Archinisis Blog: An Internship at Archinisis

A cold plunge is a shock to the system: icy water grips the body, breath shortens, and almost immediately relief sets in. Muscles ease, swelling fades, and the heat of exertion gives way to clarity. Focus sharpens, mood lifts, and what begins as discomfort transforms into energy.

In much the same way, an internship at Archinisis is both invigorating and a little daunting. Over the course of their first two weeks, our interns have submerged their bodies into a vast ocean of sensor data processing and data analysis, an experience as challenging as it is refreshing.

For our interns - Chloé, Jan, and Gerrit - it was their first hands-on encounter with sensors. Guided step by step through this unfamiliar terrain, the structured program designed by Benedikt Fasel introduced them to new concepts and showed how a simple idea can gradually evolve into a fully functioning algorithm.

Here's a glimpse at the themes they explored:

Python programming equipped them with the tools to process and analyse sensor data.
IMU data plunged them into raw motion signals.
GNSS data added a spatial layer, connecting motion with precise location and timing.
Event detection revealed how streams of numbers can be transformed into identifiable, actionable moments.
Sensor synchronization taught them how to merge multiple data sources into one.
Plotting turned dense data into clear visual insights.
Functional calibration helped refine accuracy, correct biases, and strengthen reliability.
Coordinate system alignment unified all outputs into a shared spatial framework, completing the journey from raw signals to a coherent, fully functioning data analysis system.

Here's how the interns themselves described their learning journey.

"I learned what kind of data the Naos sensor collects and how I can visualize this data using Python. Furthermore, I learned how to interpret the data and how to write first event detection algorithms, such as a step detection algorithm." Gerrit

"I learned a lot about how the Archinisis sensor works. I got to do some hands-on experimenting. Those two weeks also served as a good refresher from my bachelor's degree coding classes." Chloé

"I learned about the complex process of turning raw IMU and GNSS sensor data into interesting insights. Every sport (from running to horse riding to rowing) requires a different approach to handling data, and that makes it very exciting. I also learned about the high accuracy and frequency of the sensors, which impressed me very much." Jan

They explained how these two weeks connected to their projects and studies.

"These two weeks were beneficial for my project, as I am comparing the sensor data with a reference system, and it is important to know how both systems work and how the recorded data is processed and evaluated in each case. The Python skills I have acquired also make the evaluation process much easier." Gerrit

"It helped me get in the loop of what we are working on and with at Archinisis. I also had the chance to meet Gerrit Lang, who is working with us on the study as part of his PhD. Moreover, this experience allows me to venture slightly outside the scope of my studies and learn new things." Chloé

"After 3 years of studying data science, I can now apply what I have learned in the field of sports, which I enjoy. In addition, my internship gives me the opportunity to work with large amounts of very accurate data, which is something every data scientist would be happy about. Also, we have the benefit of learning from Benedikt’s knowledge and experience in the field." Jan

These two intense weeks mirrored not just a dip into icy water, but the steady practice of learning to swim in it. The benefits were instant, yet also compounding. Their theory-swollen brains subsided, much like how the body gradually adapts to cold immersion, shock giving way to endurance. Just as repeated exposure sharpens focus and builds resilience, the hands-on experience invigorated their curiosity and confidence. The initial chill of stepping into unfamiliar sensor programming was met with gradual adaptation and growth, echoing how one learns to find strength, rhythm, and clarity in cold water over time.

Here's what Benedikt Fasel had to say about working with interns:
"It's important to me that everyone understands what they're doing at work. These two weeks were designed to build a solid knowledge base and encourage critical thinking. It was also essential that the interns adapt to the company's way of working: we aim for precision and excellence in everything we do. Our interns must be equally detail‑oriented to uphold this level of quality."

Group picture with Benedikt and the interns

These first two weeks were only the beginning. Over the coming months, Chloé will work on horse jumping in collaboration with Gerrit, who has just embarked on his PhD at TU Dortmund, until January 2026. At the same time, Jan will be immersed in analysing stroke acceleration patterns across different stroke rates and speeds.

Looking ahead, the interns described how their internship will unfold.

"At the moment, Chloé and I are working with Archinisis' existing algorithm for the HorSense validation project and are trying to get it running." Gerrit

"I am now fully working on the new study around horse jumping in collaboration with Gerrit and with the help of Benedikt Fasel." Chloé

"In the coming months, I would like to dig deeper into the world of rowing, hoping to find explanations and patterns in the data. The solid data foundation offers many opportunities for analysis. In general, I would like to deepen my knowledge in the field of data processing and analysis from IMU and GNSS sensors and tackle interesting problems." Jan

In the end, this internship was not just a plunge but a swim: a bold, recovering challenge that dissolves apprehension, energizes learning, and leaves the interns ready to dive back in.

Picture of Benedikt and Chloe discussing findings