Embedded fibre Bragg grating array sensors in aluminium alloy matrix by ultrasonic consolidation

Fibre Bragg Grating (FBG) array sensors have been successfully embedded in aluminium alloy matrix by ultrasonic consolidation (UC) technique. The temperature and loading responses of the embedded FBG arrays have been systematically characterised. The embedded grating sensors exhibit an average temperature sensitivity of ~36pm/°C, which is three times higher than that of normal FBGs, and a loading responsivity of ~0.1nm/kg within the dynamic range from 0kg to 3kg. This initial experiment clearly demonstrates that FBG array sensors can be embedded in metal matrix together with other passive and active fibres to fabricate smart materials to monitor the operation and health of engineering structures.

Discriminating ambulation using a smart sensing plate

The automated sensing scheme described in this paper has the potential to automatically capture, discriminate and classify transients in gait. The mechanical simplicity of the walking platform offers advantages over standard force plates. There is less restriction on dimensions offering the opportunity for multi-contact and multiple steps. This addresses the challenge of patient targeting and the evaluation of patients in a variety of ambulatory applications. In this work the sensitivity of the distributive tactile sensing method has been investigated experimentally. Using coupled time series data from a small number of sensors, gait patterns are compared with stored templates using a pattern recognition algorithm. By using a neural network these patterns were interpreted classifying normal and affected walking events with an accuracy of just under 90%. This system has potential in gait analysis and rehabilitation as a tool for early diagnosis in walking disorders, for determining response to therapy and for identifying changes between pre and post operative gait. Copyright © 2009 by ASME.

The Open Data Smart City: A Case Study of Smart City Progress through Open Data Initiatives

Smart cities, cities that are supported by an extensive digital infrastructure of sensors, databases and intelligent applications, have become a major area of academic, governmental and public interest. Simultaneously, there has been a growing interest in open data, the unrestricted use of organizational data for public viewing and use. Drawing on Science and Technology Studies (STS), Urban Studies and Political Economy, this thesis examines how digital processes, open data and the physical world can be combined in smart city development, through the qualitative interview-based case study of a Southern Ontario Municipality, Anytown. The thesis asks what are the challenges associated with smart city development and open data proliferation, is open data complimentary to smart urban development; and how is expertise constructed in these fields? The thesis concludes that smart city development in Anytown is a complex process, involving a variety of visions, programs and components. Although smart city and open data initiatives exist in Anytown, and some are even overlapping and complementary, smart city development is in its infancy. However, expert informants remained optimistic, faithful to a technologically sublime vision of what a smart city would bring. The thesis also questions the notion of expertise within the context of smart city and open data projects, concluding that assertions of expertise need to be treated with caution and scepticism when considering how knowledge is received, generated, interpreted and circulates, within organizations.

Development of a Wireless MEMS Multifunction Sensor System and Field Demonstration of Embedded Sensors for Monitoring Concrete Pavements, TR-637, 2016

Pavements tend to deteriorate with time under repeated traffic and/or environmental loading. By detecting pavement distresses and damage early enough, it is possible for transportation agencies to develop more effective pavement maintenance and rehabilitation programs and thereby achieve significant cost and time savings. The structural health monitoring (SHM) concept can be considered as a systematic method for assessing the structural state of pavement infrastructure systems and documenting their condition. Over the past several years, this process has traditionally been accomplished through the use of wired sensors embedded in bridge and highway pavement. However, the use of wired sensors has limitations for long-term SHM and presents other associated cost and safety concerns. Recently, micro-electromechanical sensors and systems (MEMS) and nano-electromechanical systems (NEMS) have emerged as advanced/smart-sensing technologies with potential for cost-effective and long-term SHM. This two-pronged study evaluated the performance of commercial off-the-shelf (COTS) MEMS sensors embedded in concrete pavement (Final Report Volume I) and developed a wireless MEMS multifunctional sensor system for health monitoring of concrete pavement (Final Report Volume II).

Collaborative Systems for Smart Environments: Trends and Challenges

Part 1: Introduction

A Collaborative Mobile Crowdsensing System for Smart Cities

Nowadays words like Smart City, Internet of Things, Environmental Awareness surround us with the growing interest of Computer Science and Engineering communities. Services supporting these paradigms are definitely based on large amounts of sensed data, which, once obtained and gathered, need to be analyzed in order to build maps, infer patterns, extract useful information. Everything is done in order to achieve a better quality of life. Traditional sensing techniques, like Wired or Wireless Sensor Network, need an intensive usage of distributed sensors to acquire real-world conditions. We propose SenSquare, a Crowdsensing approach based on smartphones and a central coordination server for time-and-space homogeneous data collecting. SenSquare relies on technologies such as CoAP lightweight protocol, Geofencing and the Military Grid Reference System.

Effectively positioning water loss event in smart water networks

With the eye-catching advances in sensing technologies, smart water networks have been attracting immense research interest in recent years. One of the most overarching tasks in smart water network management is the reduction of water loss (such as leaks and bursts in a pipe network). In this paper, we propose an efficient scheme to position water loss event based on water network topology. The state-of-the-art approach to this problem, however, utilizes the limited topology information of the water network, that is, only one single shortest path between two sensor locations. Consequently, the accuracy of positioning water loss events is still less desirable. To resolve this problem, our scheme consists of two key ingredients: First, we design a novel graph topology-based measure, which can recursively quantify the "average distances" for all pairs of senor locations simultaneously in a water network. This measure will substantially improve the accuracy of our positioning strategy, by capturing the entire water network topology information between every two sensor locations, yet without any sacrifice of computational efficiency. Then, we devise an efficient search algorithm that combines the "average distances" with the difference in the arrival times of the pressure variations detected at sensor locations. The viable experimental evaluations on real-world test bed (WaterWiSe@SG) demonstrate that our proposed positioning scheme can identify water loss event more accurately than the best-known competitor.

Towards a smart semi-active prosthetic leg: preliminary assessment and testing

This paper presents a development of a semi-active prosthetic knee, which can work in both active and passive modes based on the energy required during the gait cycle of various activities of daily livings (ADLs). The prosthetic limb is equipped with various sensors to measure the kinematic and kinetic parameters of both prosthetic limbs. This prosthetic knee is designed to be back-drivable in passive mode to provide a potential use in energy regeneration when there negative energy across the knee joint. Preliminary test has been performed on transfemoral amputee in passive mode to provide some insight to the amputee/prosthesis interaction and performance with the designed prosthetic knee.

Metrological characterization of sensors and instrumentation for distribution grid monitoring and electrical asset diagnostics

The Smart Grid needs a large amount of information to be operated and day by day new information is required to improve the operation performance. It is also fundamental that the available information is reliable and accurate. Therefore, the role of metrology is crucial, especially if applied to the distribution grid monitoring and the electrical assets diagnostics. This dissertation aims at better understanding the sensors and the instrumentation employed by the power system operators in the above-mentioned applications and studying new solutions. Concerning the research on the measurement applied to the electrical asset diagnostics: an innovative drone-based measurement system is proposed for monitoring medium voltage surge arresters. This system is described, and its metrological characterization is presented. On the other hand, the research regarding the measurements applied to the grid monitoring consists of three parts. The first part concerns the metrological characterization of the electronic energy meters’ operation under off-nominal power conditions. Original test procedures have been designed for both frequency and harmonic distortion as influence quantities, aiming at defining realistic scenarios. The second part deals with medium voltage inductive current transformers. An in-depth investigation on their accuracy behavior in presence of harmonic distortion is carried out by applying realistic current waveforms. The accuracy has been evaluated by means of the composite error index and its approximated version. Based on the same test setup, a closed-form expression for the measured current total harmonic distortion uncertainty estimation has been experimentally validated. The metrological characterization of a virtual phasor measurement unit is the subject of the third and last part: first, a calibrator has been designed and the uncertainty associated with its steady-state reference phasor has been evaluated; then this calibrator acted as a reference, and it has been used to characterize the phasor measurement unit implemented within a real-time simulator.

Surveillance risks in IoT applied to smart cities

Nowadays, cities deal with unprecedented pollution and overpopulation problems, and Internet of Things (IoT) technologies are supporting them in facing these issues and becoming increasingly smart. IoT sensors embedded in public infrastructure can provide granular data on the urban environment, and help public authorities to make their cities more sustainable and efficient. Nonetheless, this pervasive data collection also raises high surveillance risks, jeopardizing privacy and data protection rights. Against this backdrop, this thesis addresses how IoT surveillance technologies can be implemented in a legally compliant and ethically acceptable fashion in smart cities. An interdisciplinary approach is embraced to investigate this question, combining doctrinal legal research (on privacy, data protection, criminal procedure) with insights from philosophy, governance, and urban studies. The fundamental normative argument of this work is that surveillance constitutes a necessary feature of modern information societies. Nonetheless, as the complexity of surveillance phenomena increases, there emerges a need to develop more fine-attuned proportionality assessments to ensure a legitimate implementation of monitoring technologies. This research tackles this gap from different perspectives, analyzing the EU data protection legislation and the United States and European case law on privacy expectations and surveillance. Specifically, a coherent multi-factor test assessing privacy expectations in public IoT environments and a surveillance taxonomy are proposed to inform proportionality assessments of surveillance initiatives in smart cities. These insights are also applied to four use cases: facial recognition technologies, drones, environmental policing, and smart nudging. Lastly, the investigation examines competing data governance models in the digital domain and the smart city, reviewing the EU upcoming data governance framework. It is argued that, despite the stated policy goals, the balance of interests may often favor corporate strategies in data sharing, to the detriment of common good uses of data in the urban context.

Development of textile wearable chemical sensors

In this elaborate, a textile-based Organic Electrochemical Transistor (OECT) was first developed for the determination of uric acid in wound exudate based on the conductive polymer poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS), which was then coupled to an electrochemically gated textile transistor consisting of a composite of iridium oxide particles and PEDOT:PSS for pH monitoring in wound exudate. In that way a sensor for multiparameter monitoring of wound health status was assembled, including the ability to differentiate between a wet-dry status of the smart bandage by implementing impedance measurements exploiting the OECT architecture. Afterwards, for both wound management as well as generic health status tracking applications, a glass-based calcium sensor was developed employing polymeric ion-selective membranes on a novel architecture inspired by the Wrighton OECT configuration, which was later converted to a Proof-of-Concept textile prototype for wearable applications. Lastly, in collaboration with the King Abdullah University of Science and Technology (KAUST, Thuwal, Saudi Arabia) under the supervision of Prof. Sahika Inal, different types of ion-selective thiophene-based monomers were used to develop ion-selective conductive polymers to detect sodium ion by different methods, involving standard potentiometry and OECT-based approaches. The textile OECTs for uric acid detection performances were optimized by investigating the geometry effect on the instrumental response and the properties of the different textile materials involved in their production, with a special focus on the final application that implies the operativity in flow conditions to simulate the wound environment. The same testing route was followed for the multiparameter sensor and the calcium sensor prototype, with a particular care towards the ion-selective membrane composition and electrode conditioning protocol optimization. The sodium-selective polymer electrosynthesis was optimized in non-aqueous environments and was characterized by means of potentiostatic and potentiodynamic techniques coupled with Quartz Crystal Microbalance and spectrophotometric measurements.

Designing real nanotube-based gas sensors

Using a combination of density functional theory and recursive Green's functions techniques, we present a full description of a large scale sensor, accounting for disorder and different coverages. Here, we use this method to demonstrate the functionality of nitrogen-rich carbon nanotubes as ammonia sensors as an example. We show how the molecules one wishes to detect bind to the most relevant defects on the nanotube, describe how these interactions lead to changes in the electronic transport properties of each isolated defect, and demonstrate that there are significative resistance changes even in the presence of disorder, elucidating how a realistic nanosensor works.

Detection of catechol using mixed Langmuir-Blodgett films of a phospholipid and phthalocyanines as voltammetric sensors

The combination of metallic phthalocyanines (MPcs) and biomolecules has been explored in the literature either as mimetic systems to investigate molecular interactions or as supporting layers to immobilize biomolecules. Here, Langmuir-Blodgett (LB) films containing the phospholipid dimyristoyl phosphatidic acid (DMPA) mixed either with iron phthalocyanine (FePc) or with lutetium bisphthalocyanine (LuPc(2)) were applied as ITO modified-electrodes in the detection of catechol using cyclic voltammetry. The mixed Langmuir films of FePc + DMPA and LuPc(2) + DMPA displayed surface-pressure isotherms with no evidence of molecular-level interactions. The Fourier Transform Infrared (FTIR) spectra of the multilayer LB films confirmed the lack of interaction between the components. The DMPA and the FePc molecules were found to be oriented perpendicularly to the substrate, while LuPc(2) molecules were randomly organized. The phospholipid matrix induced a remarkable electrocatalytic effect on the phthalocyanines; as a result the mixed LB films deposited on ITO could be used to detect catechol with detection limits of 4.30 x 10(-7) and 3.34 x 10(-7) M for FePc + DMPA and LuPc(2) + DMPA, respectively. Results from kinetics experiments revealed that ion diffusion dominated the response of the modified electrodes. The sensitivity was comparable to that of other non-enzymatic sensors, which is sufficient to detect catechol in the food industry. The higher stability of the electrochemical response of the LB films and the ability to control the molecular architecture are promising for further studies with incorporation of biomolecules.

Probing magnetic and gold nanoparticles by using MAClevers (R) as ultrasensitive sensors

Magnetic AFM probes known as MAClevers (R) were employed for sensing picogram amounts of magnetic nanoparticles, based on the cantilever frequency shifts resulting from the magnetically induced adsorption of mass. By using organothiol functionalized magnetic nanoparticles, this analytical strategy was successfully extended to the detection of gold nanoparticles, as confirmed by confocal Raman microscopy.

Modeling and analysis of laminate composite plates with embedded active-passive piezoelectric networks

The objective of this work is to present the finite element modeling of laminate composite plates with embedded piezoelectric patches or layers that are then connected to active-passive resonant shunt circuits, composed of resistance, inductance and voltage source. Applications to passive vibration control and active control authority enhancement are also presented and discussed. The finite element model is based on an equivalent single layer theory combined with a third-order shear deformation theory. A stress-voltage electromechanical model is considered for the piezoelectric materials fully coupled to the electrical circuits. To this end, the electrical circuit equations are also included in the variational formulation. Hence, conservation of charge and full electromechanical coupling are guaranteed. The formulation results in a coupled finite element model with mechanical (displacements) and electrical (charges at electrodes) degrees of freedom. For a Graphite-Epoxy (Carbon-Fibre Reinforced) laminate composite plate, a parametric analysis is performed to evaluate optimal locations along the plate plane (xy) and thickness (z) that maximize the effective modal electromechanical coupling coefficient. Then, the passive vibration control performance is evaluated for a network of optimally located shunted piezoelectric patches embedded in the plate, through the design of resistance and inductance values of each circuit, to reduce the vibration amplitude of the first four vibration modes. A vibration amplitude reduction of at least 10 dB for all vibration modes was observed. Then, an analysis of the control authority enhancement due to the resonant shunt circuit, when the piezoelectric patches are used as actuators, is performed. It is shown that the control authority can indeed be improved near a selected resonance even with multiple pairs of piezoelectric patches and active-passive circuits acting simultaneously. (C) 2010 Elsevier Ltd. All rights reserved.