This July, the city of Newcastle hosted the Sensors Applications Symposium – IEEE SAS 2025, an international event that brings together universities, companies, and research centers from around the world to discuss the future of smart sensing technologies.
Among the participants was Antonio Cancilla, R&D Engineer at Teoresi MedTech, who presented a paper on the SPS project, a solution for predictive maintenance of electric motors using self-sustainable IoT sensors and unsupervised algorithms. The paper was co-authored with Guido Comai (Teoresi MedTech) and Tommaso Polonelli (ETH Zürich).
We interviewed Antonio after his return from the event:
Antonio, what was it like presenting your work in an international context such as SAS 2025?
It was a high-level experience, with many universities from all over the world, including several top Italian institutions like Politecnico di Milano and Alma Mater Studiorum – University of Bologna. However, it wasn’t purely academic: several companies, including Teoresi, were also there to present success stories and real-world use cases. It was a very stimulating environment, open to dialogue between research and practical applications.
What stood out the most to you about the event?
Definitely the dynamic atmosphere and strong focus on fresh researchers. There were many under-30 participants, and the spotlight was clearly on applied innovation across key sectors such as medical, agriculture, and manufacturing. Discussions focused on smart sensors with real applications, which made the exchange particularly engaging.
How did your presentation go?
I had the opportunity to present our approach to predictive maintenance using self-powered sensors and online clustering algorithms. The audience was diverse, with both professors and fellow engineers, and I received some great questions—especially about the scalability potential of the SPS system in industrial settings.
Was there room for networking beyond the technical sessions?
Absolutely. The event was clearly designed to foster connections. There were thematic sessions and dedicated moments to encourage dialogue, knowledge sharing across disciplines, and future collaborations. I was able to connect with professionals working in medical and agritech applications, which could potentially open new directions for us too.
A valuable opportunity not only to showcase the strength of Teoresi’s research, but also to confirm that the future of industrial sensing is already in motion and speaks many languages.
