The growing interest in the Internet of Things and in technological, connected, and computing-enhanced spaces such as smart homes (Figure 1), intelligent environments, and responsive environments connects interaction design more and more with architecture. Everyday spaces such as home environments are increasingly filled with computing and smart objects. This trend of ubiquitous computing, as envisioned and pioneered by Mark Weiser at Xerox PARC, has since worked as a basis for designing smart environments—across people, objects, and spaces. Many researchers have further investigated how the flows and patterns of activities in a space can guide the design of interactions with smart objects . In particular, the notion of place is used when spaces frame interactions through cultural values and behavioral expectations .
In designing smart homes, attention is often paid to the user experience and to the ways in which those environments can support the inhabitants’ daily activities. Furthermore, many smart objects aim to not only support but also capture awareness of and evoke reflections about user activities in domestic environments. For example, reflecting about activities that require reductions in energy or water consumption, or reflecting about food consumption in order to foster behavior changes toward healthier food choices. Although the purposes in those examples may differ, they share the same principle: Reflection can help people make better choices and change behaviors.
In this regard, Lars Hallnäs and Johan Redström’s slow technology is an approach that emphasizes the role of technology to foster moments of reflection—instead of efficiency in performance—in domestic environments . More recently, the HCI community has provided many experimental and speculative examples of smart devices that can support reflection in the home.
In his seminal work How We Think, John Dewey describes reflection as a deep consideration of experiences and actions in order to discover connections, that is, relations between things . Reflection demands time and continuity; it helps guide people to understand a situation deeply, allowing them to take careful and informed courses of action for change. Reflection as an activity is not only an individual and internal process; it also requires external stimuli: objects, other people, activities, and the environment (see, for example, ). Furthermore, in HCI, reflection refers to the action of thinking about the information provided by smart objects in order to capture awareness about an action and its consequences. Accordingly, reflection can become a valuable concept in the design of everyday smart objects embedded in place .
People not only think with objects, but they also often engage in an activity with an object, so reflection about an activity is connected to the smart object, the activity, and the place [7,8]. Consequently, designing for reflection about an activity requires consideration of the relations among those factors, which deal with the social, aesthetic, and technical interactions in a given environment .
To design effective smart objects that support reflection, we can learn from the relations among existing objects, activities, and environments. However, smart objects intended to evoke reflection about an activity are not always designed in relation to the spaces where people perform that activity. They may also not be the objects with which users interact during that activity in order to achieve a functional goal. For example, the Energy Orb is a smart object in the form of a glass ball that provides real-time data about energy consumption and energy price, enabling users to modify their energy usage. It communicates by glowing in different colors—green when the consumption and pricing are low, and red when the consumption and pricing are high. It is a calm ambient technology that requires no cognitive effort from users. At this time, the Energy Orb is not an object that is used during an activity; it does not demand any relationship with the activity and its place. Consequently, users may soon not pay much attention to it. There are many other smart objects on the market similar to the Energy Orb—for instance, Home Joule and Energy Joule—that are designed with the purpose of helping users save energy and money and also to capture awareness about their energy consumption (e.g., http://www.ambientdevices.com/).
While a few prototypes of smart objects (mostly from eco-feedback technologies) experiment with such relations in mind, many others do not. For example, we can consider two examples, both related to water consumption: an eco-feedback display  and Waterbot . While Froehlich et al.‘s eco-feedback display is not used in relation to any activity in which water is used, Arroyo et al.‘s Waterbot is actually installed and connected to the faucet, which is the object with which the user interacts during an activity such as hand washing (Figure 2).
Therefore, we need to consider that evoking reflection in users about an activity is appropriate when the user is:
- actually doing that activity,
- in the place where the activity is usually being done/has been done, and
- interacting with the objects and/or people involved in that activity.
In addition, smart objects in a space that aim to support reflection need to provide guidance and be persistent, instead of merely representing information.
This analysis may have some advantage for guiding the design of meaningful forms of interaction for reflection about an activity . It advises designers to first consider the activities that naturally occur in a given space and the objects and people involved in that activity, and then design smart objects that evoke reflection about that activity. Thus, for designing such smart objects, the key factor is the existing relations among the components of a space.
The components of a space include objects (smart, digitally enabled, or not), people, user activities, and the architectural structure of the space itself. Considering that these components are actually interconnected and related to one another, what is the design outcome? Is it the architectural space, the object for use in a particular environment, or the object in use for a particular activity? Or is it the relations among objects, people, and activities within an environment?
Having reflection about an activity—which is in relation with objects, activity, people, and space —as a design concept, it seems clear that we should actually design the relations among those components. However, in order to have a systematic approach and a clear idea about the outcome of design, we may focus on one component at time and then consider the relations around it.
For this article, I will start with the smart space, since it physically contains the other components, and then illustrate the relations within it. I will explore the three main relations, namely: 1) smart space-activity 2) smart space-objects and 3) smart space-people relations.
Smart space-activity relations. In this relation, a smart space becomes a “place” as it holds particular activities, cultural expectations, and definitions . For example, “home” is a private architectural space where people live their private lives, have personal relationships, and perform activities that are often distinct from those in their public or professional lives. Thus, the architectural space definition and meaning are closely related to the activities the user usually does in that space. For instance, considering the home as a smart space, a kitchen is defined as a place where people make food. Accordingly, there are tasks related to that place, such as cooking, boiling water, cutting vegetables, and so on. Those are activities that by definition occur in that specific place. Other examples are, for instance, sleeping and waking up in a bedroom or taking a shower in a bathroom. Thus, for example, in designing for reflection about the activity of taking a shower, the bathroom is the right place for evoking reflections about that activity.
Smart space-objects relations. According to the definition and meaning of the space, people engage in tasks in relation to objects, which are generally presented in that specific space. Considering a smart home as an example, in a kitchen we find pans and an oven; in a bedroom, we find a bed; and so on. So, for designing a smart object for reflection about the activity of sleeping, it seems appropriate to pick a preexisting object that supports that activity and other actions related to it. For example, Bonjour is a smart alarm clock that was designed to support the same user activity for which the original was invented: waking up on time. And for that reason, it is usually placed next to a bed in a bedroom (Bonjour startup: https://www.indiegogo.com/projects/bonjour-i-smart-alarm-clock-with-a-i-sleep-2#/). Bonjour is an AI conversational agent. It is connected to the weather forecast, iCal, Google calendar, Google maps, and traffic monitoring so it can adjust the wake-up time for a user if certain conditions are met. This alarm clock also supports good sleep, which is another activity naturally related to waking up on time! Thus, an alarm clock could become a smart object not only to support waking up on time and sleeping well, but also to evoke reflections on those activities for the user with the goal of improvement.
Smart space-people relations. Some places are for a specific person. For instance, when we call a specific place in our home “my room,” this actually means that place has been configured accordingly to my taste, my daily activities, and my things. When other people interact with that place, they may not fully recognize its whole structure and configuration. Alternatively, there are also spaces that are designed for social interactions, for example the dining area in a home environment, which structures configurations that are not specific to one person.
In our spaces, which are increasingly computational and intelligent, we use objects in our daily activities. Through this article, I sought to build upon existing bodies of knowledge that are well grounded in architecture and HCI. They suggest that we first observe the pattern of people’s activities and the objects of use in a space in order to design better and supportive architectural spaces, as well as to design better computing artifacts that can support user activities [1,8]. In this way, an architectural space becomes smart by supporting natural existing relations within it, such as relations among people, objects, activities, and the space itself. Further, considering these relations when designing smart objects to support reflection about an activity—instead of creating new objects and consequently new usage and interactions—is a valuable way of structuring the analysis of complex spaces . This is well grounded in theories (e.g., distributed cognition) that describe how people think with objects, and that reflection is distributed across people, objects, and spaces [7,8]. There are three main relations between the architectural space and other components in it: people, activities, and objects. Analyzing those relations becomes even more relevant as we increasingly consider reflection as a goal for design outcomes, especially for the design of smart and interactive artifacts .
5. Rogers, Y. A brief introduction to distributed cognition. 1997; http://mcs.open.ac.uk/yr258/papers/dcog/dcog-brief-intro.pdf
9. Froehlich, J. et al. The design and evaluation of prototype eco-feedback displays for fixture-level water usage data. Proc. of the SIGCHI Conference on Human Factors in Computing Systems. ACM, New York, 2012, 2367–2376.
10. Arroyo, E., Bonanni, L., and Selker, T. Waterbot: Exploring feedback and persuasive techniques at the sink. Proc. of the SIGCHI Conference on Human Factors in Computing Systems. ACM, New York, 2005, 631–639.
Maliheh Ghajargar is a Ph.D. candidate in the Department of Architecture and Design at Politecnico di Torino, Italy. She is currently a Ph.D. visiting student in the Department of Informatics at Umeå University, Sweden. The main area of her research is the design of reflective interaction between users and computer-enhanced artifacts. firstname.lastname@example.org
©2017 ACM 1072-5520/17/07 $15.00
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.
The Digital Library is published by the Association for Computing Machinery. Copyright © 2017 ACM, Inc.