Automated Data Monitoring System for Currency Validation Machines using ZigBee Technology and Neural Networks

Abstract

This article presents an automated monitoring system designed to enhance security and control in real-time banknote processing, aimed at identifying anomalies and suspicious activities. Data transmission is performed wirelessly through Xbee S2C modules with Zigbee technology, ensuring the integrity of information such as currency, denomination, serial number, quantity of pieces, rejects, and amounts in soles (Peruvian currency) and dollars. The system interface ensures real-time tracking, storage, and analysis of the recorded process. Furthermore, it predicts the lifespan of equipment and cash flow congestion in a banking agency using FeedForward neural networks. This system optimizes processes by analyzing usage patterns and processing times, providing an efficient and cost-effective solution for monitoring in banking agencies.