HYBRYDOWY SYSTEM NAWIGACJI DO UŻYTKU WEWNĄTRZ POMIESZCZEŃ

This article describes the design and implementation of a hybrid in-building navigation system. The word hybrid has a twofold meaning in this case. On the one hand, it refers to the use of two tracking methods: demanding (beacons) and not requiring an electronic device (radio tomography imaging). On the other hand, it specifies several commercial wireless communication protocols that make up the presented system. Ultimately, the network created in this way will be designed to provide the user with location and navigation services with increased accuracy and reliability. The text describes both the topology of created networks, methods of communication between devices and their hardware layer, as well as the effects of work resulting from the actual test object.Artykuł opisuje projekt i sposób realizacji hybrydowego systemu nawigacji wewnątrzbudynkowej. Słowo hybrydowy ma w tym przypadku dwojakie znaczenie. Z jednej strony odnosi się do zastosowania dwóch metod namierzania: wymagającej (radiolatarnie) i nie wymagającej posiadania urządzenia elektronicznego (obrazowanie radio-tomograficzne). Z drugiej wyszczególnia kilka komercyjnych protokołów komunikacji bezprzewodowej składającej się na przedstawiony system. Docelowo utworzone w ten sposób sieć będzie miała za zadanie świadczyć użytkownikowi usługi lokalizacyjne i nawigacyjne o zwiększonej dokładności i niezawodności. Treść tekstu opisuje zarówno topologię tworzonych sieci, metody komunikacji między urządzeniami oraz ich warstwę sprzętową jak i efekty prac wynikłych na podstawie rzeczywistego obiektu testowego

Polar communications: Status and recommendations. Report of the Science Working Group

The capabilities of the existing communication links within the polar regions, as well as between the polar regions and the continental United States, are summarized. These capabilities are placed in the context of the principal scientific disciplines that are active in polar research, and in the context of how scientists both utilize and are limited by present technologies. Based on an assessment of the scientific objectives potentially achievable with improved communication capabilities, a list of requirements on and recommendations for communication capabilities necessary to support polar science over the next ten years is given

A Network Tomography Approach for Traffic Monitoring in Smart Cities

Traffic monitoring is a key enabler for several planning and management activities of a Smart City. However, traditional techniques are often not cost efficient, flexible, and scalable. This paper proposes an approach to traffic monitoring that does not rely on probe vehicles, nor requires vehicle localization through GPS. Conversely, it exploits just a limited number of cameras placed at road intersections to measure car end-to-end traveling times. We model the problem within the theoretical framework of network tomography, in order to infer the traveling times of all individual road segments in the road network. We specifically deal with the potential presence of noisy measurements, and the unpredictability of vehicles paths. Moreover, we address the issue of optimally placing the monitoring cameras in order to maximize coverage, while minimizing the inference error, and the overall cost. We provide extensive experimental assessment on the topology of downtown San Francisco, CA, USA, using real measurements obtained through the Google Maps APIs, and on realistic synthetic networks. Our approach provides a very low error in estimating the traveling times over 95% of all roads even when as few as 20% of road intersections are equipped with cameras

A network tomography approach for traffic monitoring in smart cities

Various urban planning and managing activities required by a Smart City are feasible because of traffic monitoring. As such, the thesis proposes a network tomography-based approach that can be applied to road networks to achieve a cost-efficient, flexible, and scalable monitor deployment. Due to the algebraic approach of network tomography, the selection of monitoring intersections can be solved through the use of matrices, with its rows representing paths between two intersections, and its columns representing links in the road network. Because the goal of the algorithm is to provide a cost-efficient, minimum error, and high coverage monitor set, this problem can be translated into an optimization problem over a matroid, which can be solved efficiently by a greedy algorithm. Also as supplementary, the approach is capable of handling noisy measurements and a measurement-to-path matching. The approach proves a low error and a 90% coverage with only 20% nodes selected as monitors in a downtown San Francisco, CA topology --Abstract, page iv

Body attenuation and path loss exponent estimation for RSS-based positioning in WSN

The influence of the human body in antenna systems has significant impact in the received signal strength (RSS) of wireless transmissions. Accounting for body effect is generally considered as being able to improve position estimation based on RSS measurements. In this work we perform several experiments with a wireless sensor network, using a sensor node equipped with an inertial measurement unit (IMU), in order to obtain the relative orientation between the sensor node and multiple anchor nodes. A model of the RSS attenuation induced by the body was created using experimental measurements in a controlled environment and applied to a real-time positioning system. A path loss exponent (PLE) estimation method using RSS information from neighbor anchors was also implemented and evaluated. Weighted centroid localization (WCL) algorithm was the positioning method used in this work. When the sensor node was placed on the user’s body, accounting for body effect produced negligible improvements (6%) in the best-case scenario and consistently degraded accuracy under real conditions, whether the node was placed on the user’s body (in the order of 3%), 10 cm away (from 14% to 35%) or 20 cm away from the body (from 42% to 105%) for results in the 70th percentile. The PLE estimation method showed improvements (in the order of 11%) when the sensor node is further away from the body. Results demonstrate that the distance between sensor node and the body has an extremely important influence on the accuracy of the position estimate.This work has been supported by FCT (Fundação para a Ciência e Tecnologia) in the scope of the project UID/EEA/04436/2013. Helder D. Silva is supported by FCT under the grant SFRH/BD/78018/2011info:eu-repo/semantics/publishedVersio

Master of Science

thesisLocation of an object or person in in-door environments is a vital piece of in-formation. Traditionally, global positioning system-based devices do an excellent job in providing location information but are limited in in-door environments due to lack of an unobstructed line of sight. Wireless environments, with their extreme sensitivity to the positioning of objects inside them, provide excellent opportunities for obtaining location information of subjects. Received signal strength (RSS) based localization methods attract special attention as they can be readily implemented with "off-the-shelf" hardware and software. Device-free localization (DFL) presents a new and promising dimension in RSS-based localization research by providing a non-intrusive method of localization. However, existing RSS-based localization schemes assume a fixed or known transmit power. Any unexpected change in transmit power, not known to the receivers in the wireless network, can introduce errors in location estimate. Previous work has shown that meticulously planned power attacks can result in expected errors, in location of a transmitting sensor, in excess of 18 meters for an area of 75 X 50 m2. We find that the localization error in DFL can increase by four-fold when under power attack of 15 dB amplitude by multiple adversaries. Certain nonadversarial circumstances can also lead to unexpected changes in transmit power which would result in increased localization error. In this thesis, we focus on detection and isolation of wireless sensor nodes in a network which vary their transmit power to cause unexpected changes in RSS measurements and lead to increased localization errors in DFL. In the detection methods presented in this thesis, we do not require a training phase and hence, our methods are robust for use in dynamic environments where the training data may get obsolete frequently. We present our work with special focus on DFL methods using wireless sensor networks. However, the methods developed are generic and can be easily extended to active localization methods using both wireless sensor networks (WSN) and IEEE 802.11 protocols. To evaluate the effectiveness of our detection method, we perform extensive experiments in indoor settings using a network of 802.15.4 (Zigbee) compliant wireless sensor nodes and present evaluation results in the form of average detection rate, ROC curves, probability of missed detection and false alarm

Flexible Electronics for Large Area Sensing and Stimulation

Advancements in soft materials and hybrid flexible electronics have enabled developments in flexible circuits and wearables. Where rigid electronics are extremely precise over small physical areas, flexible electronics have the capability to sense over large curved areas. From the onset of epidermal electronics and flexible transistors, there have been great advancements in sensing over soft curved objects, such as human skin or brain tissue. This thesis focuses on hybrid flexible electronics to sense and stimulate over large areas. The aim of the systems presented is to provide insight into complex navigation and sensor processing systems. In addition to the design, fabrication, and characterization of each device, several important characteristics of each device are investigated: material choice, curvature limits, and device sensitivity. The first device presented in this thesis uses strain gauges to track the bending of neurosurgery navigation stylets for catheter placement. The strain gauge fabrication and characterization is presented. Adhesive testing, stylet bending modeling, and noise techniques are also discussed as they were found to be critical components of the system. The device's limit of detection is 1 mm tip displacement. The purpose of the second set of devices presented is to gain object information from curved or edged robotic structures. Three sensing modes were explored: piezoelectric, strain, and capacitive. The piezoelectric sensor was founded to have a 6.7 times increase in sensitivity when an open-cell foam compliant layer is used. The strain sensor was found to have a gauge factor of 2.83 on a silicone layer and 1.5 on a polymer layer. The combination of the piezoelectric and strain sensing modes is presented. The capacitive sensor is able to detect object shape using inverse problem mathematical techniques. The third device and system presented is a flexible electrode array for stimulating the electroreceptors of electric fish. The spatial and temporal control of a conformal stimulation array enables the decoding of motor signals in the brain. The array fabrication and system development is presented. Surface modification of the electrode array successfully altered the surface energy of the array to match that of the fish for the optimal array-fish interface. In summary, the development and integration of these flexible electronic devices has been achieved. It was found that the interface between the flexible electronic devices and binding objects is critical to device sensitivity and reliability