Industrial systems are rapidly shifting from human-controlled processes towards closed-loop control systems that leverage massive sensing and machine learning (ML) to manage their operations autonomously. This paradigm shift is a key to enable emerging data-intensive and delay-sensitive Industry 4.0 applications, particularly at remote sites, e.g., offshore oil and gas fields or solar farms, where the access to cloud services is limited and human resources are scarce. Realizing these systems mandates addressing challenging research questions to enable real-time data collection and processing, low latency (sub-milliseconds) wireless data communications, robustness against uncertainties, and smart decision making.
Accordingly, this project aims to develop a robust communications-computing framework for future wireless federated fog computing systems that can serve Machine Learning applications in remote Industry 4.0 systems. To benefit from complementary expertise required for addressing unique challenges of such cross-disciplinary research and to support advanced research equipment needed in this project, we pursue an international collaboration with experts at IMDEA Networks Institute, in Madrid, Spain. IMDEA is a world-class research institution that focuses on next-generation communications and computing systems.