In 1999 Kevin Ashton, then at P&G, coined the term ‘Internet of Things’. It s a new term, but not a new operation. It was known as pervasive computing, ubicomp, and ambient intelligence. These iterations could not make their demos and prototypes real as until the 90s database storage was too expensive. It is the Cloud, operational from 2000s, that enables #IoT.
In 2003 I understood it like this:
Buildings, cars, consumer products, and people become information spaces by transmitting all kinds of data through Radio Frequency Tags that are rapidly replacing the barcode. We are entering a land where the environment has become the interface, where we must learn anew how to make sense. Making sense is the ability to read data as data and not noise.
Still this is the challenge we face today. How to make sense of big and small data? What is the balance between semi-autonomous decision making and human idiosyncratic insight, intuition and oversight into real everyday conditions?
What becomes the toplevel skill in this environment? Serendipity used to be an interpretative tool, the skill to lay bare hidden connections. Now the ability to read data as data has become the top level skill. How else are you going to make sense of the serendipity that is scripted into your profiling strategies? How do you differentiate between content and context is your content is inherently contextualized?
In 2016 an operational definition of Internet of Things (IoT) is the seamless data flow between the
- BAN (body area network): the ambient hearing aide, the smart t-shirt, Glass
- LAN (local area network): the smart meter as a home interface
- WAN (wide area network): Telematics, ITS, Connected Car
- VWAN (very wide area network): the smart city as e-gov services everywhere no longer tied to physical locations
Whoever ensures traceability, sustainability and security linking up the gateways is able to offer the best possible feedback on physical and mental health, the best possible household decisions based on real time monitoring for resource allocation, the best possible decision making based on real time data and information from open sources and the best possible alignments of local energy providers with the global potential of wider communities.
Products are gateways linking up the networks.
Google has the Glass and the Lens. You go home and synch your data into the Nest. Google had a Power-meter, but that did not get traction. Then you go to your car. A Google car. Or as Google is in Youtube and in several automotive associations. So you synch your data from your health and home into the car. You are always within the Google Cloud. For the next hub, the smart city, Google is in libraries, open data projects and partnering wisely with smart city infrastructure providers.
Every new set of techniques brings forth its own literacy:, the deliberate attempt of a technology to disappear as technology, implies that designers not only produce new products but also the process itself. If you want to play in IoT you need a system perspective.
Sure, this is hard.
When Captain Cook sailed into Botany Bay Aborigines kept fishing. They did not see a boat. The 'Endeavour' was too big and too strange to be a boat. To them it was an island. Only when Cook lowered a small boat did they react. They attacked immediately.
This is how we react to ontological change, deep change that shocks our belief in reality. We keep shifting our worries that something might be wrong into more rigid old patterns of what is real, what is true and what is normal.
We like the keep things as they are.
In our current architectures we are used to dealing with three groups of actors: citizens/endusers; industry/subject matter experts (sme); and those involved in governance/legal matters. These all are characterized by certain qualities.
In our current models and architectures we build from and with these actors as entities in mind. The data flow of IoT will engender new entities consisting of different qualities taken from the former three groups diminishing the power of the traditional entities.
In this new conceptual space you have to build new notions of privacy (privacies), security (securities), assets, risks and threats, business models and personal and company goals.