Classificando o número de pessoas em um ambiente via sinal RF: uma abordagem aplicando aprendizado de máquina

Abstract

This work proposes a technique for counting people in an already populated environment. Initially, a survey of the technologies and solutions designed for this purpose is carried out. As a proof of concept, a counting solution is analyzed for a small number of people, at two different frequencies, applying machine learning to the descriptive statistics of an RF signal. Finally, classification results are presented for a more realistic scenario, with up to 350 people in the environment, using a software-defined radio measurement system for data collection. The results demonstrate significant accuracy in counting the number of people per classification into groups of individuals.