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The proliferation of RF networks coupled with the diverse and growing set of mobile devices, opened the doors for a new class of context awareness through contact-free ambient sensing. Since our initial challenges paper in 2007, the field of device-free passive sensing has witnessed an exponential growth; covering areas such as intrusion detection, mobile healthcare, whole-home gesture recognition, traffic estimation, border protection, among others. In this talk, we give a holistic overview of the area of contactfree ambient sensing based on RF technology, highlighting how it evolved over a decade from binary-detection in controlled environments to commercial systems for border protection and smart homes. We also give insights about the current trends and possible future research challenges.

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Abstract-The widespread usage of wireless local area networks and mobile devices has fostered the interest in localization systems for wireless environments. The majority of research in the context of wireless-based localization systems has focused on device-based active localization, in which a device is attached to tracked entities. Recently, device-free passive localization (DfP) has been proposed where the tracked entity is neither required to carry devices nor participate actively in the localization process. DfP systems are based on the fact that RF signals are affected by the presence of people and objects in the environment. The DfP concept enables a wide range of applications including intrusion detection and tracking, border protection, and smart buildings automation. Previous studies have focused on small areas with direct line of sight and/or controlled environments. In this paper, we present the design, implementation and analysis of Nuzzer, a large-scale device-free passive localization system for real environments.Nuzzer is designed to satisfy specific goals; high accuracy, ubiquitous coverage, scalability, and operation in real environments. Without any additional hardware, it makes use of the alreadyinstalled wireless data networks to monitor and process changes in the received signal strength (RSS) transmitted from access points at one or more monitoring points. We present probabilistic techniques for DfP localization and evaluate their performance in a typical office building, rich in multipath, with an area of 1500 square meters. Our results show that the Nuzzer system gives device-free location estimates with less than 2 meters median distance error using only two monitoring laptops and three access points. This indicates the suitability of Nuzzer to a large number of application domains.

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We present the design and implementation of the Horus WLAN location determination system. The design of the Horus system aims at satisfying two goals: high accuracy and low computational requirements. The Horus system identifies different causes for the wireless channel variations and addresses them to achieve its high accuracy. It uses location-clustering techniques to reduce the computational requirements of the algorithm. The lightweight Horus algorithm helps in supporting a larger number of users by running the algorithm at the clients.We discuss the different components of the Horus system and evaluate its performance on two testbeds. Our results show that the Horus system achieves its goal. It has an error of less than 0.6 meter on the average and its computational requirements are more than an order of magnitude better than other WLAN location determination systems. Moreover, the techniques developed in the context of the Horus system are general and can be applied to other WLAN location determination systems to enhance their accuracy. We also report lessons learned from experimenting with the Horus system and provide directions for future work.

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