TinyML and Edge AI prevent damage to mixer
A meat mixing machine sustained pregel damage as the meat mixture froze. This damaged the mixing gases, resulting in high costs and downtime.
Kasper Tiebe, Master's student Applied AI at the HvA, with support from the Fieldlab, developed a TinyML solution to detect this early and prevent downtime.
How TinyML monitors plastic consumption in real time
A producer of labels and tags, wanted to better understand the plastic consumption and performance of their Melzer die-cutting machine. No real-time data was available to analyse production efficiency or material consumption.
Students from the Hogeschool van Amsterdam developed a TinyML solution through the Fieldlab that now measures and transmits production data automatically.
TinyML as a solution to tackle noise pollution
A factory received more than 250 reports of noise pollution from local residents in 2022. The challenge? The noise was coming from the rolling mill, but was difficult to locate and analyse.
Students from the HvA developed a prototype in the Fieldlab that uses TinyML and sensors to detect noise nuisance as well as indicate exactly where and when it occurs. This allows for targeted intervention.
Reading analogue meters with AI and image recognition
Hundreds of analogue meters hang on the plant premises, providing vital information on consumption. These meters are read manually.
A Master Applied AI student at the Hogeschool van Amsterdam, Lenka Piet, in collaboration with the Fieldlab, developed a solution using Edge AI and image recognition to automatically read the existing meters.