The technology used here is Artificial Intelligence and Machine Learning. All building blocks are present, with a camera, a 4G modem, an edge computing device on which the algorithm runs and a cloud platform for capturing and interpreting the data. For the more technical among us, you might also like know that the model was trained using the yolo model (YoloV4) and Darknet using transfer learning techniques. It was therefore developed using fully open source technologies in Python, so you are not entirely dependent on a cloud provider. A fairly simple construction in itself, but one that can make a big difference in the fight against the virus.
A way to make your city smarter
There are many areas of application where this piece of intelligence could prove useful, e.g. an automatic message in bus or tram when more than 5% of passengers aren't wearing their masks or at the entrance to shopping malls. It would also fit in perfectly with the bigger picture of a Smart City. After all, we use new technologies to make cities safer by turning raw data into smart insights. In addition to detecting masks, the same set-up could also be used to see how people move through a city or to count passers-by, monitoring and encouraging social distancing in real time. All data is centralized on a data platform, fully compliant with GDPR rules, of course. The idea is to make data usable by giving it the right meaning, correlating different data sources and building intelligent applications. The ultimate goal is to improve urban life or organize the city better. Based on the data, for example, it is possible to make a dashboard which shows you when a shopping street is busy. A barometer like this helps to prevent crowds, which is quite important in these times.
Any questions about the algorithm? Interested in a smart camera? Or how can this fit in with a Smart City context?
Our experts are here to help!