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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.

1. Manual, One-Time Association

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.

Challenges

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:

  • Frustration for end-users: In the case of Siren Marine above, if the association process were to require a lot of work by the end-user, this could lead to customer dissatisfaction with the product, which isn’t a great initial impression when the product hasn’t even been used yet.
  • Operational overhead: In the case of the solar panels on trucks, if the association process were to require a lot of work by the paid-installers, this could result in significant operational overhead in, well, paying the installers.
  • Human error: For any use case that involves manual association, you leave open the possibility of human error. Incorrectly entering a serial number or a sensor spec could lead to issues and further frustration for whomever is performing the association.

How to Overcome

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:

  • Allow users to scan barcodes or QR codes instead of manually entering serial numbers. If you’ve built a mobile app for your use case, you can use the phone’s camera to scan a barcode, scan a QR code, or use optical character recognition (OCR). That being said, make sure to consider the environmental conditions under which association will be performed! Rain and snow can make it difficult to use a touch screen and bright sun overhead can make it difficult to see the screen.
  • Prompt the user during their setup process to enter the needed data. If a user logs in for the first time, don’t force them to search for where they need to enter the data (e.g. serial number) but instead prompt them immediately.
  • Include data validation to avoid human error. For example, you might have a list of all serial numbers of device sold, so you can validate that the serial number the user entered is a valid serial number.
  • Auto-populate data where you can. In the case of the solar panels, if there are a common set of sensors that are attached, then instead of forcing the paid-installers to manually enter the specs each time, you might include a dropdown of the common sensor options then auto-populate relevant data fields based on their selection.

2. Manual, Repeated Association

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.

Challenges

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.

  • Because sensors are getting placed on different assets, those sensors often need to rely on battery power (opposed to manual, one-time associations which often draw power from the thing to which the sensors are connected). Battery challenges can be extensive and nuanced, so I’ll actually be saving this for a dedicated post or two, stay tuned!
  • Mitigating missed associations is the second new challenge. For manual, one-time associations it’s very difficult to miss associating because associating is a necessary step of the process. That is, it would be very difficult for a paid-installer to forget to associate the sensors because that’s a key part of installation.

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!

How to Overcome

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:

  • Make sure there’s a way of identifying an issue in the first place. It’s likely that the organization in question already has a means of tracking their total inventory numbers before they got this shiny new IoT solution. If possible, create an automated way to flag if there is a discrepancy in the purported inventory numbers and the number of associated assets.
  • Put operational processes in place. Once you’ve identified a discrepancy, investigate what’s causing it. Is there another means by which assets can enter the property that circumvents the normal association process? Is there a hidden bug that’s preventing association? Is human error leading to issues? In many cases, you may be able to reduce the issues you discover with technology, but ultimately you’ll need to solve through operational processes.

3. Automatic, One-Time Association

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!

4. Automatic, Repeated Association

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.

What Challenges Are You Facing?

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.

Have Questions? Talk to an Expert

Calum McClelland

Calum is the Director of Projects at Leverege and graduated from Brown University in May 2016 with a major in Philosphy. Striving to change himself and the world for the better, Calum values active living, life-long learning, and keeping an open mind.

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