PiezoMotor is involved in several projects working with global tech giants to create motion in telecom infrastructure. We believe micromotors using piezo technology will play an important role when it comes 5G and IoT. The coming months we will publish articles related to the subject. In order to succeed PiezoMotor works closely with several partners. Today we let our friend Jon Lindén, CEO and co-founder of Ekkono Solutions, share his views on the meaning of reflection in the new age of data.
A few weeks ago I attended a seminar with the management coach and motivational speakerChrister Olsson, who said “experience without reflection, is no experience”. Take a second to reflect on that. What Olsson says is that only registering impressions through our senses, without processing it, is not really a learning experience.
Do you see the similarities with Internet of Things? I do. IoT is all about connecting things – basically anything that can be connected – and collect sensor data. And then what? Catch phrases like “data is the new oil” are flying around, and it might be true, but it’s when you process and reflect on the data, that you refine it and extract its true value.
What struck me when listening to Olsson was that data is neutral, while reflections are contextual and subjective. What we see is what we see, but processing it takes personal preferences, previous experiences, conditions, and the purpose of the reflection into account. And this is where it starts to get really interesting.
Smart automation on a global scale
Historically a sensor measured one value and indicated when it exceeded a generic threshold. Like a motor running hot. Today a sensor is a data source, and it’s joined with other sources to draw complex conclusions. Tailored, individual conclusions. Like the motor is running hot, butconsidering humidity, surrounding temperature and workload, it’s normal and not a problem because it’ll not cause any degrading wear on the motor.
This kind of conclusions enables automation. Smart automation. Global automation, since you can support both Swedish and Malaysian deployments without custom programming or manual supervision, by letting the device learn what’s good and what’s not, enabling experts to remotely support the machine only when actual, qualified issues occur.
The relationship between machine learning and IoT
So how do we make things reflect on their experiences? Through machine learning of course. This is why IoT and machine learning are so closely related. By continuously training the machine learning model for an individual device or machine, it learns the specific conditions, what has the biggest impact on performance, preferences of people using it, and how weather and other factors impact usage.
I’ve heard that it takes 10,000 hours of practice to become an expert. Machine learning is tirelessly processing sensor data 24/7, training an ever-better model, which should make it an expert in just under 14 months. Reflecting on every impression it gets. How can this help you and your business? Reflect on that.