Modeling, learning, and leveraging functional data in smart and connected systems

In smart and connected systems, functional data is becoming increasingly prevalent due to advancements in sensing technologies. The uniqueness of functional data is that it provides continuous and smooth measurements. For example, temperature readings in a roasting process cycle or heart rate measurements from wearable health devices are inherently time-varying, serving as functional data. Compared with scalar data, functional data exhibits intrinsic correlations in temporal and/or spatial domains, allowing for the description of patterns and trends embedded within it. When modeled correctly, these patterns can provide valuable insights for anomaly detection, performance optimization, and smart decision-making.