Virtual Antenna® enables reliable cellular connectivity for Withings’ new product line

30 May 2023 Case Studies

Download the case study here. 


AI & Machine Learning: Simplifying IoT Antenna Integration

Aitor Moreno
24 May 2023 Blog

Probably not too many people have missed the recent uptake in general awareness of the power of Artificial Intelligence (AI), and its subset: Machine Learning (ML) enabled by neural networks. Not unlike a volcano, this has been a “waiting to happen” eruption which now leads to the generation of endless new use cases, some of which are extremely powerful, others may take some time to prove. Tools like ChatGPT, and AutoGPT and their variations are changing how we deal with problems that require a broad set of data. Ignion, a company known for its innovative mindset, has embraced this opportunity to automate the development process for its Virtual Antenna® technology giving the IoT market access to a powerful and useful design tool.

How did the Ignion journey to an ML-powered digital twin design tool begin?

Many moons and designs ago our development team looked at the possibilities of this new expanding computational toolkit and set out to leverage it to automate the development tools and processes leading to the best use of our Virtual Antenna® technology. We rapidly discovered that training a ML model, or relying on specific libraries was not enough, and focused our internal processes to consider the entire workflow. Next, we took a new look at data management, making it a part of our design and engineering workflows, and as a result, thousands of anonymized designs and all their relevant parameters were collected, stored, and compressed to enable extraction of the relevant metadata. Machine Learning is used to complement computationally expensive electromagnetic real-world lab simulations with relatively cost-effective requests to a cloud-based model.

The ultimate self-learning antenna design tool for your IoT project

The design datasets are used to train regression and classification models for the prediction of an optimal design from an RF perspective. The outcome includes several important indicators of RF performance, including radiation efficiency which measures how input power converts to radiated power, important in determining wireless coverage and battery consumption. The reflection coefficient (S11) as a function of frequency shows impedance matching to guarantee transmission is maximized within the selected frequency bands.  The optimal matching network setting (i.e., a network of inductors and capacitors and their precise values) is also included in the design recommendations based on the ever-increasing library of projects.

What is the outcome of leveraging machine learning for antenna integration in IoT?

The result was the launch of our Antenna Intelligence Cloud™ early in 2022, based on the forward-thinking and many years of preparation and dedication by our R&D and Engineering teams. Nowadays the models are trained in an active learning environment to continuously improve by using new data. The resulting algorithms allow engineers to design optimal Virtual Antenna® technology-centric RF systems, making the formerly complex process as straightforward as building with LEGO blocks.

As Ignion’s AI journey continues, the company plans to explore further advancements in RF system design not unlike the evolution we have seen in the mobile phone industry. Stay tuned!

the author

Aitor Moreno

Aitor Moreno is Ignion’s Cloud Product Manager and oversees the Antenna Intelligence CloudTM strategy and roadmap implementation, working in close collaboration with Engineering and Marketing teams at Ignion. Aitor graduated…

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Ignion at IoT Days Summer

29 Jun 2023 Events
Event schedule:

Panel: Why the World Needs IoT

Thursday, June 29, 2023, 10am EDT


Exponential growth in the need for energy and materials to stave off climate change, reduce hunger, and otherwise ensure a quality of life will drive innovation around the globe. IoT will act as both a cause and a catalyst for these innovations. The technology is now bringing results in energy management, resource conservation, waste management, air quality monitoring, and smart agriculture. This conference track will provide the latest IoT use cases in ESG platforms.

Join our VP Product & Marketing Johan Pedersen in this panel.

  • When? June 29.
  • Where? Save your online spot here.


Ignion at Hardware Pioneers UK

13 Jul 2023 Events

The must-attend event for engineering teams and C-level executives who are building the next generation of smart and connected products. Main topics covered at the show: Component shortage challenges and solutions, Edge AI, Sensor technology, IoT security, FPGA technology, Ultra-wideband (UWB), Cellular IoT, AI hardware, Power Management technology; and many more.

  • When? 13 July 2023 – Central London.
  • Where? Business Design Centre. 52 Upper Street, London, N1 0QH.
  • How? Visit our booth #60.


*Co-funded by the European Union.

Ignion at Embedded World China

14 Jun 2023 Events

Since 2003, Nürnberg Messe has hosted Embedded World Exhibition&Conference, the leading event for the global embedded industry. It showcases the latest trends and innovations in this fast-growing field. To serve the Chinese market better, NürnbergMesse China Co., Ltd. and IM Creativity (Shenzhen) Co., Ltd. will launch Embedded World China in Shanghai from June 14-16, 2023. This show will cover a wider area than East China and provide a trustworthy platform for the community of embedded technology developers.

Over 300 exhibitors are expected to participate in the Shanghai World Expo representing the areas of components, modules, application systems, embedded image processing systems, and communications, in addition to more than 10,000 trade visitors. The show will focus on intelligent and secure design and solutions for the automobile and IoT industry.

  • When? Jun 14-16 2023.
  • Where? Hall 3, Shanghai World Expo Exhibition & Convention Center.
  • How? Visit our booth @A298.


*Co-funded by the European Union.