Vasantha Kumar A@Vasanth_VK

Problem: Network outages and equipment failures can have severe consequences, including financial losses, disrupted services, and reputational damage. Traditional maintenance approaches are reactive, addressing issues only after they occur. This leads to inefficiencies, increased costs, and prolonged downtime. There is a critical need for a proactive solution that predicts potential failures and enables timely interventions solution:ProactiveGuard is a cutting-edge predictive maintenance system designed to revolutionize how organizations manage their infrastructure. The system integrates operational data (e.g., sensor readings), connectivity metrics (e.g., network performance), and geospatial data (e.g., location-based environmental factors) to predict failures before they happen. Key features of ProactiveGuard include: Real-Time Risk Prediction : Uses machine learning models to analyze historical and real-time data, providing accurate predictions of failure probabilities. Geospatial Insights : Incorporates location-specific data to identify patterns and correlations between environmental conditions and equipment performance. Actionable Alerts : Generates risk levels (Low, Medium, High) and actionable recommendations to guide maintenance teams. Scalable Architecture : Built with a modular design to support integration with IoT devices, APIs, and third-party systems.

Problem Statement: People with motor disabilities struggle to use digital devices. Voice commands are slow, and existing hardware solutions are expensive. 💡 Solution: An AI-powered eye-tracking cursor using IBM Granite Vision Transformer to enable hands-free control of PCs and smartphones with just eye movements and blinks. 🚀 Key Features: ✅ Gaze-Based Cursor Movement – Move the cursor by looking around. ✅ Blink to Click – Short blink for left-click, long blink for right-click. ✅ Gaze Scrolling – Look up/down to scroll pages and reels. ✅ Real-Time AI Adaptation – Model learns user-specific gaze patterns. ✅ No Extra Hardware Needed – Works with a standard webcam.