Nothing Special   »   [go: up one dir, main page]

skip to main content
research-article
Open access

Reshaping the Smart Home Research and Development in the Pandemic Era: Considerations around Scalable and Easy-to-Install Design

Published: 07 April 2022 Publication History

Abstract

Smart home research has traditionally included visiting participants' homes to build testbed environments and evaluate their experience. However, in-person home deployment poses limitations around scalability and is not a feasible method in the context of the COVID-19 pandemic. The smart home research community is now facing the need to reshape and innovate research methods and design approaches. This study introduces a scalable smart home platform prototype that demonstrates possible solutions to address issues and limitations posed by the pandemic, such as improving package design, enabling user-driven installation, and facilitating remote evaluation and maintenance. The prototype uses off-the-shelf products with specially designed packaging to ensure interoperability as well as ease of shipping and installation. In this study, the prototype kits were shipped to participants' homes to understand and evaluate user perceptions and experiences around installation and initial use. Responses to a post-installation questionnaire and remote monitoring of system status showed that the participants easily completed their self-installation of the prototype without any on-site support. The study also showed potential for a scenario-based evaluation of the prototype using a remote, contactless research procedure.

References

[1]
Noura Abdi, Xiao Zhan, Kopo M Ramokapane, and Jose Such. 2021. Privacy Norms for Smart Home Personal Assistants. In Proceedings of the 2021 CHI Conf. on Human Factors in Computing Systems. 1--14.
[2]
Sami Abu-El-Haija, Nisarg Kothari, Joonseok Lee, Paul Natsev, George Toderici, Balakrishnan Varadarajan, and Sudheendra Vijayanarasimhan. 2016. Youtube-8m: A large-scale video classification benchmark. arXiv preprint arXiv:1609.08675 (2016).
[3]
Mohammad Arif Ul Alam, Nirmalya Roy, and Archan Misra. 2019. Tracking and Behavior Augmented Activity Recognition for Multiple Inhabitants. IEEE Transactions on Mobile Computing (2019).
[4]
Samaneh Aminikhanghahi and Diane J Cook. 2019. Enhancing activity recognition using CPD-based activity segmentation. Pervasive and Mobile Computing, Vol. 53 (2019), 75--89.
[5]
Noah Apthorpe, Yan Shvartzshnaider, Arunesh Mathur, Dillon Reisman, and Nick Feamster. 2018. Discovering smart home internet of things privacy norms using contextual integrity. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Vol. 2, 2 (2018), 1--23.
[6]
J Arunvivek, S Srinath, and MS Balamurugan. 2015. Framework development in home automation to provide control and security for home automated devices. Indian Journal of Science and Technology, Vol. 8, 19 (2015).
[7]
Amine Lotfi Bourbia, Heesuk Son, Byoungheon Shin, Taehun Kim, Dongman Lee, and Soon J Hyun. 2016. Temporal dependency rule learning based group activity recognition in smart spaces. In 2016 IEEE 40th Annual Computer Software and Applications Conf., Vol. 1. IEEE, 658--663.
[8]
Serge Thomas Mickala Bourobou and Younghwan Yoo. 2015. User activity recognition in smart homes using pattern clustering applied to temporal ANN algorithm. Sensors, Vol. 15, 5 (2015), 11953--11971.
[9]
AJ Bernheim Brush, Bongshin Lee, Ratul Mahajan, Sharad Agarwal, Stefan Saroiu, and Colin Dixon. 2011. Home automation in the wild: challenges and opportunities. In proceedings of the SIGCHI Conf. on Human Factors in Computing Systems. 2115--2124.
[10]
Paulo Carreira, S'ilvia Resendes, and André C Santos. 2014. Towards automatic conflict detection in home and building automation systems. Pervasive and Mobile Computing, Vol. 12 (2014), 37--57.
[11]
Nico Castelli, Corinna Ogonowski, Timo Jakobi, Martin Stein, Gunnar Stevens, and Volker Wulf. 2017. What Happened in my home? An end-user development approach for smart home data visualization. In Proceedings of the 2017 CHI Conf. on Human Factors in Computing Systems. 853--866.
[12]
Diane J Cook, Aaron S Crandall, Brian L Thomas, and Narayanan C Krishnan. 2012. CASAS: A smart home in a box. Computer, Vol. 46, 7 (2012), 62--69.
[13]
Karen L Courtney. 2008. Privacy and senior willingness to adopt smart home information technology in residential care facilities. (2008).
[14]
Prafulla N Dawadi, Diane J Cook, Maureen Schmitter-Edgecombe, and Carolyn Parsey. 2013. Automated assessment of cognitive health using smart home technologies. Technology and health care, Vol. 21, 4 (2013), 323--343.
[15]
Lucas DiCioccio, Renata Teixeira, and Catherine Rosenberg. 2013. Measuring home networks with homenet profiler. In International Conf. on Passive and Active Network Measurement. Springer, 176--186.
[16]
Shabnam FakhrHosseini, Chaiwoo Lee, and Joseph F Coughlin. 2020. Home as a Platform: Levels of Automation for Connected Home Services. In International Conf. on Human-Computer Interaction. Springer, 451--462.
[17]
Shuo Feng, Peyman Setoodeh, and Simon Haykin. 2017. Smart home: Cognitive interactive people-centric Internet of Things. IEEE Communications Magazine, Vol. 55, 2 (2017), 34--39.
[18]
Andrej Grgurić, Miran Movs mondor, and Darko Huljenić. 2019. The SmartHabits: an intelligent privacy-aware home care assistance system. Sensors, Vol. 19, 4 (2019), 907.
[19]
Sylvain Hallé, Sébastien Gaboury, and Bruno Bouchard. 2016. Towards user activity recognition through energy usage analysis and complex event processing. In Proceedings of the 9th ACM International Conf. on PErvasive Technologies Related to Assistive Environments. 1--8.
[20]
Kamil Hawdziejuk and Ewa Grabska. 2017. Cooperation of agents in the agent system supporting smart home control. In International Conf. on Cooperative Design, Visualization and Engineering. Springer, 57--64.
[21]
Chen-Yu Hsu, Rumen Hristov, Guang-He Lee, Mingmin Zhao, and Dina Katabi. 2019. Enabling identification and behavioral sensing in homes using radio reflections. In Proceedings of the 2019 CHI Conf. on Human Factors in Computing Systems. 1--13.
[22]
Yang Hu, Dominique Tilke, Taylor Adams, Aaron S Crandall, Diane J Cook, and Maureen Schmitter-Edgecombe. 2016. Smart home in a box: usability study for a large scale self-installation of smart home technologies. Journal of reliable intelligent environments, Vol. 2, 2 (2016), 93--106.
[23]
Danny Yuxing Huang, Noah Apthorpe, Frank Li, Gunes Acar, and Nick Feamster. 2020. Iot inspector: Crowdsourcing labeled network traffic from smart home devices at scale. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Vol. 4, 2 (2020), 1--21.
[24]
Timo Jakobi, Gunnar Stevens, Nico Castelli, Corinna Ogonowski, Florian Schaub, Nils Vindice, Dave Randall, Peter Tolmie, and Volker Wulf. 2018. Evolving needs in iot control and accountability: A longitudinal study on smart home intelligibility. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Vol. 2, 4 (2018), 1--28.
[25]
Taehun Kim, Junsung Lim, Heesuk Son, Byoungheon Shin, Dongman Lee, and Soon J Hyun. 2017. A multi-dimensional smart community discovery scheme for IoT-enriched smart homes. ACM Transactions on Internet Technology (TOIT), Vol. 18, 1 (2017), 1--20.
[26]
Wilhelm Kleiminger, Christian Beckel, Thorsten Staake, and Silvia Santini. 2013. Occupancy detection from electricity consumption data. In Proceedings of the 5th ACM Workshop on Embedded Systems For Energy-Efficient Buildings. 1--8.
[27]
Narayanan C Krishnan and Diane J Cook. 2014. Activity recognition on streaming sensor data. Pervasive and mobile computing, Vol. 10 (2014), 138--154.
[28]
Alex Krizhevsky, Vinod Nair, and Geoffrey Hinton. [n.d.]. CIFAR-100 (Canadian Institute for Advanced Research). ( [n.,d.]). http://www.cs.toronto.edu/ kriz/cifar.html
[29]
Josephine Lau, Benjamin Zimmerman, and Florian Schaub. 2018. Alexa, are you listening? Privacy perceptions, concerns and privacy-seeking behaviors with smart speakers. Proceedings of the ACM on Human-Computer Interaction, Vol. 2, CSCW (2018), 1--31.
[30]
Thai Le, Blaine Reeder, Daisy Yoo, Rafae Aziz, Hilaire J Thompson, and George Demiris. 2015. An evaluation of wellness assessment visualizations for older adults. Telemedicine and e-Health, Vol. 21, 1 (2015), 9--15.
[31]
Yann LeCun and Corinna Cortes. 2010. MNIST handwritten digit database. http://yann.lecun.com/exdb/mnist/. (2010). http://yann.lecun.com/exdb/mnist/
[32]
Chaiwoo Lee and Joseph F Coughlin. 2015. PERSPECTIVE: Older adults' adoption of technology: an integrated approach to identifying determinants and barriers. Journal of Product Innovation Management, Vol. 32, 5 (2015), 747--759.
[33]
Chaiwoo Lee, John Rudnik, Shabnam Fakhrhosseini, Sheng-Hung Lee, and Joseph F. Coughline. 2020. Development of data-based personas for user-centered design of the connected home. In 22nd DMI: Academic Design Management Conf. Impact the Future by Design .
[34]
Junsung Lim, Heesuk Son, Byoungheon Shin, and Dongman Lee. 2016. CASPRE: A context-aware standby power reduction scheme for household appliances. In 2016 IEEE International Conf. on Pervasive Computing and Communication Workshops (PerCom Workshops). IEEE, 1--6.
[35]
Sebastian Lühr, Geoff West, and Svetha Venkatesh. 2007. Recognition of emergent human behaviour in a smart home: A data mining approach. Pervasive and Mobile Computing, Vol. 3, 2 (2007), 95--116.
[36]
Davit Marikyan, Savvas Papagiannidis, and Eleftherios Alamanos. 2019. A systematic review of the smart home literature: A user perspective. Technological Forecasting and Social Change, Vol. 138 (2019), 139--154.
[37]
Caroline Lancelot Miltgen and Dominique Peyrat-Guillard. 2014. Cultural and generational influences on privacy concerns: a qualitative study in seven European countries. European journal of information systems, Vol. 23, 2 (2014), 103--125.
[38]
Maurice Mulvenna, William Carswell, Paul McCullagh, Juan Carlos Augusto, Huiru Zheng, Paul Jeffers, Haiying Wang, and Suzanne Martin. 2011. Visualization of data for ambient assisted living services. IEEE Communications Magazine, Vol. 49, 1 (2011), 110--117.
[39]
Ehsan Nazerfard and Diane J Cook. 2015. CRAFFT: an activity prediction model based on Bayesian networks. Journal of ambient intelligence and humanized computing, Vol. 6, 2 (2015), 193--205.
[40]
Tuan Anh Nguyen and Marco Aiello. 2013. Energy intelligent buildings based on user activity: A survey. Energy and buildings, Vol. 56 (2013), 244--257.
[41]
Helen Nissenbaum. 2020. Privacy in context .Stanford University Press.
[42]
Fco Ordó nez, Paula De Toledo, Araceli Sanchis, et al. 2013. Activity recognition using hybrid generative/discriminative models on home environments using binary sensors. Sensors, Vol. 13, 5 (2013), 5460--5477.
[43]
Eunil Park, Yongwoo Cho, Jinyoung Han, and Sang Jib Kwon. 2017. Comprehensive approaches to user acceptance of Internet of Things in a smart home environment. IEEE Internet of Things Journal, Vol. 4, 6 (2017), 2342--2350.
[44]
Christopher Pereyda, Nisha Raghunath, Bryan Minor, Garrett Wilson, Maureen Schmitter-Edgecombe, and Diane J Cook. 2019. Cyber-physical Support of Daily Activities: A Robot/Smart Home Partnership. ACM Transactions on Cyber-Physical Systems, Vol. 4, 2 (2019), 1--24.
[45]
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei. 2015. ImageNet Large Scale Visual Recognition Challenge. International Journal of Computer Vision, Vol. 115, 3 (2015), 211--252. https://doi.org/10.1007/s11263-015-0816-y
[46]
Heesuk Son, Jeongwook Park, Hyunju Kim, and Dongman Lee. 2019. Distributed Multi-Agent Preference Learning for An IoT-enriched Smart Space. In 2019 IEEE 39th International Conf. on Distributed Computing Systems (ICDCS). IEEE, 2090--2100.
[47]
Gina Sprint, Diane Cook, Roschelle Fritz, and Maureen Schmitter-Edgecombe. 2016. Detecting health and behavior change by analyzing smart home sensor data. In 2016 IEEE International Conf. on Smart Computing. IEEE, 1--3.
[48]
Yonglong Tian, Guang-He Lee, Hao He, Chen-Yu Hsu, and Dina Katabi. 2018. RF-based fall monitoring using convolutional neural networks. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Vol. 2, 3 (2018), 1--24.
[49]
Darpan Triboan, Liming Chen, Feng Chen, and Zumin Wang. 2017. Semantic segmentation of real-time sensor data stream for complex activity recognition. Personal and Ubiquitous Computing, Vol. 21, 3 (2017), 411--425.
[50]
Charles Truong, Laurent Oudre, and Nicolas Vayatis. 2020. Selective review of offline change point detection methods. Signal Processing, Vol. 167 (2020), 107299.
[51]
Tim LM van Kasteren, Gwenn Englebienne, and Ben JA Kröse. 2011. Human activity recognition from wireless sensor network data: Benchmark and software. In Activity recognition in pervasive intelligent environments. Springer, 165--186.
[52]
Tinghui Wang and Diane J Cook. 2020. sMRT: Multi-Resident Tracking in Smart Homes with Sensor Vectorization. IEEE Transactions on Pattern Analysis and Machine Intelligence (2020).
[53]
Diana Yacchirema, Jara Suárez de Puga, Carlos Palau, and Manuel Esteve. 2018. Fall detection system for elderly people using IoT and big data. Procedia computer science, Vol. 130 (2018), 603--610.
[54]
Surong Yan, Kwei-Jay Lin, Xiaolin Zheng, and Wenyu Zhang. 2019. Using latent knowledge to improve real-time activity recognition for smart IoT. IEEE Transactions on Knowledge and Data Engineering, Vol. 32, 3 (2019), 574--587.
[55]
Mingmin Zhao, Fadel Adib, and Dina Katabi. 2016. Emotion recognition using wireless signals. In Proceedings of the 22nd Annual International Conf. on Mobile Computing and Networking. 95--108.
[56]
Serena Zheng, Noah Apthorpe, Marshini Chetty, and Nick Feamster. 2018. User perceptions of smart home IoT privacy. Proceedings of the ACM on Human-Computer Interaction, Vol. 2, CSCW (2018), 1--20.
[57]
Jia Zhou, Pei-Luen Patrick Rau, and Gavriel Salvendy. 2012. Use and design of handheld computers for older adults: A review and appraisal. International Journal of Human-Computer Interaction, Vol. 28, 12 (2012), 799--826.
[58]
A Leah Zulas, Aaron S Crandall, and Maureen Schmitter-Edgecombe. 2014. Caregiver needs from elder care assistive smart homes: Children of elder adults assessment. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, Vol. 58. SAGE Publications Sage CA: Los Angeles, CA, 634--638.

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Proceedings of the ACM on Human-Computer Interaction
Proceedings of the ACM on Human-Computer Interaction  Volume 6, Issue CSCW1
CSCW1
April 2022
2511 pages
EISSN:2573-0142
DOI:10.1145/3530837
Issue’s Table of Contents
This work is licensed under a Creative Commons Attribution International 4.0 License.

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 April 2022
Published in PACMHCI Volume 6, Issue CSCW1

Check for updates

Author Tags

  1. case study
  2. pandemic
  3. research method design
  4. scalability
  5. smart home
  6. user experience

Qualifiers

  • Research-article

Funding Sources

  • MIT AgeLab C3 Connected Home Logistics Consortium

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 432
    Total Downloads
  • Downloads (Last 12 months)154
  • Downloads (Last 6 weeks)24
Reflects downloads up to 16 Feb 2025

Other Metrics

Citations

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Login options

Full Access

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media