We are proud to let you know that we’ve partnered with Edge Impulse and ARM to deliver efficient, power-optimized on-device machine learning solutions so we can increase the added value of our deliveries. We are excited to be able to begin to unlock endless possibilities for our customers through machine learning by making our devices smarter.
Category: IoT Blog
IRNAS and Smart Parks have been working on designing the next generation of open-source tracking solutions for national park management and wildlife protection for the past two years and the deployment of these solutions in the field has proven very valuable.
There is a common problem with having many devices on the same I2C line. In case one of them fails, it can interrupt communication between the master and the other slaves. Rerouting function calls from application to drivers through a special class can help tackle this.
Part 2 of article series about running machine learning algorithms on microcontrollers. In this part, we deploy the machine learning model to a microcontroller and compare it with results in Part 1.
In this two-article series we will see how to train a machine learning model and deploy it to a microcontroller. For that, we will use TensorFlow Lite framework.
Advance sensor systems, data analysis and machine learning for the development of cost-effective hybrid varistor electronic components with improved thermal stability
The innovation company IRNAS, providing the smart IoT solutions for industrial applications and the cutting-edge technology manufacturer of overvoltage protective and EMI suppression components, Bourns, did join forces on the NexGenHVEC project to accelerate development and advance the production line by implementing data collection and machine learning technologies.
Implementing good practices of software engineering on embedded software development is becoming more and more important. This blog is a demonstration of a simple example showing the setup of a development environment for embedded software development on nRF52 on Linux mashing using the GCC compiler.
By supporting execution of external Python scripts PlanetCNC has enabled us to build end-to-end automated custom CNC systems. In this blog we are showing you the benefits of CNC system automation using Python, based on a simple beam scanning example.
In low power devices it is important to closely inspect the power coonsumption behaviour of all modules on the device. To be able to have constant insight in the behaviour of our devices we have developed a fully automated power consumption test system using Otii Enterprise.
Acquisition of scientific equipment has been on an unsustainable run for a very long time. We are on a mission to pave the way to an alternative approach for scientists to be able to maximize the impact of the advantages that technology brings into their day-to-day life. We’re developing custom technollgical solutions through project-oriented collaborations with research organizations, putting technology in place to serve the needs of science.