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All Journal International Journal Of Economics Social And Technology
Calvin Eben Ezer Silaban
Universitas Prima Indonesia
Automotive Engineering Computer Science & IT Economics, Econometrics & Finance Law, Crime, Criminology & Criminal Justice Social Sciences

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Smart Piggy Bank System with Multi-Sensor Counterfeit Banknote Detection and Real-Time IoT Monitoring Calvin Eben Ezer Silaban; Despaleri Perangin Angin; Rianto Nadapdap
International Journal Of Economics Social And Technology Vol. 5 No. 1 (2026): Maret-Mei 2026
Publisher : Lembaga Riset Ilmiah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59086/ijest.v5i1.1448

Abstract

The circulation of counterfeit banknotes poses a growing risk to individuals and small businesses that rely on cash-based savings, yet most prior studies address counterfeit detection and automated savings management in isolation. This research addresses that gap by designing and implementing a Smart Piggy Bank System that simultaneously performs multi-sensor counterfeit banknote detection and real-time IoT-based financial monitoring. The proposed system integrates an IR sensor and photodiode for banknote insertion detection, a TCS34725 RGB color sensor for denomination identification, and a UV sensor for authenticity verification. An Arduino microcontroller processes sensor data and displays results on a 16×2 LCD, while an ESP8266 module transmits transaction data to the Blynk IoT cloud platform for real-time remote monitoring. Experimental validation was conducted on Indonesian banknotes of Rp20,000, Rp50,000, and Rp100,000 under both good and wrinkled physical conditions across 11 trials. The system achieved an overall detection accuracy of 90.91%, calculated as (correct detections / total trials) × 100% = 10/11, with an average response time of 1.5–2.2 seconds. The sole misclassification occurred on a wrinkled Rp20,000 banknote due to RGB and UV signal instability under degraded physical conditions. Compared to prior single-sensor systems, the proposed multi-sensor fusion approach improves detection robustness, while the IoT integration provides real-time transaction transparency unavailable in isolated detection systems
Co-Authors Despaleri Perangin Angin Rianto Nadapdap