In current times, the proliferation of smart and IoT devices is generating vast amounts of data, presenting new challenges for leveraging this information to enhance efficiency, drive innovation, and improve decision-making. One significant application is crowd monitoring, which is becoming crucial in urban environments by improving public safety, optimizing traffic flow, and enhancing the management of events and public spaces. The analysis of wireless network traces has emerged as an effective method for real-time crowd size estimation and movement pattern analysis. WiFi Probe Requests have proven particularly valuable for providing these real-time insights and behaviors. The primary focus of this thesis is on estimating the number of people by processing and analyzing captured WiFi Probe Request messages.