Attempting to Define "Internet of Things"
Attempting to Define "Internet of Things"
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How do you define the undefinable?
To start with. I want to call out that attempting to define “IOT” is like attempting to define “the cloud”. Over time, “cloud” has settled on a definition that revolved around a collection of attributes: scalable, self-service, pay for what you use, and internet accessible. These still fluctuated greatly, and to some degree were dependent on the viewpoint of the consumer of “cloud” based services. But it gave us a starting point.
Using that as an example, I think we could define IOT solutions as also requiring a set of attributes:
Things – A ‘thing’ is a specialized, autonomous piece of technology capable of performing an action, but does not possess a traditional human user interface. A phone or computer is a device. A security hand scanner, motion sensor, or even the GPS sensor in a phone could be considered a “thing”..
Data – Our things, being highly specialized, will have limited capabilities. But one of these will be the ability to report on the information they gather so something else can process the data, turning it into information. They *may* also be able to receive commands to alter their function (i.e. changing your sampling rate from 1s to 5s). In many case, we can likely expect both.
Connectivity – How that data moves in and out of “the things”, requires some type of connection. This could be a cellular network, location specific wi-fi, etc… In part, this refers to how the “things” interact or the data is gathered. The connection can be persistent (always on), or transient (on/off as required), but if you have to do stuff like plug a device into it or move data via USB or SD, we’re lacking the “internet” part of IOT. A big discussion point here is if the “thing” is directly connected, or requires assistance to connect (like the GPS sensors mentioned above).
Management – This attribute is how we track the “things”. Are they curated and highly managed (likely in a factory scenario). Or are they anonymous and unmanaged (open sourced climate telemetry gathering). This also covers attributes like how do I identify the device and separate it from “rogue” devices.
So with a set of initial attributes identified, the next step is to use them to define some scenarios.
A Factory Scenario
So Jason’s post calls out a manufacturing scenario. I’m careful to “a” scenario, because our definition above allows for a nearly infinite set of scenarios. But here’s one possibility: a single factory that makes widgets. For this scenario, we can identify the our IOT attributes.
The things: each piece of machinery has 3 sensors on it: power monitoring, pieces made, and operating temperature and one actuator: power control
Data: The sensors each capture a specific measurement every 1 second and report it every 5 seconds while the machine is running to a local controller.
Connectivity: The sensors area wired to a “controller” that’s mounted on the machine. This in turn is connected into the factory’s private wi-fi network. While the controller can take action on the data, it mostly just displays it and hands it back up to a central service on the network.
Management: When a machine is installed in the factory, there’s a step where the machine (and its sensors) are connected to the network, and “registered” with the factory’s services. Additionally, since the sensors are hard-wired to the machine “controller”, it has information about the sensors it can in turn share up to the factory services.
So we have a basic scenario that has all four attributes, and meets our basic criteria. The factory is capable of determining when the data is trending downward (perhaps power is increasing while pieces being produced is being reduced). It can then take action like telling the machine to shut down because a technician is on the way. We can also collect and trend the data, mining it over time.
But IOT also creates some common challenges.
Ingestion of telemetry: If I only have 100 machines, this isn’t a big deal. But what I’m in a scenario where I have several thousand or hundreds of thousands? How do I scale my factory services to ingest that many connections and messages?
Device Management: Sensors fail and have to get replaced. As machines fail, they may be parted out. So a sensor that fails may be replaced with a sensor that used to be on a different machine. So I constantly need to be able to track the relationships.
Connectivity: What happens if the factory wi-fi goes down? Or worse yet a visitor to the factory taps into the network and starts sending rogue messages that alter my factory data? What if they send commands to the machines that cause them to overheat?
It’s these challenges that all the vendors are racing to solve with their various IOT Solutions!
What are the solutions?
I recently saw slides from a session given by Alessandro Bassi at the M2M+ Industry Summary in Milano, Italy. In this session, he calls out that innovation for its own sake will usually fail. It needs to be supported by a good business model. So the vendors in this space are all attempting to offer their business solutions.
In some cases, these solution are highly targeted. The tech startup NEST, is a good example of this. It has a thing, the thing gathers data, it’s connected and transmits the data, and its managed (you register your device). In this case, the vendor is trying to solve a specific problem, driving down home energy costs, and marketing this solution to consumers is their business model.
In other cases, the solutions are industry focused. With the vendor providing a collection of services that work together in a more flexible way to help drive larger, more strategic initiatives. In the link I just shared, it’s a collection of solutions targeting hardware and software to help with factory scenarios like I listed above. This solution is positioned to organizations that are in that industry vertical, to address the requirements of that industry.
And lastly, we have services like the ones I’ve been working with lately; ISS, Service Bus, Project Orleans, and HDInsight. These are more building block oriented. They aren’t specific industry or even set of scenarios. They are meant to allow higher level, more encompassing solutions to be created. These get marketed to either software vendors looking to build our commercial or consumer solutions, or to organizations that need to build out customized solutions for internal use.
Each approach has pros and cons, but then they are also targeting a different business models. So it’s about picking the approach that best addresses your needs. Meanwhile, the vendors are all looking to capitalize on the market and find a way to sell their solution to solve the “IOT problem”.
Summary – have we accomplished anything?
This was the first time I’ve really put any of these thoughts down. Looking back over the typos and grammar errors, I have to ask if I’ve accomplished anything. I did set down a rough definition for what I think “IOT” is. This also allows me to call out some of the common challenges to related scenarios and ultimately even call out the types of solutions the industry is offering. So I guess you could say I have defined IOT.
But I can’t help and think the practical reality is more difficult. The definition of IOT will continue to evolve and there will always be shades of gray. So it’s important to keep in mind that different things to different people. With that in mind, I think I’ll stick to my “remain calm and ask questions” approach, and when someone comes to me with “an IOT scenario”, my first response will always be “so tell me about it”. The scenario and its challenges will always trump an arbitrary terminology definition. And in the end, it’s the solution and the business value that is brings that really matters more than the industry buzzword. Isn’t it?
Until next time!
Published at DZone with permission of Brent Stineman , DZone MVB. See the original article here.
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