Search

Piezoelectric Energy Harvesters (PEHs) are typically employed to provide additional source of energy for a sensing system. However, studies show that a PEH can be also used as a sensor to acquire information about the source of vibration by analysing the produced voltage signal. This opens a possibility to create Simultaneous Energy Harvesting and Sensing (SEHS) system, where a single piece of hardware, a PEH, acts as both, a harvester and as a sensor. This raises a question if it is possible to design a bi-functional PEH device with optimal harvesting and sensing performance. In this work, we propose a bi-objective PEH design optimisation framework and show that there is a trade-off between energy harvesting efficiency and sensing accuracy within a PEH design space. The proposed framework is based on an extensive vibration (strain and acceleration) dataset collected from a real-world operational cable-stayed bridge in New South Wales, Australia. The bridge acceleration data is used as an input for a PEH numerical model to simulate a voltage signal and estimate the amount of produced energy. The numerical PEH model is based on the Kirchhoff-Love plate and isogeometric analysis. For sensing, convolutional neural network AlexNet is trained to identify traffic speed labels from voltage CWT (Continuous Wavelet Transform) images. In order to improve computational efficiency of the approach, a kriging metamodel is built and genetic algorithm is used as an optimisation method. The results are presented in the form of Pareto fronts in three design spaces.

Intelligent reflecting surfaces (IRSs) have been proposed as a promising technology to enhance signal transmissions in high-frequency bands. Up to now, the research on the performance of large networks with IRSs is still in its infancy. In this article, we study a Poisson bipolar network with line segment blockages and reflectors. By deriving the probability that an IRS can successfully reflect a signal from a transmitter to a receiver and the distribution of the distance traveled by the reflected signal, the performance impact of deploying IRSs on the signal propagation is investigated. The aggregated interference through reflective paths via IRSs is derived by modeling the IRSs as additional interfering sources with non-uniformly distributed interfering power in different directions. With these results, the signal-to-interference-and-noise ratio (SINR) and the achievable rate are further derived, where a characteristic function and the inverse theorem are adopted to handle the complicated channel fading of reflective signals. From the analysis, IRSs have a great potential to enhance the network performance, but the tradeoff between signal enhancement and reflective interference is important. That is, the performance gain suffers from a diminishing return with a large IRS fraction due to the growth of reflective interference.

We design a system, SolarGest, which can recognize hand gestures near a solar-powered device by analyzing the patterns of the photocurrent. SolarGest is based on the observation that each gesture interferes with incident light rays on the solar panel in a unique way, leaving its discernible signature in harvested photocurrent. Using solar energy harvesting laws, we develop a model to optimize design and usage of SolarGest. To further improve the robustness of SolarGest under non-deterministic operating conditions, we combine dynamic time warping with Z-score transformation in a signal processing pipeline to pre-process each gesture waveform before it is analyzed for classification. We evaluate SolarGest with both conventional opaque solar cells as well as emerging see-through transparent cells. Our experiments demonstrate that SolarGest achieves 99% for six gestures with a single cell and 95% for fifteen gesture with a $2\times 2$2×2 solar cell array. The power measuement study suggests that SolarGest consume 44% less power compared to light sensor based systems.

Metamaterials have been explored to achieve extraordinary response to incident radiations, not accessible to conventional materials. Metamaterial attributes are derived from spatially arranged sub-wavelength resolved metaelements. Additive manufacturing technologies offer capabilities to fabricate complex metastructures with novel remarkable responses. Two-photon polymerization (TPP) based additive manufacturing has gained popularity due to its exceptional precision and minimal processing stages. However, the major bottleneck in the development of TPP based fabrication is its dependence on engineered/proprietary/expensive two-photon active materials for initiation of polymerization process. Here, we propose an acrylate and carbon dot composite resin for additive manufacturing of all-carbon, all-dielectric metamaterials. Two-photon irradiation induces photo-induced electron transfer from the surface states of carbon quantum dots, which in turn initiates the TPP. The composite resin is devoid of any other two-photon dye/initiator. The effect of carbon dot concentration on fabrication process parameters and fabrication resolution have been systematically investigated. Several linear/complex planar and 3D structures have been fabricated with high replication fidelity. As a proof-of-concept, the composite resinhas been used for the realization of resonant and chiral metamaterials. Furthermore, theoretical calculations are also performed to evaluate the optical activity of these metastructures. Our results demonstrate steps towards realizing all-dielectric, all-carbon based metamaterials.

Floating car data (FCD) refers to the motion and sensor data produced by moving vehicles on the road. Given that traffic management authorities and drivers can benefit from FCD enormously, there is an urgency to develop efficient FCD collection and dissemination techniques that scale with peak road traffic. In this paper, we present CarAgent, a message exchange protocol that periodically collects and uploads FCD to data centres with the minimal utilisation of existing mobile network resources. We also show how CarAgent can be easily extended to efficiently disseminate FCD to all vehicles in a target area using Dedicated Short Range Communication (DSRC), a recently released wireless communication standard for vehicles. We analytically derive the key performance metrics of CarAgent and validate them with simulations. We evaluate CarAgent using microscopic simulation of road traffic in real street maps while incorporating wireless protocol details of Long Term Evolution (LTE) and DSRC. Simulation results confirm that, compared to the state-of-the-art, CarAgent consumes 50% less LTE resources for FCD collection. For FCD dissemination, CarAgent consumes 45% less DSRC resources while improving the speed of dissemination significantly.

Advances in nanotechnology are paving the way for a new generation of sensor networks at the nanoscale, promising radically new applications in medical, biological, and chemical fields. At the nanoscale, it is difficult to use large batteries for prolonged operations, necessitating energy harvesting as the most viable solution for these nanosensor networks. Unfortunately, the rate at which energy can be harvested at the nanoscale may not be sufficient to simultaneously power all of the conventional device components, including the microprocessor, memory, sensor, and the communication radio. We propose a simplified architecture for energy-harvesting nanosensor networks that uses the energy signatures of monitored events for efficient event recognition at the sink. Using the instantaneous harvested energy to transmit a short pulse of proportional amplitude, the proposed architecture obviates the need for several conventional sensor node elements, including the microprocessor, memory, and sensor. In this article, we validate the feasibility of the architecture using a novel application of nanosensor networks for microscopic monitoring of chemical reactors, and we demonstrate that different types of reactions can be detected accurately at a remote sink.

Recent advancements in energy-harvesting hardware have created an opportunity for realizing batteryless wearables for continuous and pervasive human activity recognition (HAR). Unfortunately, power consumption of accelerometers used in conventional HAR is relatively high compared to the amount of power that can be harvested practically, which limits the usefulness of energy harvesting. Here, the authors present and evaluate a novel energy-harvesting wearable sensor architecture, HAR from Kinetic Energy (HARKE), that doesn't require using an accelerometer. Using off-the-shelf products, the authors demonstrate that the voltage of a kinetic harvester exhibits distinguishable patterns to distinctly infer human activities. Their results demonstrate that HARKE is as accurate as an accelerometer-based HAR system, yet consumes only a small fraction of the limited harvested energy.

Wireless mesh networks (WMN) have attracted considerable interest in recent years as a convenient, flexible and low-cost alternative to wired communication infrastructures in many contexts. However, the great majority of research on metropolitan-scale WMN has been centered around maximization of available bandwidth, suitable for non-real-time applications such as Internet access for the general public. On the other hand, the suitability of WMN for mission-critical infrastructure applications remains by and large unknown, as protocols typically employed in WMN are, for the most part, not designed for real-time communications. In this paper, we describe the Smart Transport and Roads Communications (STaRComm) project at National ICT Australia (NICTA), which sets a goal of designing a wireless mesh network architecture to solve the communication needs of the traffic control system in Sydney, Australia. This system, known as SCATS (Sydney Coordinated Adaptive Traffic System)and used in over 100 cities around the world, connects a hierarchy of several thousand devices -- from individual traffic light controllers to regional computers and the central Traffic Management Centre (TMC)-- and places stringent requirements on the reliability and latency of the data exchanges. We discuss our experience in the deployment of an initial testbed consisting of 7 mesh nodes placed at intersections with traffic lights, and share the results and insights learned from our measurements and initial trials in the process.

One of the critical issues in Web-based e-commerce has been how to efficiently and effectively integrate and query heterogeneous, diverse e-catalogs. We propose an integration framework for building and querying catalogs. Our approach is based on a hybrid of peer-to-peer data sharing paradigm and Web-services architecture. Peers in our system serve as domain-specific data integration mediators. Links between peers are established based on the similarity of the domain they represent. The relationships are used for routing queries among peers. As the number of catalogs involved grow larger, the need for filtering irrelevant data sources will become increasingly high. We apply a summarisation technique to summarise the content of catalogs. The summaries are used to pre-selecting data sources that are relevant to a user query.One of the critical issues in Web-based e-commerce has been how to efficiently and effectively integrate and query heterogeneous, diverse e-catalogs. We propose an integration framework for building and querying catalogs. Our approach is based on a hybrid of peer-to-peer data sharing paradigm and Web-services architecture. Peers in our system serve as domain-specific data integration mediators. Links between peers are established based on the similarity of the domain they represent. The relationships are used for routing queries among peers. As the number of catalogs involved grow larger, the need for filtering irrelevant data sources will become increasingly high. We apply a summarisation technique to summarise the content of catalogs. The summaries are used to pre-selecting data sources that are relevant to a user query.

The major bottleneck in fabrication of engineered 3D nanostructures is the choice of materials. Adding functionality to these nanostructures is a daunting task. In order to mitigate these issues, we report a two-photon patternable all carbon material system which can be used to fabricate fluorescent 3D micro/nanostructures using two-photon lithography, with subwavelength resolution. The synthesized material system eliminates the need to use conventional two-photon absorbing materials such as two-photon dyes or two-photon initiators. We have used two different trifunctional acrylate monomers and carbon dots, synthesized hydrothermally from a polyphenolic precursor, to formulate a two-photon processable resin. Upon two-photon excitation, photogenerated electrons in the excited states of the carbon dots facilitate the free radical formation at the surface of the carbon dots. These radicals, upon interaction with vinyl moieties, enable cross-linking of acrylate monomers. Free-radical induced two-photon polymerization of acrylate monomers without any conventional proprietary two-photon absorbing materials was accomplished at an ultrafine subwavelength resolution of 250 nm using 800 nm laser excitation. The effect of critical parameters such as average laser power, carbon dot concentration, and radiation exposure were determined for the fabrication of one-, two-, and three-dimensional functional nanostructures, applicable in a range of domains where fluorescence and toxicity are of the utmost importance. A fabrication speed as high as 100 mm/s was achieved. The ability to fabricate functional 3D micro-/nanostructures is anticipated to instigate a paradigm shift in various areas such as metamaterials, energy storage, drug delivery, and optoelectronics to name a few.