Bringing Artificial Intelligence (AI) and Machine Learning (ML) to the industrial edge
When I was a student some thirty years ago, I spent my vacations working for a company that developed industrial control systems. They could actually be regarded as rudimentary industrial IoT systems — we would take readings from sensors located inside the machines, parse them through simple processing scripts, and then send the outputs over a wire to control equipment on the factory floor. For example, I made a system that controlled a furnace, based on inputs such as temperature and time.
How times have changed! Today’s industrial IoT systems are far more capable on a number of dimensions:
- Sensors are much more accurate, and can measure different types of inputs, including pressure, friction, vibration, and appearance.
- Communications greater capacity and reliability, enabling wired and wireless connectivity over longer distances.
- The ability to handle all of the data flowing in from the edge has massively improved.
This last point does not only refer to faster processing, larger storage volumes, and more bandwidth. It also refers to the increased ability to derive insights and take immediate action based on them automatically with Artificial intelligence (AI). This latent technology trend has been re-ignited by the explosion of sensors’ data – Industrial IoT data – and has started to transform operations at the edge, leading to new and exciting possibilities.
Read the entire article here, Bringing Artificial Intelligence (AI) and Machine Learning (ML) to the industrial edge
Via the fine folks at HP Enterprise.