Sigma Software at electronica fair 2024: When Software Meets Hardware

The world’s leading trade fair electronica 2024 gathered 3,480 exhibitors from 59 countries and regions and about 80,000 visitors from around 100 countries and regions. The unprecedented number of visitors originates from the increased interest in electronic components – from automotive, healthcare, defence, and other industries.

Photo credit: electronika fair

This year, electronica was more international than ever with the share of international visitors totaling 54 percent. We witnessed a massive attendance of the fair as well as a plethora of exhibiting companies from Asian countries (overwhelming amount of Chinese visitors) which signifies a major tendency for the ever-increasing competition and even fight for innovations and a bigger market share.

On the background of sustainability, key topics of the fair were artificial intelligence, the future of mobility, and the development of young talent.

Notably, one of the key topics of a hardware exhibition was a completely software-based theme of artificial intelligence. Though it totally reflects one of the main trends I see in today’s manufacturing – synergy of software and hardware.

Semiconductors attracted a lot of attention and crowds of visitors, which once again proved the increased interest in this area due to their necessity in various industries and deficiency in the supply chain. We have clearly observed that semiconductors are modifying their approaches and tech ecosystem to improve their flexibility by means of software.

Photo credit: electronika fair

Predictive Maintenance Solution for Brake Pad Wear

Sigma Software took part with a stand in the Automotive section together with our partner company PGUB Management Consultants. Our team presented a predictive maintenance solution for brake pad wear – Truck Driving Simulator. This solution analyzes real-time vehicle data to forecast maintenance needs.

Visitors could see in real time how driving style impacts the wear of spare parts — in that case, brake pads. For commercial logistics, such insights translate into significant savings on spare parts procurement and warehouse management.

The solution was developed using Eclipse Software Defined Vehicle (SDV) tools, Microsoft’s technology stack, and the expertise of Sigma Software engineers in the automotive domain. The choice of Eclipse SDV tools was very well motivated. It is an open-source platform designed to accelerate automotive software development by enabling modular, scalable solutions that work across various hardware and software environments. And this is especially valuable for predictive maintenance systems, where real-time data processing and integration with in-vehicle and cloud systems are critical.

In combination with Microsoft’s technology stack, which powers our cloud infrastructure and machine learning models, we can efficiently handle large-scale data analysis and ensure robust system performance.

The simulator was a real showstopper, attracting attention and allowing visitors to tangibly experience the solution’s potential. We had a lot of discussions on how predictive maintenance can enhance safety, reduce costs, and optimize vehicle management.

Meanwhile, we are working on the next stage: integrating real vehicle data into the ML model. The prototype is being assembled in one of Sigma Software’s offices these days. It is the front part of a car, with all the main parts: brake discs, brake pads, sensors from which we get data for the predictive maintenance solution, steering wheel, accelerator, brake pedals, and an electric engine to move the brake disc, so it is an E-vehicle!

The team is extremely motivated and enthusiastic about the project’s future development. We are looking forward to discussing the results and insights we have received with our partners and clients.

• #AI/ML
• #Automotive