IoT offers many possibilities, but where do you start?

C# Azure Edge Internet of Things (IoT) Industrial IoT Hive

It has been predicted for years that IoT- short for (the) Internet of Things- faces a promising future. However, if you keep saying that for long enough – and hear it over and over again – eventually it’s going to become nothing more than a meaningless mantra, a kind of promising football player who never comes off the bench to prove his skills. In some cases, things can take some time. It has been said that many new technologies are overestimated in the short term, yet underestimated in the long term.

The perfect conditions for IoT

With that being said, the tide for IoT is really turning. The combination of (private) 5G, cheap IoT devices, and the cloud’s scalability, create new possibilities that are interesting for many different companies and sectors. Via IoT it is possible to collect data and use smart algorithms to process new insights that until recently seemed impossible. Like predicting the maintenance of a production line in a factory, managing office parking spaces, or monitoring warehouse stocks, and doing this all remotely.

IoT challenges

It is important to realize that working with IoT requires new skills and creates a potential set of new challenges:

  • IoT has a piece of software by default. With a camera, for example, you want to have the option to turn it on and off, to change the position, or even to record only if there is a certain event. Like a fire or a burglar in the picture.
  • The software for IoT works differently than that of a website. For example, with a site you don’t want a continuous loop where data is processed in real-time, but with IoT you do. It requires a different way of programming, which creates a threshold to really get started with IoT. IoT security also works differently, with different protocols and more focus on physical protection.
  • Managing IoT- especially with key utilities – is still often done per device. But what if you have 1,000 at some point? Or perhaps they are spread out in many different locations. Do you have time and resources to manage every device if you want to push an update?

Hive platform

At LINKIT we have developed the Hive platform, with which we aim to make IoT solutions simpler and more accessible for companies by removing many of these mentioned barriers. Hive is a partial SaaS solution that allows you to manage your IoT devices on a single platform. In this setup, you’ll store all the data locally. The entire platform is made up of several modules: the Hive baseline platform and the Hive Portal.

1. Hive baseline platform

The baseline is, as the name suggests, the basic product of Hive. It ensures that you can connect devices and receive data directly. Everything is stored in the customer’s own cloud environment. The big advantage of this is you will never lose your data when you stop using Hive. The Baseline rollout and all devices are automated in Azure Dev Ops. You don’t need IoT knowledge for that. Additionally, the maintenance of the baseline can be outtasked entirely to LINKIT .


If you are going to use IoT, you will always need to install some software to make the end devices suitable for gathering the right info or doing the right task. As an example, you may want to combine a camera with a thermometer, and setting things up so that the camera only starts to film when a certain temperature has been detected on the thermometer. For a large part of these installations we already have blueprints in place to automatically connect your devices to Hive. For a smaller part customisation will be needed.

C# instead of C++

Technically, Hive offers the great advantage that the code is written in C# (C-sharp). A more accessible code than C++, which is normally used for IoT. It’s a lot easier to find programmers who can handle C#, making the devices more accessible to manage and possibly expand the functionalities.

2. Hive’s portal

The Portal is the SaaS part of the solution hosted by LINKIT and this is offered optionally. The main advantage is that the portal allows you to directly update groups of IoT devices from a single device. For example, you can tell all parking meters in Friesland that it is free parking today, while in Groningen, or other areas, the parking price is unchanged. Or to order cameras from a specific section to all start recording when there is a security risk. This is all possible with IoT, and normally, you have to orchestrate these types of commands on a per-device basis. With the Hive Portal, it is possible to simultaneously manage and deploy large IoT amounts while maintaining a birds-eye overview of the environment.

Different versions in one portal

In addition to scalability, working with different versions of IoT is also important. Let’s suppose a supermarket chain installs a POS system in one of its stores, and another version of this system in a different store a year later. This would usually make it tricky to manage both of these systems as they are not integrated. With Hive it’s possible to easily link systems together as they all send data to the same platform.

Less data with Microsoft Edge

A final important issue is that of data storage. Storing and processing all this data from IoT in the cloud while doing it in real-time requires a lot of resources. However, with Microsoft Edge technology t’s now possible to do this differently. For example, you can have certain tasks performed locally on specific IoT devices. Let’s take our camera example, and say it only records when there is movement. This functionality can be carried out with MS Edge on the device itself, instead of in the cloud. This is a great way to save cloud resources for other tasks that cannot be done at a local level. Please keep in mind this does not work on any IoT device.

3. Additional options: AI in Machine Learning

IoT can also be utilised for AI and Machine Learning. For example, in a factory you can use the data from IoT to automate quality inspection. Normally, quality per batch is inspected manually by a quality control inspector. If something seems wrong, the whole batch is often rejected. But what if you can immediately stop the machine if there is a product with an abnormality? The same is true for predictive maintenance, where you use IoT to teach an algorithm when a particular component needs to be replaced. These are possibilities that can greatly increase the efficiency of processes. You can find a full overview of all our articles and cases about this at our topic page about AI and Machine Learning.

Have you become curious about Hive’s possibilities for your company? Check our Hive product page or get in touch with Dick van Straaten, our IoT Lead at LINKIT, for more information and a demo.