AI/ML based Log Analysis and Predictive Maintenance on Safe Storage Devices

Artificial Intelligence and deep learning are playing key roles in the filed of anomaly detection and predictive maintenance. The goal of this work is to incorporate Machine Learning and Auto ML techniques in the context of Safe Storages, which can be used for different purposes like storing valuable items in banks. The first phase of this program is to build machine learning models or incorporate language models like Chatgpt and other Auto ML techniques in order to construct a virtual engineer which can be helpful to technicians in the workplace. A virtual engineer which receives and analyzes the log files of safe storage devices and detects the problem and suggests a way to fix it. The second phase is to build a predictive framework which enables us to predict when a failure is going to happen in the system. By having such information, we can reduce the costs related to maintenance and make the support process more efficient.