08-05-2019
3 min. read
Sjors de Kleijn

How you get ready for AI using IoT

Kickstart your AI implementation with big data

Artificial Intelligence is the latest Industry 4.0 topic rising to the industry's attention. It may be too far away for you at this time, but that doesn't mean you shouldn't be ready for itRead why and how you should prepare your machines using IoT to benefit from AI in the (near) future.

Artificial Intelligence offers opportunities for the manufacturing industry

AI-technology offers many powerful benefits for industrial automation: increased efficiency, cost savings, upgraded customer experiences and new business models. Machines and systems get smarter and new AI platforms pop up daily, so the application of self-learning systems is getting closer.

The key ingredient of implementing AI: Big Data

To implement AI, machine learning or deep learning, you need data to work with. The machine's insights (from PLC, sensors, robots, controllers, etc.) are necessary to create algorithms and find trends, which is instrumental to a successful implementation of AI. There are companies who use AI successfully and the common denominator is big data.

So if you want to get started on your AI strategy, then big data is the key ingredient you need to get started. But how to collect and store this data? That's when IoT comes into play!

Use IoT for connectivity and data storage

Machines generate a lot of data, but it's usually stored locally and only accessed by the PLC programmer. Why not store this information in a secure environment using smart connectivity?

That way your data becomes accessible to all. New IoT protocols, like MQTT, open the door to collect data securely and efficiently from industrial devices. This machine-to-machine (M2M) connectivity protocol transfers this data to time series database clusters in the cloud.

Data insights make it possible to execute extensive analysis and apply AI capabilities that make your machines smarter or even self-learning.

IoT is your stepping stone to AI.

But what about security? Cybersecurity is a hot issue these days, so you should be aware of any potential risks.

Share your data but protect it too

When industrial machine components get smarter, the IoT security risks increase. When it comes to cybersecurity, the integrity of (machine) data is very important. You don't want your data on the street and made public to anyone. It can harm your brand name or business when this happens.

So before you decide to store data in an (open) cloud environment, be sure you trust your IoT partner to reduce the security risks to a minimum.

When to start implementing Artificial Intelligence?

As AI is evolving rapidly, it's not the question of why but when to take advantage of it. But how to start implementing it?

My advice is to be prepared and start today by collecting and storing your machine's big data. You'll then be a step ahead and can use this data when AI implementation comes up.

But before you're ready for AI, your data doesn't have to go to waste. Take advantage of the collected big data and use it for other applications: visualise it in dashboards or generate notifications. You can monitor the machine's state or report productivity to manufacture improved machines and troubleshoot faster.

Get AI ready: start collecting big data now

Using IXON's IoT feature to store machine data easily, you will be prepared to store data securely – from scratch to the cloud – in just hours. The integrated connectivity collects the data from the PLC and sends it securely to the IXON Cloud. Configured without any coding and fully configurable on the web-based cloud platform called IXON Cloud.

As we use an open cloud environment, the data can be transferred now or in the future to any AI tool using our API.

Our affordable data logging feature can be tested for free. Just request a Cloud Logging trial and connect your machines to the IXON Cloud using our IXrouter (request an evaluation kit here).

Case study: How IoT made data storage easy for Water IQ

Our customers use the data features to their advantage. This case study explains how Cloud Logging helped Water IQ provide better service with machine data visualisation.

[[Download the Water IQ case study]]