People transit monitoring using WiFi and Bluetooth signals with AI support
Thesis in external company
keywords ARTIFICIAL INTELLIGENCE, MACHINE LEARNING, SENSORI, WI-FI
Reference persons CLAUDIO ETTORE CASETTI, PAOLO GIACCONE
Thesis type EXPERIMENTAL
Description The thesis consists in the collection and analysis of data from sensors capable of detecting the presence and / or passage of people through the Wi-Fi and Bluetooth signals generated by their smartphones. The sensors, on which the thesis is concerned, are installed in places with transit of people (for example, public buses). Using ML / AI techniques, we want to analyze the large volumes of data returned by the sensors, comparing them with experimentally observed data, in order to design techniques capable of determining with a certain degree of fidelity, the number of people present in the surrounding environment. The Thesis will be carried out in Dropper (www.dropper.ai).
Required skills Programming languages: C and Python. Basic Data Analysis Techniques, ML and AI.
Deadline 13/09/2023 PROPONI LA TUA CANDIDATURA