Lighting the future with data: Neil Ross Daniel Manohar on his internship at Signify

What does Signify do? 

Neil Ross: 'Signify is the global leader in lighting, offering high-quality products, systems and services to both professional customers and consumers. Their connected lighting solutions not only illuminate spaces but also collect valuable data that can be used to optimise environments. These innovations are helping to create a safer, smarter and more sustainable world.' 

What kind of projects or tasks were you involved in during your placement? 

Neil Ross: 'I worked on developing a machine learning model to accurately track the number of people entering and exiting rooms using radar sensor data. The idea was to improve existing rule-based systems, making them more accurate and reliable for real-world applications.’ 

‘The project was done in collaboration with another data science intern based in Dubai. We had regular online meetings every other day, and weekly team meetings with the Systems Expert Team at Signify. We also presented our progress to clients on a monthly basis, ensuring the solution met their needs.’ 

‘Essentially, the radar sensors would send out raw data, which I then labelled, identifying whether it represented one person walking in, two people walking out, and so on. This labelled data was used to train the machine learning model, which could then predict real-time foot traffic. The system was first tested in our own space before being trialled at the client's location. The ultimate goal was to build a more accurate, sensor-based solution to optimise office usage, ensuring lights are only on when needed or meeting rooms are properly utilised.' 

What was the most valuable thing you learned during your time there? 

Neil Ross: 'The biggest learning curve was setting everything up from scratch. At university, we are usually handed clean datasets and told to build a model. Here, I had to collect the data myself, make sure the sensor was working, and navigate the entire process of setup and troubleshooting.' 

How did the placement match your expectations going in? Anything that surprised you? 

Neil Ross: 'I was surprised by how open and welcoming everyone was. Even people who weren’t directly involved in my project were curious and supportive, they would ask questions, share ideas, and offer to help. I expected a more hierarchical atmosphere, but Signify turned out to be a really collaborative and friendly place to work.' 

What was the biggest challenge you faced, and how did you handle it? 

Neil Ross: 'The most challenging part was dealing with a malfunctioning sensor early in the project. We had to decode its signal, only to discover that the instructions were incorrect and the hardware wasn’t functioning as it should. Since I was new to this area, it took time to understand the problem and escalate it properly. Eventually, we got approval to replace it, and I learned a lot about planning for risk and dealing with unexpected issues along the way.' 

Did the experience influence your ideas about your future career path? 

Neil Ross: 'It definitely confirmed that I want to pursue a career in data science. I would still be interested in exploring other domains like healthcare or logistics, but the core of my work will be in data science.' 

What’s next for you? 

Neil Ross: 'I am hoping to do another internship, possibly at Philips in Groningen, working on a different type of project. After that, I will work on my graduation project.' 

You can connect with Neil Ross Daniel Manohar on LinkedIn.