Release the potential in IoT with Edge Machine Learning
Machine learning has been used to train and learn machines for decades. Moving into Industry 5.0, we all need to take that extra scope of responsibility to make machines, factories and entire supply chains seamlessly connected and more sustainable by continuously learning on the edge. We have to create truly smart devices to learn individually, predict and optimize themselves.
To truly make connected things smart, you need to collect data, process it and continue to learn onboard single devices. By “smart” we mean that products become self-learning, predictive and context-aware to understand and adapt to the individual application, load and environment where they are deployed. The solution to smart IoT spells Edge Machine Learning.
From Edge Computing – to Edge Machine Learning
Edge Computing has been around since the late 90s, and simply means that you bring computation and data storage closer to the sources of data. But, the possibility of doing actual machine learning, and not just inference at the edge of the network, is fairly new. Machine learning on the edge means that you can learn individual use and super-local conditions – even on really small devices that run MCUs.
Using Incremental Learning, you also get the ability to learn by doing, in real-time, meaning the more data that is processed onboard a device or a machine, the more personalized insights the product gets. It is not about collecting as much data as possible; It is about processing the right data. The more accurate training, the more personal insights and machine learning models.
Explore the benefits of Edge Machine Learning
- Make your products smart, personalized and make them “learn by doing”
- Stop collecting a lot of data. Start with what you have.
- Learn what’s normal and detect deviations
- Predict and make your maintenance remote
Ekkono is a technology pioneer, hence very experienced tech and IT entrepreneurs. Our customers appreciate our niched expertise and understanding of complicated infrastructures. They come to us with a problem, but we always focus on the solution. We use a refined model of the well-known CRISP-DM method for a structured progress along every project, from start to finish. Our customers are the domain experts, we know how to deploy Edge Machine Learning to get smart, secure and sustainable connected products.