The goal of our research group is to develop architectures, methodologies, and tools that facilitate effective and efficient collection and use of Auto-ID data in order to monitor performance, predict system anomalies, and make timely decisions for improved performance. Our research efforts are focused on various Auto-ID technologies and their applications in network-centric manufacturing, adaptive inventory management, shop floor control, warehouse operations, distributed decision-making, wireless sensor networks, and multi-sensor environments.

We are looking forward to working with manufacturing industry to provide them with viable solutions, as well as with Auto-ID hardware and software vendors to test, evaluate, and improve their products.