Towards a rich sensing stack for IoT devices

The broad spectrum of interconnected sensors and actuators, available on various mobile devices and smartphones and collectively defined as the Internet of Things (IoT), have evolved into platforms with ability to both collect personal sensory data and also change the users' immediate environment. The continuous streams of richly annotated sensory data on these IoT devices have also enabled the emergence of a new class of context-aware apps that use the data to infer user context and accordingly customize their responses in real-time. However, this growth in the number of apps has not been complemented with adequate system support on the IoT devices resulting in monolithic apps that each implement and execute their own customized sensing pipelines. In this paper, we outline our vision of a sensing stack, akin to a networking stack, that can facilitate the development and execution of context-aware apps on IoT devices. There are several advantages to building a rich sensing stack. First, it allows apps to reuse stages of the sensing pipeline easing their development. Second, the layers of the stack allow for both in- and cross-layer resource optimization. Finally, it allows better control over the shared data as instead of raw-sensor data, higher-level semantic abstractions, such as inferences can now be shared with apps. We describe our initial efforts towards creating the different building blocks of such a sensing stack.