Jacob Abbott (Indiana University), Jayati Dev (Indiana University), DongInn Kim (Indiana University), Shakthidhar Reddy Gopavaram (Indiana University), Meera Iyer (Indiana University), Shivani Sadam (Indiana University) , Shirang Mare (Western Washington University), Tatiana Ringenberg (Purdue University), Vafa Andalibi (Indiana University), and L. Jean Camp(Indiana University)

In the last decade integration of Internet of Things (IoT) ecosystems has increased exponentially, and it is necessary that our understanding of human behavior when interacting with multiple smart devices in an IoT ecosystem keep pace. To better understand users’ perceptions and use of in-home IoT ecosystem over time, we implemented an ecosystem in homes of participants so that we could both test previous findings about individual devices and identify differences that arise in the content of a home with multiple IoT devices. Specifically, we recruited eight participants from separate households who installed identical IoT configurations, and interviewed each participant for five weeks. We included an Android dashboard to provide device control and data transparency. We detail the semi-structured interviews to compare user perceptions of what devices are classified as IoT, the perceived sustainability of IoT devices, interactions with and desires of dashboard information, and exploration of current notification preferences and mitigation strategies. We discuss the factors which participants identified as being relevant to their personal experiences with IoT devices and contribute recommendations for dashboard designs and control mechanisms for IoT devices. We note that the participants uniformly had a more expansive definition of IoT than that found in much of the previous literature, implying that our understanding of perceptions of in-home IoT may be informed by previous research on security systems, wearables, watches, and phones. We identify where our results reify findings of studies of those devices.

View More Papers

Preventing SIM Box Fraud Using Device Model Fingerprinting

BeomSeok Oh (KAIST), Junho Ahn (KAIST), Sangwook Bae (KAIST), Mincheol Son (KAIST), Yonghwa Lee (KAIST), Min Suk Kang (KAIST), Yongdae Kim (KAIST)

Read More

Detection and Resolution of Control Decision Anomalies

Prof. Kang Shin (Kevin and Nancy O'Connor Professor of Computer Science, and the Founding Director of the Real-Time Computing Laboratory (RTCL) in the Electrical Engineering and Computer Science Department at the University of Michigan)

Read More

Folk Models of Misinformation on Social Media

Filipo Sharevski (DePaul University), Amy Devine (DePaul University), Emma Pieroni (DePaul University), Peter Jachim (DePaul University)

Read More

Why People Still Fall for Phishing Emails: An Empirical...

Asangi Jayatilaka (Centre for Research on Engineering Software Technologies (CREST), The University of Adelaide, School of Computing Technologies, RMIT University), Nalin Asanka Gamagedara Arachchilage (School of Computer Science, The University of Auckland), M. Ali Babar (Centre for Research on Engineering Software Technologies (CREST), The University of Adelaide)

Read More