involvement before the deployment takes place. If it’s really not possible to have the participant supervise the setup, just be extra careful and ask if you’re not sure of something!

PRACTICALITIES

Getting there. You’ve done all the difficult preparation: You’ve found an exciting research idea; you’ve designed an extensive study to facilitate the idea; you’ve got the project ethically approved; you’ve built or programmed your hardware and software for deployment; and you’ve lined up the first household for study participation.

But have you thought about how you are going to get your deployment equipment into the participants’ home, alongside any extra items (e.g., multiway mains adaptor, a laptop for debugging) that you may need just in case? Such administrative thoughts hardly seem relevant when you’re in your research bubble, yet without such considerations the deployment may not happen at all. Can you get your hardware onto public transport, or do you need to take a car? If you need to return to the participants’ home with little notice, can you get there easily?

Can you park nearby? Will it take multiple trips between the household and the vehicle to carry all your equipment inside? Can you prevent your equipment from getting wet if it’s raining? These are just some of the situations you need to prepare for when doing household deployments.

Dangerous environments. Although your own home may be a safe haven, you may find the household of a participant to be a dangerous environment.

Accessing particular technology or
items within participants’ homes may
involve tricky maneuvers, such as
crawling under furniture or leaning
into tight spaces, that can lead to an
injury. As silly as it sounds, even just
walking around in a new, unfamiliar
environment while maintaining core
focus on the deployment can cause
havoc; for example, by banging your
head on low-hanging lamps and
knocking into other furniture you’re
not used to being around. You need to
consider your own health: For example,
the participant may smoke or their
furniture may be dusty; therefore
you may want to bring any necessary
medication. This is all assuming that
going to the participant’s house in the
first place is safe! Lone studies may
put yourself at risk by meeting an
unfamiliar person (or people) in their
private location. Ethics departments
often insist that you perform a checking-
in scheme (i.e., where you inform
another member of the research team
that you have arrived at, and departed
from, a household), yet the location of
participants’ homes may not permit
this if the mobile phone signal is poor or
even nonexistent. You may need to visit
locations in advance to see if there is a
phone signal, and, for extremely remote
locations, ensure you take a colleague
or rethink whether you can include this
household in your study.

Accessing IC T. We are all familiar with tangled wires behind a TV stand or sofa, not knowing the cables for the television from the ancient stereo system you used once in the ’90s. However, this can make it extremely difficult to identify which devices you are looking to monitor in households—in one household, we unknowingly monitored the wrong device. The tangled wires make it challenging to identify individual devices, and in some instances you may not realize your mistake until the end of the study. Many times, participants themselves cannot make sense of the tangle. Alongside this, it can also be a challenge to physically access the devices you wish to monitor, and may often involve moving heavy or delicate furniture to reach sockets and cables. It may be worth asking the participant to move furniture or fish out wires for you, if they are capable, just to be on the safe side.

 

ACKNOWLEDGMENTS

We thank the ESPRC (grant numbers: W95738G; and EP/K011723/1 as part of the Research Councils UK Energy Programme) and the EDF (as part of the R&D ECLEER Programme) who funded this research. As the article is based on our experiences of deployments and those reported in prior publications, there is no data to make publicly available.

 

Endnotes

1. Kimel, J. and Lundell, J. Exploring the
nuances of Murphy's Law—long-term
deployments of pervasive technology into
the homes of older adults. Interactions 14, 4
(2007), 38–41.

2. Gaver, W., Sengers, P., Kerridge, T., Kaye, J., and Bowers, J. Enhancing ubiquitous computing with user interpretation: Field testing the home health horoscope. Proc. of the SIGCHI Conference on Human Factors in Computing Systems. ACM, New York, 2007, 537–546.

3. Hnat, T. W., Srinivasan, V., Lu, J., Sookoor, T.I., Dawson, R., Stankovic, J., and Whitehouse, K. The hitchhiker's guide to successful residential sensing deployments. Proc. of the 9th ACM Conference on Embedded Networked Sensor Systems. ACM, New York, 2011, 232–245.

4. Tolmie, P., Crabtree, A., Egglestone, S., Humble, J., Greenhalgh, C., and Rodden, T. Digital plumbing: The mundane work of deploying UbiComp in the home. Personal and Ubiquitous Computing 14, 3 (2010), 181–196.

5. Doyle, J., Bailey, C., Scanaill, C. N., and van den Berg, F. Lessons learned in deploying independent living technologies to older adults’ homes. Universal Access in the Information Society 13, 2 (2014), 191–204.

6. Goulden, M., Greiffenhagen, C., Crowcroft, J., McAuley, D., Mortier, R., Radenkovic, M., and Sathiaseelan, A. Wild interdisciplinarity: Ethnography and computer science. International Journal of Social Research Methodology 20, 2 (2017), 137–150.

 

Helena Tendedez is a computer science Ph.D. student at Lancaster University, specializing in digital health and human-computer interaction. She completed her bachelor’s degree in computer science in 2015. Her doctoral research involves working with clinicians and industry partners to unite healthcare professionals with the data they need for enhanced decision making. → [e-mail]

Kelly Widdicks is a computer science Ph.D. student at Lancaster University. Her research concerns the demand for data, and its consequent energy consumption, associated with user practices. In the next stage of her research, she is looking to explore effective interventions for data demand reduction in everyday life. → [e-mail]

Mike Hazas is a reader in the School of Computing and Communications at Lancaster University, working at the confluence of computer science (Ph.D., University of Cambridge) and sociology (B. A., Lancaster University). His past work has included interventions in thermal comfort, practices around food and cooking, and on-demand streaming and social networking. → [e-mail] DOI: 10.1145/3292019 COPYRIGHT HELD BY AUTHORS INTERACTIONS.ACM.ORG JANUARY–FEBRUARY 2019 INTERACTIONS 57