Joint Ultra-wideband and Signal Strength-based Through-building Tracking for Tactical Operations

Accurate device free localization (DFL) based on received signal strength (RSS) measurements requires placement of radio transceivers on all sides of the target area. Accuracy degrades dramatically if sensors do not surround the area. However, law enforcement officers sometimes face situations where it is not possible or practical to place sensors on all sides of the target room or building. For example, for an armed subject barricaded in a motel room, police may be able to place sensors in adjacent rooms, but not in front of the room, where the subject would see them. In this paper, we show that using two ultra-wideband (UWB) impulse radios, in addition to multiple RSS sensors, improves the localization accuracy, particularly on the axis where no sensors are placed (which we call the x-axis). We introduce three methods for combining the RSS and UWB data. By using UWB radios together with RSS sensors, it is still possible to localize a person through walls even when the devices are placed only on two sides of the target area. Including the data from the UWB radios can reduce the localization area of uncertainty by more than 60%.Comment: 9 pages, conference submissio

Dial It In: Rotating RF Sensors to Enhance Radio Tomography

A radio tomographic imaging (RTI) system uses the received signal strength (RSS) measured by RF sensors in a static wireless network to localize people in the deployment area, without having them to carry or wear an electronic device. This paper addresses the fact that small-scale changes in the position and orientation of the antenna of each RF sensor can dramatically affect imaging and localization performance of an RTI system. However, the best placement for a sensor is unknown at the time of deployment. Improving performance in a deployed RTI system requires the deployer to iteratively "guess-and-retest", i.e., pick a sensor to move and then re-run a calibration experiment to determine if the localization performance had improved or degraded. We present an RTI system of servo-nodes, RF sensors equipped with servo motors which autonomously "dial it in", i.e., change position and orientation to optimize the RSS on links of the network. By doing so, the localization accuracy of the RTI system is quickly improved, without requiring any calibration experiment from the deployer. Experiments conducted in three indoor environments demonstrate that the servo-nodes system reduces localization error on average by 32% compared to a standard RTI system composed of static RF sensors.Comment: 9 page

Multiple target tracking with RF sensor networks

pre-printRF sensor networks are wireless networks that can localize and track people (or targets) without needing them to carry or wear any electronic device. They use the change in the received signal strength (RSS) of the links due to the movements of people to infer their locations. In this paper, we consider real-time multiple target tracking with RF sensor networks. We apply radio tomographic imaging (RTI), which generates images of the change in the propagation field, as if they were frames of a video. Our RTI method uses RSS measurements on multiple frequency channels on each link, combining them with a fade level-based weighted average. We introduce methods, inspired by machine vision and adapted to the peculiarities of RTI, that enable accurate and real-time multiple target tracking. Several tests are performed in an open environment, a one-bedroom apartment, and a cluttered office environment. The results demonstrate that the system is capable of accurately tracking in real-time up to four targets in cluttered indoor environments, even when their trajectories intersect multiple times, without mis-estimating the number of targets found in the monitored area. The highest average tracking error measured in the tests is 0.45 m with two targets, 0.46 m with three targets, and 0.55 m with four targets

Breathfinding: A Wireless Network that Monitors and Locates Breathing in a Home

This paper explores using RSS measurements on many links in a wireless network to estimate the breathing rate of a person, and the location where the breathing is occurring, in a home, while the person is sitting, laying down, standing, or sleeping. The main challenge in breathing rate estimation is that "motion interference", i.e., movements other than a person's breathing, generally cause larger changes in RSS than inhalation and exhalation. We develop a method to estimate breathing rate despite motion interference, and demonstrate its performance during multiple short (3-7 minute) tests and during a longer 66 minute test. Further, for the same experiments, we show the location of the breathing person can be estimated, to within about 2 m average error in a 56 square meter apartment. Being able to locate a breathing person who is not otherwise moving, without calibration, is important for applications in search and rescue, health care, and security

Application-driven data processing in wireless sensor networks

Wireless sensor networks (WSNs) are composed of spatially distributed, low-cost, low-power, resource-constrained devices using sensors and actuators to cooperatively monitor and operate into the environment. These systems are being used in a wide range of applications. The design and implementation of an effective WSN requires dealing with several challenges involving multiple disciplines, such as wireless communications and networking, software engineering, embedded systems and signal processing. Besides, the technical solutions found to these issues are closely interconnected and determine the capability of the system to successfully fulfill the requirements posed by each application domain. The large and heterogeneous amount of data collected in a WSN need to be efficiently processed in order to improve the end-user comprehension and control of the observed phenomena. The thesis focuses on a) the development of centralized and distributed data processing methods optimized for the requirements and characteristics of the considered application domains, and b) the design and implementation of suitable system architectures and protocols with respect to critical application-specific parameters. The thesis comprehends a summary and nine publications, equally divided over three different application domains, i.e. wireless automation, structural health monitoring (SHM) and indoor situation awareness (InSitA). In the first one, a wireless joystick control system for human adaptive mechatronics is developed. Also, the effect of packet losses on the performance of a wireless control system is analyzed and validated with an unstable process. A remotely reconfigurable, time synchronized wireless system for SHM enables a precise estimation of the modal properties of the monitored structure. Furthermore, structural damages are detected and localized through a distributed data processing method based on the Goertzel algorithm. In the context of InSitA, the short-time, low quality acoustic signals collected by the nodes composing the network are processed in order to estimate the number of people located in the monitored indoor environment. In a second phase, text- and language-independent speaker identification is performed. Finally, device-free localization and tracking of the movements of people inside the monitored indoor environment is achieved by means of distributed processing of the radio signal strength indicator (RSSI) signals. The results presented in the thesis demonstrate the adaptability of WSNs to different application domains and the importance of an optimal co-design of the system architecture and data processing methods

ERK Pathway in Activated, Myofibroblast-Like, Hepatic Stellate Cells: A Critical Signaling Crossroad Sustaining Liver Fibrosis.

Fibrogenic progression of chronic liver disease, whatever the etiology, is characterized by persistent chronic parenchymal injury, chronic activation of inflammatory response, and sustained activation of liver fibrogenesis, and of pathological wound healing response. A critical role in liver fibrogenesis is played by hepatic myofibroblasts (MFs), a heterogeneous population of α smooth-muscle actin—positive cells that originate from various precursor cells through a process of activation and transdifferentiation. In this review, we focus the attention on the role of extracellular signal-regulated kinase (ERK) signaling pathway as a critical one in modulating selected profibrogenic phenotypic responses operated by liver MFs. We will also analyze major therapeutic antifibrotic strategies developed in the last two decades in preclinical studies, some translated to clinical conditions, designed to interfere directly or indirectly with the Ras/Raf/MEK/ERK signaling pathway in activated hepatic MFs, but that also significantly increased our knowledge on the biology and pathobiology of these fascinating profibrogenic cells

Hepatic Myofibroblasts: A Heterogeneous and Redox-Modulated Cell Population in Liver Fibrogenesis

During chronic liver disease (CLD) progression, hepatic myofibroblasts (MFs) represent a unique cellular phenotype that plays a critical role in driving liver fibrogenesis and then fibrosis. Although they could originate from different cell types, MFs exhibit a rather common pattern of pro-fibrogenic phenotypic responses, which are mostly elicited or sustained both by oxidative stress and reactive oxygen species (ROS) and several mediators (including growth factors, cytokines, chemokines, and others) that often operate through the up-regulation of the intracellular generation of ROS. In the present review, we will offer an overview of the role of MFs in the fibrogenic progression of CLD from different etiologies by focusing our attention on the direct or indirect role of ROS and, more generally, oxidative stress in regulating MF-related phenotypic responses. Moreover, this review has the purpose of illustrating the real complexity of the ROS modulation during CLD progression. The reader will have to keep in mind that a number of issues are able to affect the behavior of the cells involved: a) the different concentrations of reactive species, b) the intrinsic state of the target cells, as well as c) the presence of different growth factors, cytokines, and other mediators in the extracellular microenvironment or of other cellular sources of ROS