A scalable IoT framework to design logical data flow using virtual sensor

During recent years, we have witnessed an explosion in the Internet of Thing (IoT) in terms of the number and types of physical devices. However, there are many limitations of these devices regarding their computing power, storage, and connection capabilities. They affect on-device processing of sensed data significantly. Centralized treatment of IoT data has proven challenging for many use cases demanding real time response. This paper aims at augmenting sensor data processing using the concept of virtual sensors. We propose a scalable virtual sensor framework that supports building a logical dataflow (LDF) by visualizing either physical sensors or custom virtual sensors. The process produces high-level information from the sensed data that can be easily perceived by machines and humans. A web-based virtual sensor editor (VSE) is also implemented on the top of the framework to simplify creation and configuration of the LDF. The VSE supports cross-platform and real-time verification for composed LDF. The paper also presents a catalog of supported virtual sensor type along with preliminary performance study.