Agent-Based Faults Monitoring in Automatic Teller Machines

Abstract

Automated Teller Machine (ATM) has gained widespread acceptance as a convenient medium to facilitate financial transaction without need for human agent. However, ATM deployers are facing challenges in maximizing the uptime of their ATMs as a result of wide gap in fault detection, notification and correction of the ATMs. One way to ameliorate this situation is through intelligent monitoring of ATM by resident software agents that monitor the device real time and report faulty components real time to facilitate quick response. We proposed an architecture for rule-based, intelligent agent based monitoring and management of ATMs. Agents are used to perform remote monitoring on the ATMs and control function such software maintenance. Such agents can detect basic events or correlate existing events that are stored in a database to detect faults. A system administrator can securely modify the monitoring policies and control functions of agents. The framework presented here includes software fault monitor, hardware fault monitor and transaction monitor. A set of utility support agents: caller agent and log agent are used to alert network operator and log error and transaction information in a database respectively. at-1, stuck-at-0 faults in digital circuits validate the point that faulty circuits dissipates more and hence draw more power.