Addressing the Need to Capture Scenarios, Intentions and Preferences: Interactive Intentional Programming in the Smart Home

Mathias Funk, Lin-Lin Chen, Shao-Wen Yang, Yen-Kuang Chen

The Internet of Things (IoT) and connected products have become part of the advance of ubiquitous technology into personal and professional living spaces, such as the smart home. What connectivity and distributed computing have made possible, is still programmed only according to more or less simplified rule systems (or in traditional code); the mapping between what end users intend or would value and what can be expressed in rules is not straightforward. This article analyzes the temporal, preferential, technical, and social complexity of mapping end-user intent to rules, and it suggests new concepts to better frame information that needs to be captured to create smart-home systems that better match users’ intents. We need a new approach aimed at first capturing end users’ intentions and potential usage scenarios, then providing this information to a control system that learns to resolve intentions and scenarios for available devices in the context. The new approach should deconstruct and rebuild IoT-related programming at a higher level of abstraction that allows end users to express long-term intentions and short-term preferences, instead of programming rules. Based on related work, a first-person perspective and analysis of current smart-home programming practices, the concept of Interactive Intentional Programming (IIP), is introduced and discussed.