294 research outputs found

    A Hybrid Localization Approach in Wireless Sensor Networks by Resolving Flip Ambiguity

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    Localization has received considerable attention because many wireless sensor network applications require accurate knowledge of the locations of the sensors in the network. In the process the location calculation is achieved by either distance measurements or angle-of‐arrival measurement. However, the former technique suffers from flip ambiguity due to either the presence of insufficient reference points or uncertainties in the inter‐nodal distance measurements in a triangular network structure. A recently proposed quadrilateral structure (an extended complex version of a trilateration structure) can resolve flip ambiguity of a node in dense deployments under restricted orientations for anchors. However, the technique leaves open issues to consider imprecise inter‐nodal distances between all pairs of nodes as complexity increases due to measurement uncertainties in determining the locations. Moreover, both the structures (trilateral and quadrilateral) completely fail to resolve flip ambiguity in sparse node deployments as sufficient nodes are not available in order to determine the signs in calculated angles. On the other hand, AOA can provide the sign of the angles but requires expensive hardware calibration to provide a high‐level of accuracy in the measured angles. Therefore, there is a need of a localization technique that is cheaper, less complex, and robust by considering measurement uncertainties between all pair of nodes and more importantly, involves fewer reference nodes. The primary contributions of this thesis include a hybrid technique that uses low‐accuracy (cheap) AOA measurements along with erroneous distance measurements between each pair of nodes in a much simpler triangular network that corresponds to a sparse deployment. In our initial phase we develop mathematical models involving only two reference nodes that are able to resolve flip ambiguity a unknown node with a high probability of success even with an RMS error as high as 150 in the line‐of‐bearing estimate, which avoids the need for calibration in many practical situations. In later phases, we modelled our hybrid localization technique to accommodate imprecise inter‐nodal measurements between all pairs of nodes. In the final phase, we intend our localization technique to solve ambiguity in extremely sparse scenarios with non‐closed network structure that are yet to be solved by existing localizations approaches. Resolution of flip ambiguity is useful, not only to develop lower‐complexity localization techniques, but also for many lower‐layer network functionalities such as geographic routing, topology control, coverage and tracking, and controlled mobility when a large number of these nodes have to be deployed

    Visible Light Positioning using Received Signal Strength for Industrial Environments

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    There is a forecast for exceptional digital data traffic growth due to the digitisation of industrial applications using the internet of things. As a result, a great need for high bandwidth and faster transmission data rates for future wireless networks has emerged. One of the considered communication technologies that can assist in satisfying this demand is visible light communications (VLC). VLC is an emerging technology that uses the visible light spectrum by mainly utilising lightemitting diodes (LEDs) for simultaneous indoor lighting and high bandwidth wireless communication. Some of the applications of VLC are to provide high data rate internet in homes, offices, campuses, hospitals, and several other areas. One of these promising areas of application is for industrial wireless communications. The research project will provide a review of VLC applications intended for industrial applications with an emphasis on visible light positioning (VLP). In this research work, a three-dimensional (3D) positioning algorithm for calculating the location of a photodiode (PD) is presented. It solely works on measured powers from different LED sources and does not require any prior knowledge of the receiver’s height unlike other works in the literature. The performance of the proposed VLP algorithm in terms of positioning error is evaluated using two different trilateration algorithms, the Cayley–Menger determinant (CMD) and the Linear Least Squares (LLS) trilateration algorithms. The evaluation considers different scenarios, with and without receiver tilt, and with multipath reflections. Simulation results show that the CMD algorithm is more accurate and outperforms the LLS trilateration positioning algorithm. Furthermore, the proposed method has been experimentally assessed under two different LED configurations, with different degrees of receiver tilt, and in the presence of a fully stocked storage rack to examine the effect of multipath reflections on the performance of VLP systems. It was observed from simulations and experimental investigations that the widely used square LED-configuration results in position ambiguities for 3D systems while a non-lattice layout, such as a star-shaped configuration, is much more accurate. An experimental accuracy with a 3D median error of 10.5 cm was achieved using the CMD algorithm in a 4 m × 4 m × 4.1 m area with a horizontal receiver. Adding receiver tilt of 5◩ and 10◩ increases the median error by an average of 29% and 110%, respectively. The effect of reflections from the i storage rack has also been thoroughly examined using the two mentioned trilateration algorithms and showed to increase the 3D median positioning error by an average of 69% in the experimental testbed for the areas close to the storage rack. These results highlight the degrading effect of multipath reflections on VLP systems and the necessity to consider it when evaluating these systems. As the primary consideration for positioning systems in industrial environments is for mobile robots, the encouraging results in this thesis can be further improved though the use of a sensor fusion method

    Navigating the IoT landscape: Unraveling forensics, security issues, applications, research challenges, and future

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    Given the exponential expansion of the internet, the possibilities of security attacks and cybercrimes have increased accordingly. However, poorly implemented security mechanisms in the Internet of Things (IoT) devices make them susceptible to cyberattacks, which can directly affect users. IoT forensics is thus needed for investigating and mitigating such attacks. While many works have examined IoT applications and challenges, only a few have focused on both the forensic and security issues in IoT. Therefore, this paper reviews forensic and security issues associated with IoT in different fields. Future prospects and challenges in IoT research and development are also highlighted. As demonstrated in the literature, most IoT devices are vulnerable to attacks due to a lack of standardized security measures. Unauthorized users could get access, compromise data, and even benefit from control of critical infrastructure. To fulfil the security-conscious needs of consumers, IoT can be used to develop a smart home system by designing a FLIP-based system that is highly scalable and adaptable. Utilizing a blockchain-based authentication mechanism with a multi-chain structure can provide additional security protection between different trust domains. Deep learning can be utilized to develop a network forensics framework with a high-performing system for detecting and tracking cyberattack incidents. Moreover, researchers should consider limiting the amount of data created and delivered when using big data to develop IoT-based smart systems. The findings of this review will stimulate academics to seek potential solutions for the identified issues, thereby advancing the IoT field.Comment: 77 pages, 5 figures, 5 table

    Roadmap on signal processing for next generation measurement systems

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    Signal processing is a fundamental component of almost any sensor-enabled system, with a wide range of applications across different scientific disciplines. Time series data, images, and video sequences comprise representative forms of signals that can be enhanced and analysed for information extraction and quantification. The recent advances in artificial intelligence and machine learning are shifting the research attention towards intelligent, data-driven, signal processing. This roadmap presents a critical overview of the state-of-the-art methods and applications aiming to highlight future challenges and research opportunities towards next generation measurement systems. It covers a broad spectrum of topics ranging from basic to industrial research, organized in concise thematic sections that reflect the trends and the impacts of current and future developments per research field. Furthermore, it offers guidance to researchers and funding agencies in identifying new prospects.AerodynamicsMicrowave Sensing, Signals & System

    Culture of Communication in The Space of Co-Working Newsrooom of Online Media

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    Technology has driven a change in the mainstream media editorial room towards the digital newsroom. Media that develops models of editorial space integrated with digital platforms has been widely practiced. Including, designing a newsroom work place to support the performance needed by media companies that are adaptive to change. The newsroom or editorial room no longer uses a cubical arrangement, but rather a shared work space. This research uses a constructionist paradigm according to a qualitative research approach with a phenomenological method. The results showed that the co-working space newsroom accelerated the coordination for the production of �breaking news�. Communication in the newsroom becomes without bureaucracy, consequently it becomes free of structure and a cross levels. The implication is that the newsroom culture of the co-working space becomes more flexible and fast in collaboration with fellow journalists and writers to raise the latest news issues. Another implication is that the newsroom supports the creative ideas of media actors

    Terahertz Technology and Its Applications

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    The Terahertz frequency range (0.1 – 10)THz has demonstrated to provide many opportunities in prominent research fields such as high-speed communications, biomedicine, sensing, and imaging. This spectral range, lying between electronics and photonics, has been historically known as “terahertz gap” because of the lack of experimental as well as fabrication technologies. However, many efforts are now being carried out worldwide in order improve technology working at this frequency range. This book represents a mechanism to highlight some of the work being done within this range of the electromagnetic spectrum. The topics covered include non-destructive testing, teraherz imaging and sensing, among others

    Investigation into Smart Multifunctional Optical System-On-A-Chip Sensor Platform and Its Applications in Optical Wireless Sensor Networks

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    Wireless sensor networks (WSNs) have been widely used in various applications to acquire distributed information through cooperative efforts of sensor nodes. Most of the sensor nodes used in WSNs are based on mechanical or electrical sensing mechanisms, which are susceptible to electromagnetic interference (EMI) and can hardly be used in harsh environments. Although these disadvantages of conventional sensor nodes can be overcome by employing optical sensing methods, traditional optical systems are usually bulky and expensive, which can hardly be implemented in WSNs. Recently, the emerging technologies of silicon photonics and photonic crystal promise a solution of integrating a complete optical system through a complementary metal-oxide-semiconductor (CMOS) process. However, such an integration still remains a challenge. The overall objective of this dissertation work is to develop a smart multifunctional optical system-on-a-chip (SOC) sensor platform capable of both phase modulation and wavelength tuningfor heterogeneous sensing, and implement this platform in a sensor node to achieve an optical WSN for various applications, including those in harsh environments. The contributions of this dissertation work are summarized as follows. i)A smart multifunctional optical SOC sensor platform for heterogeneous sensing has beendeveloped for the first time. This platform can be used to perform phase modulation and demodulation in a low coherence interferometric configuration or wavelength tuning in a spectrum sensing configuration.The multifunctional optical sensor platform is developed through hybrid integration of a light source, an optical modulator, and multiple photodetectors. As the key component of the SOC platform, two types of modulators, namely, the opto-mechanical and electro-optical modulators, are investigated. For the first time, interrogating different types of heterogeneous sensors, including various Fabry-Perot (FP) sensors and fiber Bragg grating (FBG) sensors, with a single SOC sensor platform, is demonstrated. ii)Enhanced understanding of the principles of the multifunctional optical platform withanopto-mechanical modulator has been achieved.As a representative of opto-mechanical modulators, a microelectromechanical systems (MEMS) based FP tunable filter is thoroughly investigated through mechanical and optical modeling. The FP tunable filter is studied for both phase modulation and wavelength tuning, and design guidelines are developed based on the modeling and parametric studies. It is found that the MEMS tunable filter can achieve a large modulation depth, but it suffers from a trade-off between modulation depth and speed. iii) A novel silicon electro-optical modulator based on microring structures for optical phase modulation and wavelength tuning has been designed. To overcome the limitations of the opto-mechanical modulators including low modulation speed and mechanical instability, a CMOS compatible high speed electro-optical silicon modulator is designed, which combines microring and photonic crystal structures for phase modulation in interferometric sensors and makes use of two cascaded microrings for wavelength tuning in sensors that require spectrum domain signal processing. iv)A novel optical SOC WSN node has been developed. The optical SOC sensor platform and the associated electric circuit are integrated with a conventional WSN module to achieve an optical WSN node, enabling optical WSNs for various applications. v) A novel cross-axial dual-cavity FP sensor has been developed for simultaneous pressure and temperature sensing.Across-axial sensor is useful in measuring static pressures without picking up dynamic pressures in the presence of surface flows. The dual-cavity sensing structure is used for both temperature and pressure measurements without the need for another temperature sensor for temperature drift compensation. This sensor can be used in moderate to high temperature environments, which demonstrates the potential of using the optical WSN sensor node in a harsh environment

    1-D broadside-radiating leaky-wave antenna based on a numerically synthesized impedance surface

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    A newly-developed deterministic numerical technique for the automated design of metasurface antennas is applied here for the first time to the design of a 1-D printed Leaky-Wave Antenna (LWA) for broadside radiation. The surface impedance synthesis process does not require any a priori knowledge on the impedance pattern, and starts from a mask constraint on the desired far-field and practical bounds on the unit cell impedance values. The designed reactance surface for broadside radiation exhibits a non conventional patterning; this highlights the merit of using an automated design process for a design well known to be challenging for analytical methods. The antenna is physically implemented with an array of metal strips with varying gap widths and simulation results show very good agreement with the predicted performance
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