A Support System for Managing Failures of an Electronic Gaming Machine Environment
Computer systems, and in particular hosting servers such as Electronic Gaming Machines (EGM), have become very complex systems, and the requirement for 24/7 service requires fast correction of machine failures. Networks can include several thousands of devices, spread out over a geographic area of thousands of square kilometers. Maintenance and downtime can cost millions of dollars per year. System operators and technicians need the ability to monitor, diagnose, analyze and predict a problem from available information (events, alarms, diagnostic reports, log files etc.), in order to quickly perform the required corrective actions. The objective of this research is to utilize information retrieval and machine learning techniques to design and develop a semi automated decision support system for managing failures of an EGM environment.