ACM SIGCOMM MAGESys 2019

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 a 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. 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 system security. We analyze the impact of our device 
detection platform at the drone's energy consumption. In 
addition, we evaluate our indoor device detection in terms 
of 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 
detection regarding spatial expansion and reachable devices.


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ACM Library Access

@inproceedings{Haus:MAGESys2019,
 author = {Haus, Michael and Krol, Jan and Ding, Aaron Yi and Ott, J\"{o}rg},
 title = {Feasibility Study of Autonomous Drone-based IoT Device Management in Indoor Environments},
 booktitle = {Proceedings of the ACM SIGCOMM 2019 Workshop on Mobile AirGround Edge Computing, Systems, Networks, and Applications},
 series = {MAGESys'19},
 year = {2019},
 isbn = {978-1-4503-6879-7},
 location = {Beijing, China},
 pages = {1--7},
 numpages = {7},
 url = {http://doi.acm.org/10.1145/3341568.3342105},
 doi = {10.1145/3341568.3342105},
 acmid = {3342105},
 publisher = {ACM},
}

M. Haus, J. Krol, A. Y. Ding, J. Ott. Feasibility Study of Autonomous Drone-based IoT Device Management in Indoor Environments. In Proceedings of the ACM SIGCOMM 2019 Workshop on Mobile AirGround Edge Computing, Systems, Networks, and Applications (MAGESys'19).