Edge Computing

Increase the performance of your Industrial IoT with edge-based devices

Kapernikov makes your industrial sensors smarter by combining them with local computing power. By putting intelligence on the edge of your network, we increase the performance of your Industrial Internet of Things. We make use of off-the-shelf components to develop smart sensors and we train artificial intelligence for the highest performance.

We can help you to:

  • Extend the capabilities of classic PLC automation
  • Make your legacy production machines more intelligent
  • Unlock your data
  • Integrate edge devices with your robots or production processes
  • Improve real-time process control
  • Make remote deployment and management possible

Intelligence on the edge

Your production machines and robots have become smarter. Digital sensors are able to register everything 24/7, creating your own Industrial Internet of Things (IoT). The flip side is that your cameras and data sensors generate massive amounts of data, which become harder to manage. Transmitting all this data over the network and storing it puts a high strain on your network bandwidth, data storage and computational power.

The answer lies in processing sensor data close to your production machines. Edge-based devices enable you to collect real-time data about your production processes, while transmitting only the necessary information over the network. This reduces the flow of traffic to the central server and provides real-time local data analysis.

Edge computing for manufacturers

We typically deliver turn-key projects for manufacturers. But just as much, we like to share our knowledge about edge computing with our customers. For machine builders, our consultants can be the ideal in-project support. We share our knowledge about the latest evolutions in hardware and software and work together with your team to shorten your development cycle.

Edge computing technologies

We use any commercial, open source or custom developed software on low-power embedded devices or powerful industrial PCs. We can set up technologies such as Azure Device Twins to allow for remote configuration or to use the IoT hub for data logging and control.

However we integrate different cloud providers or use on premise

  • Local computing power to make smarter sensors
  • Provisioning
  • Remote monitoring of an edge device
  • Local deployment over unreliable intermittent connection

We can process any type of sensor data. Typically, the biggest opportunities come from sensors that create a lot of data, such as cameras or vibration sensors. Also, battery-powered, environmental monitoring sensors with limited connectivity pose interesting challenges.