Instinctive Assistive Indoor Navigation using Distributed Intelligence

Cyber-physical systems (CPS) and the Internet of Things (IoT) offer a significant potential to improve the effectiveness of assistive technologies for those with physical disabilities. Practical assistive technologies should minimize the number of inputs from users to reduce their cognitive and physical effort. This article presents an energy-efficient framework and algorithm for assistive indoor navigation with multi-modal user input. The goal of the proposed framework is to simplify the navigation tasks and make them more instinctive for the user. Our framework automates indoor navigation using only a few user commands captured through a wearable device. The proposed methodology is evaluated using both a virtual smart building and a prototype. The evaluations for three different floorplans show one order of magnitude reduction in user effort and communication energy required for navigation, when compared to conventional navigation methodologies that require continuous user inputs.