pechrkool
PSPubet Sangmahamad
Pubet Sangmahamad
NTNipont Tangthong
Nipont Tangthong
PSPatchadaporn Sangpet
Patchadaporn Sangpet
PAPrayoot Akkaraekthalin
Prayoot Akkaraekthalin
This work presents an S21-based 2.4 GHz microwave sensing system with a 3D-printed dielectric lens for automatic passenger counting in aircraft applications. The proposed system employs a pair of microwave antennas forming a transmission sensing link across the passenger pathway, where the presence of a passenger perturbs the transmitted microwave signal and produces a detectable variation in the transmission coefficient, S21. A hemispherical dielectric lens fabricated from acrylonitrile butadiene styrene (ABS) is integrated with each antenna to improve the directional radiation characteristics of the sensing link. The measurements show that the lens increases the average realized gain from 2.26 to 4.02 dBi while maintaining operation at 2.4 GHz. The sensing system is integrated with a NanoVNA and a MATLAB-based processing platform for sequential S21 acquisition, human-event discrimination, automatic counting, and automatic display updating. Experimental responses obtained from humans and representative non-human materials, including plywood, plastic, and steel, demonstrate distinguishable S21 characteristics under the investigated conditions and provide the basis for an experimentally derived human-response detection window. The complete system was experimentally evaluated in an actual Airbus A320 aircraft using 30 participants over five repeated counting trials. The system achieved a mean counting accuracy of 90.67%. These results demonstrate the feasibility of the proposed microwave sensing approach for aircraft passenger-counting applications.