Unlocking Contextual Intelligence - Anywhere, Anytime, and Everywhere

Despite having billions of data sensing devices that virtually acquire data about anything, anywhere, not all smart applications are intelligent. Context-awareness being at the core of intelligence, it is a contradiction founded on the impotence of these applications to effectively leverage this plethora of big data and infer context in real-time. Hence, in this paper, we propose a conceptual architecture and instantiate a working prototype of the Distributed Contextual Intelligence System (DCIS) - a ubiquitous, mobile edge-based context management mechanism. Unlike any traditional Context Management System, DCIS is an ultra lightweight, event-driven, dynamically scaling agent-based system that overcomes the barriers to ubiquitous contextfacilitating context anywhere, anytime, and everywhere so that any application can be intelligent. Our prototype - Zoolocity, is based on edge devices that execute light-weight context inference on data that it can acquire and dynamically collaborate with nearby edges in real-time. Thus, unlike any previous works that do not provide any evidence or motivation towards distributed context management, we demonstrate how applications can use DCIS agents to become fully context-aware about any scene it is involved in, unlocking any intelligent feature. This is enabled by two key novel contributions: a method to spontaneously share interoperable context and infer geospatially sparse complex activities in near real-time using generalised entity interaction modelling.