Feasibility study of autonomous drone-based IoT device management in indoor environments

Abstract

Future computing environments are embedded with many sensors for applications like augmented reality. Much of the deployed Internet of Things (IoT) technology is designed to be invisible. To support user's privacy awareness, a map of surrounding sensing devices is beneficial to determine the nature of data collection taking place in any given area. Moreover, security and governance issues are among the challenges IoT poses to organizations which might not know exactly which IoT devices are connected to their network. For instance, many employees bringing their own devices to the workplace. We explore the feasibility to use small COTS drones to create indoor maps of wireless devices. These comprehensive device maps serve as basis for device localization and monitoring to enhance user privacy and network security. We analyze the impact of our device management platform at the drone's energy consumption and evaluate the device detection rate, explored area, and localization error. Due to the restricted battery capacity of the drone, we simulate larger areas with a varying number of IoT devices to highlight the limits of our drone-based device management platform regarding area exploration and reachable IoT devices.