This is the third post in my series on the Top Challenges to Successful IoT Initiatives — And How to Overcome Them. In my previous post, What is Pairing / Association of IoT Devices?, we explored what association (sometimes called pairing) means and why this is such a critical piece of IoT. The power of IoT lies in mirroring the physical world in digital form, which is accomplished through sensors that collect data from and about physical things. However, this means that we need to know that this sensor corresponds to this thing in the physical world, which is accomplished through the process of association.
Association can be manual or can be automatic, and it can be performed only once or may need to be performed multiple times. These two dimensions give us a total of four categories for which I’ll provide examples, challenges, and how to overcome them below.
Since association is quite common in asset tracking use cases, I’ll be featuring that use case as the underlying example in this post.
The vast majority of use cases will fall into this category, in which there's some manual effort required to associate one or more sensors to a given thing, but this association only needs to be performed once.
An example of this can be found in the smart boating solution we’ve built for Siren Marine. Siren Marine provides the MTC device to boat owners which allows them to track their boat’s position and monitor bilge level, high water, and engines. When customers sign up to a subscription for Siren Marine, they’re able link the MTC device to their account by manually entering the serial number of the device, thus associating it to their boat.
Another IoT solution we’ve worked on involves installing solar panels onto trucks. These solar panels store energy throughout the day and can be used to power subsystems within the truck (such as A/C) when the truck isn’t being driven, helping to reduce fuel consumption and lower costs. Paid-installers install the solar panels and other sensors onto the trucks using a setup app, into which they manually enter information such as the specs of the sensors and where those sensors are placed on the truck.
While the association is performed by both end-users and paid-installers respectively, in both use cases there is manual effort required for association but then the devices and sensors remain on the boat/truck for an extended period of time without being removed and placed on another boat/truck.
Since association is one-time, the challenges faced for this category are not that significant in aggregate. However, by nature of being a manual process there are still a few challenges to consider:
The answer is simple, although that doesn’t make it easy: Do everything you can to reduce the burden placed on the person associating. Preclude the possibility of human error. Here are some examples of how you might accomplish that:
This category comes into play for use cases that involve a rotating set of things that you’re tracking or monitoring, such as inventory: vehicles, medical assets, or any number of relatively high-value assets that come in and out of a given property. As IoT solutions continue to decrease in cost, the set of viable things to track will increase, but for now these use cases tend to focus on high-value assets for which the cost-to-track is justified.
An example of this could include inventory tracking in a warehouse setting. To track inventory as it enters the warehouse and moves throughout, sensors to enable indoor locationing are placed on each piece of inventory as it enters the property and then taken off when the inventory leaves.
This use case therefore involves manual, repeated association because there's manual effort required in the association process (i.e. scanning the barcode of the sensor and scanning the barcode of the piece of inventory) and because the same sensor will be placed on many pieces of inventory over the course of its life, meaning association will need to be repeated over and over.
This category is one of the most challenging because it contains all of the challenges outlined above for manual, one-time associations but the degree of challenge is multiplied many times by the number of associations that need to be performed. So both operational overhead and human error, as detailed above, apply here too but with higher impact.
In addition, there are two new challenges that arise for this category.
Manual, repeated associations require that the sensors be transferred from one thing to another with relative ease. But this ease of transferring also means that the sensor isn’t intrinsically tied to the asset, which opens up the possibility that association is skipped for a given asset. This becomes particularly challenging if assets can enter a property in different ways. In the warehouse setting, for example, inventory might sometimes be staged before being stored and sometimes stored directly upon arriving. This variance in process can lead to inventory slipping through the cracks without sensors being associated consistently.
Missing associations can become extremely problematic. If the sensor you’re using to track a given asset isn’t placed on an asset, how would you know? You could reconcile your inventory numbers with the number of sensors associated to assets to identify a gap, but now you have to spend a lot of effort tracking down those assets without associated sensors. Why? Well, because by definition they don’t have the sensor to track them!
All of the recommendations in the above category apply here too, so I won’t reiterate them. But for this new challenge of missed associations, here’s what you can do:
Associations that fall into this category are those for which the sensors are built directly into the thing in question. The association is automatic because the sensors are intrinsically tied to the thing and this only occurs once—when the thing is built. An example in this category would be autonomous vehicles. Autonomous vehicles require many sensors to function, but all of these sensors are built directly into the vehicle itself and are therefore automatically associated to that vehicle.
As I was creating these different categories as a framework for conceptualizing association, I struggled with this category the most. In a way, this category doesn’t really exist. IoT represents systems of systems, and in this case it’s somewhat meaningless to talk about the sensors making up the system of an autonomous vehicle since they’re all integrated. The interesting thing to focus on is instead the autonomous vehicle itself. When focusing on the autonomous vehicle, you can then ask more useful questions. For example, how might the vehicle be associated to a person or a given company (e.g. a fleet management company)? But if this is the focus, now we’ve moved into one of the other 3 categories.
My thinking on these topics is constantly evolving, so if you’ve encountered better examples for this category or if you think the framework could be improved, please let me know below!
If you’re in the category of manual, repeated association, then this category represents the holy grail. By making the association automatic, you can sidestep most of the challenges detailed above (e.g. human error).
As far as examples, unfortunately I can’t share anything concrete right now because the solutions we’ve worked on that would provide the best examples are currently under NDA. At a high level though, this category will almost always involve assets that have a digital component into which you can plug the sensor, allowing the sensor to draw data from the asset and therefore automatically self-associate.
The major challenge here is technological; is it even possible to automatically associate the sensor to the thing for this particular use case? In many cases, the answer is no.
I have a few topics in mind for my next post, but this series is ultimately meant to be helpful to you, the reader! So if there’s a particular challenge that you’re facing or that you’d like me to explore, please let me know, and I’ll make sure to prioritize it. Just click the button below and include your suggestion in the "How can we help?" field.
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