Abstract-To simulate crowds at mass events, realistic movement data of people is required. Despite their limited capacity for approximating real human mobility, synthetic movement models are traditionally used for this purpose. More realistic simulations can be achieved by using real-life movement data, gathered by observing people in the desired context. This paper presents a method for tracking people at mass events without the need for active cooperation by the subjects. The mechanism works by scanning at multiple locations for packets sent out by the Wi-Fi interface on visitors' smartphones, and correlating the data captured at these different locations. The proposed method can be implemented at very low cost on Raspberry Pi computers. This implementation was trialed in two different contexts: a popular music festival and a university campus. The method allows for tracking thousands of people simultaneously, and achieves a higher coverage rate than similar methods for involuntary crowd tracking. Moreover, the coverage rate is expected to increase even further as more people will start using smartphones. The proposed method has many applications in different domains. It also entails privacy implications that must be considered when deploying a similar system.

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Physical-layer ngerprinting investigates how features extracted from radio signals can be used to uniquely identify devices. is paper proposes and analyses a novel methodology to ngerprint LoRa devices, which is inspired by recent advances in supervised machine learning and zero-shot image classi cation. Contrary to previous works, our methodology does not rely on localized and low-dimensional features, such as those extracted from the signal transient or preamble, but uses the entire signal. We have performed our experiments using 22 LoRa devices with 3 di erent chipsets. Our results show that identical chipsets can be distinguished with 59% to 99% accuracy per symbol, whereas chipsets from di erent vendors can be ngerprinted with 99% to 100% accuracy per symbol. e ngerprinting can be performed using only inexpensive commercial o-the-shelf so ware de ned radios, and a low sample rate of 1 Msps. Finally, we release all datasets and code pertaining to these experiments to the public domain.

We present the NIProxy, a flexible network intermediary which aims to improve the Quality of Experience (QoE)