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Discover how PES University students are revolutionizing indoor asset tracking for manufacturing with Edge AI and TinyML in this 57-minute EDGE AI TALK. Follow along as Professor Vadiraja Acharya and students Peddineni Bavitha and Prajwal M demonstrate their capstone project that combines Wi-Fi and BLE signals with machine learning on energy-efficient microcontrollers to create a real-time asset tracking and visualization system for factory floors. Learn about their innovative approaches to power optimization, tracking accuracy improvements, and 3D visualization techniques for intelligent asset monitoring in Industry 4.0 environments. The presentation covers BLE and Wi-Fi RSSI signal analysis, TinyML-powered location classification, real-time 3D asset tracking implementation, comparisons of low-power edge hardware options, and practical use cases for intelligent tracking in manufacturing settings.
