AI Powered Laptop Fault Detection and Diagnosis

This project showcases a sophisticated AI-powered chatbot created with PyTorch that is intended to improve laptop operation through predictive maintenance, tailored user experience, energy management, and security improvements. By monitoring and analyzing system data such as temperature, RAM utilization, performance, and possible threats, the chatbot predicts faults, makes suggestions, and increases efficiency. It also learns user habits to adapt suggestions, maximizes battery life, and detects security risks to protect the device. This complete assistant uses machine learning and natural language processing in a web application to increase device dependability and user happiness Fault diagnosis is detecting irregularities in a system’s performance using data from sensors, logs, or real-time activities. It focuses on identifying anomalies in important factors like as temperature, memory consumption, disk health, and network traffic. This procedure frequently comprises fault detection, which detects deviations from normal operating conditions; fault isolation, which identifies the specific component or process producing the problem; and fault analysis, which finds the root cause of the failure and recommends remedial actions. Modern problem diagnostic systems use artificial intelligence and machine learning to increase accuracy and efficiency. Algorithms are taught using previous data to detect patterns and forecast failures. This predictive functionality decreases downtime, lowers maintenance costs, and extends gadget life.