One way to classify an IoT System is by where you find them.
We can have IoT in the Home, Shops, Workplaces, Hospitals, Factories, Cities, Hotels, Amusement Parks, Roads, Airports, Schools, Universities and even in Outer Space! Accordingly we have the so-called Smart: Home, City, Utilities, Retail, Grids, Buildings, Offices, Supply Chain, Farming; plus a host of other industrial application areas including Industrial Internet, and in the consumer marketplace Wearables; plus Connected: Health, Car etc.
Another way is to distinguish IoT systems is in terms of technology employed.
In this respect, it is clear is that many new technologies are emerging—the same being ones that could potentially be applied to many of these application areas. Indeed, technology is evolving at such a rapid rate that it is valid to speak of a new era in which everything is being instrumented and connected for control, data-logging and real-time collaborative purposes.
In summary, the changing nature of the technological landscape will create a number of seismic changes to the ways in which we will live, work and play in the future—and it is possible to identify key formative and shaping factors in this new era as listed below.
Major changes and forces impacting the IoT technological landscape are as follows:
- Instrumenting the entire world (systems/machines are everywhere).
- Machines are becoming smaller and more powerful.
- Machines are receding into the background and becoming invisible!
- Machines collaborate with each other.
- Machines manage everything—every transaction / process.
- Everything comes with a chip inside—everything has intelligence.
- Every device is connected—for control, data logging, collaboration.
- Perpetual connectivity—everything is connected to a network.
- The Internet is becoming a data-source and less of a destination!
- The world is turning into data—and the machines know the data.
- Stuff just works or gets work done.
- Screens are not required for most tasks.
- What was human initiated is now machine dominated!
- Apps are becoming verbs—computer managed tasks just happen.
- Devices automatically discern human intent!
- Products self-work —they manage and switch themselves on/off alone.
Over and above this list of technological aspects of the IoT landcsape are 7 basic prinicples that encompass general IoT design principles:
IoT needs (general systems):
- Reliability—stable services
- Safety—not harmful to humans / ecosystems
- Security— no hacking / system exploits
- Privacy—personal / private data is secure
- Interoperability—works across brands
- Autonomy—no Internet and the system still works (within limits)
- Speed—fast and real-time response times, timely data-aggregation
Doubtless it is relatively easy to list all of the general requirements that our new wonder technology must be able to meet—but it is rather more difficult to design, build and operate these seemingly magical solutions with any degree of success.
IoT Design Principles
In fact, optimally managing and/or shaping the IoT design process (in general terms)—so far as this is possible—is the key goal of the present site. Towards this aim we have formulated an actual science of the Internet of Things; and our new science is grounded upon a single concept: that of Situated Intelligence.
Interestingly our concept of Situated Intelligence (see later article) is in close alignment with the Dr. Tom Bradicich, VP of Server Engineering at HP—who has generated a related analysis “The 7 Principles of the IoT”; named as:
- Big Analog Data (ref. MONITOR, INTEGRATE, ACT appropriately within the IoT Environment)—whereby the natural and physical world is/are fully/densely instrumented plus appropriately connected for DISTRIBUTED INTELLIGENCE;
- Perpetual Connectivity (ref. MONITOR, INTEGRATE, ACT)—IoT is always connected, system is always on and working. Likewise problems are self-reported, and fixes are pushed automatically, maintenance is semi-automatic—upgrades, fixes pushed instantly as needed, plus keep/motivate everyone informed—that is keep people/employees/users in the design/build/operation loop(s)—and thus create IoT devices with solution space(s) that are closely matched to problem space(s);
- Really Real-Time (ref. MONITOR, INTEGRATE, ACT)—for IoT real-time actually begins back at the IoT Thing itself—at the sensor or the moment the data is acquired—ergo we blend the world of operational technology (OT), sensors, and data measurement with the world of IT;
- Immediacy Versus Depth (ref. MONITOR, INTEGRATE, ACT)—there is always a trade-off between speed and depth; but it is better (in general) to compute everything at the first instant that it can be—and so to push data processing to the edge (see point 5);
- Compute shift to Data Source (ref. MONITOR, INTEGRATE, ACT)—compute moves closer to the source of data; we wish to avoid transferring large amounts of unnecessary data around the IOT system – but rather to send small, narrowly focussed data sets on a just-in-time basis (see point 6 below);
- The Next ‘V’ (ref. MONITOR, INTEGRATE, ACT)—Big data is commonly characterised by the infamous “V’s”— Volume, Velocity, Variety, and Value. With IOT there is a fifth “V”—Visibility. (Visibility refers to the benefit afforded by not having to transfer large amounts of data to remote people or locations). Ergo we have the concept of access to data and applications “independent of time and place”. Mark Templeton, CEO of Citrix, adds a third independence: “independence of device”.
The upshot of Tom’s analysis of the rapidly evolving IoT field is that the IoT is driving a new set of five key design requirements:
- Big Analog Data—capture/process/act-on/report as much relevant data as possible—in relation to relevant problem/solution spaces;
- Perpetual Connectivity—core activities / services are never interrupted;
- Real time reporting/control/action—appropriate data-processing / data-aggregation, leading to optimal problem resolution as required;
- Visibility of Services—instrumented objects have real-time visibility system-wide; henceforth distributed computing is enabled;
- Objects self-manage/self-analyse/self-report—autonomous operations with escalation (to central/distributed control node(s)).
Ergo, the Internet of Things (IOT) is a nexus of devices and services that allow for data exchange and appropriate data-analysis/data-processing no matter where the end-user (human and/or machine) may be located. The author calls this ‘Situated Intelligence‘—whereby a smart device knows WHO/WHAT needs WHICH capability WHERE, WHEN and HOW. Note that the Who/What (the requesting actor), Which (requested data/capability), When (normally ASAP) are normally known—and all that remains is WHERE AND HOW.
Henceforth, by means of a detailed ontological analysis—we have defined in general terms what the IoT subject area is all about. In other words we have specified all of the key features (that is goal-specific aims) that comprise this unique and complex domain of computing/instrumented technology. It only remains for us to delve into the identified areas in greater detail—and in order to see how these elements are built into real-world IoT systems and instrumented environments etc.
Why not join us now—as we embark on a fascinating journey into these topics in the hope of discovering in detail what the future world of IoT will be like.