This paper reports our experience with crowd monitoring technologies in the challenging real-world conditions of a modern, open-space museum. We seized the opportunity to use the NEMO science center as a testbed, and studied the effectiveness of neighborhood discovery and density estimation algorithms in a network formed by visitors wearing bracelets emitting RF beacons. The diverse set of conditions (flash crowds in open spaces vs. single person booths) revealed three interesting findings: (i) state-of-the-art density estimation fails in 80% of the cases, (ii) RSS-based classifiers fail too, because their underlying assumptions do not hold in many scenarios, and (iii) neighborhood discovery can obtain exact information in an energy-efficient way, provided that static and mobile nodes are differentiated to filter out “passers by” clobbering the true popularity of an exhibit. The overall lesson from the experiment is that today’s algorithms are quite far from the ideal of monitoring popularity in a privacy-preserving and energy-efficient way with minimal infrastructure across the set of heterogeneous conditions encountered in practice.@en

When deploying a testbed infrastructure for Wireless Sensor Networks (WSNs), one of the most challenging features is to provide repeatable mobility. Wheeled robots, usually employed for such tasks, strive to adapt to the wide range of environments where WSNs are deployed, from chaotic office spaces to neatly raked potato elds. For this reason, wheeled robots often require an expensive customization step in order to adapt, for example, their localization and navigation systems to the specific environment. To avoid this issue, we present Gondola, a parametric robot infrastructure based on pulling wires, rather than wheels. Gondola avoids the most common problems of wheeled robots and easily adapts to many WSNs' scenarios. Different from existing solutions, Gondola can easily move in 3-dimensional space, with no need of a complex localization system and with an accuracy that is comparable to o-the-shelf traditional robots.@en