How do system conceptual models work? This is all about having some notions of how the system works. Understanding a value proposition: what does it do, how does it work, and how do we use it. Connected products are usually more complex than simple non-connected products. E.g. if you look at a light bulb, it is connected to a receiver, connected to a switch, connected to the internet, connected to an app. Next to that, connectedness requires users to think about system models. Which bit does what? Where does code run? What fails/still works if connectivity is lost?

There is a distinction between the rules of operation when connected and controlled from the cloud to when the control is operating locally. In addition to price, aesthetics and features, customers have to understand how a product connects, operates, and whether that meets their needs. When you are buying lights, which used to be a simple thing, you now have to think how it all connects, and how well does this match your needs. For people, it is important to have this operational understanding and give users indications on whether something is connected (with functions in cloud) of disconnected, communicating (or not) and functioning locally. The alternative, and what probably is best, is to simplify the conceptual model: in the case of Starbucks that sometimes provides free coffee, the user perceives that a free coffee is being offered directly through their mobile phone, while in reality there is a system of recognition of the users’ telephone via a local beacon, connecting to a cloud processing the information before sending the coupon wirelessly back to the phone.

“The complexity of the system is presented as a simple function to the user. “ - Claire Rowland

The first aspect to discuss in this simplification of complexity is to distribute the functionality to suit the context of use, with nearly all interactions via smart phone apps and interactions mirrored on e.g. phone, thermostat or any interface that is function-related. Fitting better with people’s common assumptions and their everyday life. Would this integration happen in app, device, or both? The risk of making the wrong decision is that you may end up involving too many features within the same system. Would simplification result in minimal elegance, or would features be perceived as missing?

The second aspect that resolves system complexity is consistency. Users should not have to worry whether different wording, situations or actions across distributed interfaces mean different things. Consistency means making everything mean the same, using the same language. Give functions the same name and terminology. However different the UIs, same functions must have the same name. If you give different names to the same function, people may not understand. Follow device platform conventions and be true to the device A fake screen does not need a fake bezel. A thermostat does not have to pretend it’s an iPhone. Nest uses visual and audio cues to tie the thermostat to the function. One thing that does not need to be the same is the interaction architecture. The logical structure of UI features and controls is likely to be platform dependent.

“Users should not have to worry if words, situations or actions mean the same thing.”  - Jakob Nielsen 

The last aspect addressing this system complexity is continuity in the experience of cross device interactions. This is not about seamlessness. It often means handling interstitial states gracefully. Cross-device interactions won’t always be smooth and immediate. We expect switches to work directly: you press the switch and it turns on. Over a network, those things don’t necessarily happen at the same time. There are two ways of dealing with this. One is lying, and representing what the instruction could be representing. E.g. Instagram indicates you already liked something, when the system is still sending the signal. The second thing you can do is being really transparent: separating the confirmation of the action from the action itself, keeping the user openly informed about the real state of the application, even if it is still processing. When some devices only check into the network occasionally, there may be conflicting information about the status of the system. Data and actions may need to be time-stamped. But how acceptable is uncertainty? If you have a safety and critical need, you can’t accept uncertainty. It is interesting to be critical about the contexts of application and evaluate what to prioritize: precise but old data, or fuzzy but timely data?

Interestingly, even though there are many forms of data collection, most applications have limited diversity of output, essentially in light, sound and movement. Evolving in a world of full-scale connectedness of objects implies that we look beyond these traditional forms of output; a few strategies for new developments are recommended by Tina Aspiala, the creator of KnowCards:

• Combining various functions and capacities

• Think of unthinkable places

• Consider our native interfaces

• Induce new senses

• Develop new parts

• A future where things are a lot more human, tactile and polite

Internet of Things and the “smartification” of cities and public space

According to Ross Atkin, the integration of technology in everyday objects, as a cultural phenomenon, comes close to the principle of smartification of public space, and the ethical implications of politics and government involvement in the develop of smart cities. the problem with the school of smart city is that people can't opt out from using it. If we have an issue with privacy related with a consumer product, we can opt for not having it in our house. The same is not possible when talking about public space, because once governments decide for implementation, the only way of avoiding it would be to leave the city.

[su_vimeo url="https://vimeo.com/148369907" width="900"] [/su_vimeo]

In this perspective, the problematic of cities’ smartification should use digital technology to solve problems experienced by citizens. Services and applications are built around the needs of the people whose problems they are trying to solve, and should be as simple as they can be and easy to explain. That has benefits in terms of reliability and transparency. What it is, what it does, and why do you got it. On the other hand, and addressing the issue of data collection such applications should collect as little data as required to solve the problem at hand for the citizen. The cultural shift in this field implies, in its very essence, a shift to address people, the citizens, and their needs, rather than the IT companies and government officials.

"There is no logic that can be superimposed on the city. People make it, and it is to them, not buildings, that we must fit our plans.” - Jane Jacobs 1958

Notes:

• The organisation has made all the video recordings of all talks at the Thingscon's vimeo account.

• You can find the slides of the keynote speeches and workshops at the Thingscon's slideshare account.

• Finally, you can read the reports about ThingsCon here.