Requirements Of Real Applications Research Articles

A Practical Group Authentication Scheme for Smart Devices in IoT

Internet of things (IoT) is used to provide real-time data collection and analysis of the target area by the cooperation of low-cost devices. The authentication towards multiple devices has become the research hot-spot considering of the requirement in real applications. Sensitivity and privacy of data have caused widespread concerns because low-cost devices are neither tamper-proof nor capable of performing public key cryptography efficiently. However, many researchers only focus on the authentication between two devices in the network. They ignore the authentication among group devices attached to one network. In this paper, we propose A Practical Group Authentication Scheme for Smart Devices in IoT. Note that one device group to be authenticated consists of a group of smart devices. The personal digital assistant (PDA) as the group leader controls authentication operations in its group. From the security analysis, our scheme can resist to various attacks. In addition, the performance analysis shows that our scheme has lower computational cost than the existing scheme.

Stretchable Fiber Biofuel Cell by Rewrapping Multiwalled Carbon Nanotube Sheets.

The fiber-type biofuel cell is attractive as an implantable energy source because the fiber can modify various structures and the wound can be stitched like a suture. In addition, in daily life, the biofuel cell is forced by human motion, and stretchability is a critical requirement for real applications. Therefore, we introduce a new type of highly stretchable, stable, soft fiber biofuel cell with microdiameter dimensions as an energy harvester. The completed biofuel cell operated well in fluids similar to human fluids, such as 20 mM phosphate-buffered 0.14 M NaCl solution (39.5 mW/cm2) and human serum (36.6 μW/cm2). The fiber-type biofuel cell can be reversibly stretched up to 100% in tensile direction while producing sustainable electrical power. In addition, the unique rewrapping structure, which traps the enzyme between multiwalled carbon nanotube sheets, enormously enhanced the stability of the biofuel cell when the biofuel cell was repeatedly stretched (the power density retention increased from 63 to 99%) and operated in human serum (the power density retention increased from 29 to 86%). The fiber can be easily woven into various structures, such as McKibben braid yarn, and scaled up by series and parallel connections.

Decomposition method for fast computation of gigapixel-sized Fresnel holograms on a graphics processing unit cluster.

A parallel computation method for large-size Fresnel computer-generated hologram (CGH) is reported. The method was introduced by us in an earlier report as a technique for calculating Fourier CGH from 2D object data. In this paper we extend the method to compute Fresnel CGH from 3D object data. The scale of the computation problem is also expanded to 2gigapixels, making it closer to real application requirements. The significant feature of the reported method is its ability to avoid communication overhead and thereby fully utilize the computing power of parallel devices. The method exhibits three layers of parallelism that favor small to large scale parallel computing machines. Simulation and optical experiments were conducted to demonstrate the workability and to evaluate the efficiency of the proposed technique. A two-times improvement in computation speed has been achieved compared to the conventional method, on a 16-node cluster (one GPU per node) utilizing only one layer of parallelism. A 20-times improvement in computation speed has been estimated utilizing two layers of parallelism on a very large-scale parallel machine with 16 nodes, where each node has 16 GPUs.

Performance Evaluation of RIPng, EIGRPv6 and OSPFv3 for Real Time Applications

In this modern Internet era and the transition to IPv6, routing protocols must adjust to assist this transformation. RIPng, EIGRPv6 and OSPFv3 are the dominant IPv6 IGRP (Interior Gateway Routing Protocols). Selecting the best routing protocol among the available is a critical task, which depends upon the network requirement and performance parameters of different real time applications. The primary motivation of this paper is to estimate the performance of these protocols in real time applications. The evaluation is based on a number of criteria including: network convergence duration, Http Page Response Time, DB Query Response Time, IPv6 traffic dropped, video packet delay variation and video packet end to end delay. After examining the simulation results, a conclusion will be extracted to reveal the findings of which protocol performs the best upon implementation within a IPv6 WAN. OPNET modeler simulator is used to evaluate the accomplishment of these protocols. To get the results, three scenarios are designed, one for each protocol.

Hydrogen Generation through Solar Photocatalytic Processes: A Review of the Configuration and the Properties of Effective Metal-Based Semiconductor Nanomaterials

Photocatalytic water splitting and organic reforming based on nano-sized composites are gaining increasing interest due to the possibility of generating hydrogen by employing solar energy with low environmental impact. Although great efforts in developing materials ensuring high specific photoactivity have been recently recorded in the literature survey, the solar-to-hydrogen energy conversion efficiencies are currently still far from meeting the minimum requirements for real solar applications. This review aims at reporting the most significant results recently collected in the field of hydrogen generation through photocatalytic water splitting and organic reforming, with specific focus on metal-based semiconductor nanomaterials (e.g., metal oxides, metal (oxy)nitrides and metal (oxy)sulfides) used as photocatalysts under UVA or visible light irradiation. Recent developments for improving the photoefficiency for hydrogen generation of most used metal-based composites are pointed out. The main synthesis and operating variables affecting photocatalytic water splitting and organic reforming over metal-based nanocomposites are critically evaluated.

Optimized Parallel Implementation of Extended Kalman Filter Using FPGA

There are enormous numbers of applications that require the use of tracking algorithms to predict the future states of a system according to its previous accumulated states. Thus, many efficient techniques are widely adopted to estimate the future states of a system at every point in time to get the desired performance levels. Kalman filter is a popular and an efficient method for online estimations for linear measurements. Extended Kalman Filter (EKF), on the other hand, is more suited for nonlinear measurements. However, EKF algorithm is well known to be computationally intensive, and may not achieve the strict requirements of real time applications. This issue has motivated researchers to consider the use of parallel processing platforms such as Field Programmable Gate Arrays (FPGAs) and Graphic Processing Units (GPUs) to meet the real time requirements. This paper provides an optimized parallel architecture for EKF using FPGA. Our approach exploits many optimization and parallel techniques such as pipelining, loop unrolling, dataflow, and inlining; and utilizes the inherently parallel architecture nature of FPGAs to accelerate the estimation process. Our experimental analyses show that our optimized implementation of EKF can achieve better results when compared to other implementations using GPU and multicore platforms. Moreover, higher performance levels can be achieved when operating on larger data sizes. This is due to our proposed optimization techniques that we have applied, and the exploited inherent parallelism among EKF operations.

Energy-Efficient Algorithm to Construct the Information Potential Field in WSNs

The information gradient-based routing and navigation protocols have been proved to be effective when collecting data from the distributed wireless sensor networks, because the data collector can achieve the global objective through local greedy decision based on the information gradient. An efficient method to establish this information gradient is to solve a discrete approximation to the harmonic function, which is called information potential field (IPF). However, the energy-efficient and quick convergence methods to construct the IPF should be fully investigated to trade off the energy efficiency and the quality of the IPF, especially in the large-scale networks with high dynamics. In this paper, two algorithms are proposed to efficiently construct the IPF, including <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hierarchical skeleton-based construction algorithm</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">value estimating substitution algorithm</i> . Both algorithms obey the typical hypotheses on WSN settings and the gossip-styled propagation principle. In addition, we propose the advanced approaches to construct the IPF to tackle the challenges of its practical applications, such as obstacles, task priorities, and sensor energy budget. Comprehensive simulation results show the feasibility of the proposed algorithms, which can reduce the number of iterations to reach a convergence status by 80% so as to conserve energy, and they perform well considering the requirements of real applications.

Neutrosophic number linear programming method and its application under neutrosophic number environments

In real world, there exists determinate and/or indeterminate information. Hence, the indeterminate problems are inevitable and have to be taken into account in optimization problems. Then, a neutrosophic number (NN) is very suitable for expressing determinate and/or indeterminate information because a NN (\(z=a + bI\)) consists of its determinate part a and its indeterminate part bI for \(a,b\in R\), where the symbol “I” denotes indeterminacy and R is all real numbers. This paper firstly presents some basic operations of NNs and a neutrosophic function involving NNs, which is simply called a NN function and then develops a NN linear programming (NNLP) method to handle NN optimization problems. Moreover, a numerical example and an application of production planning are provided, respectively, to show the solving method and application of NNLP problems. In general, the NNLP method yields the basic NN solutions. Further, the possible ranges of the optimal solution are discussed when the indeterminacy I is specified as a possible interval ranges corresponding to actual requirements in real applications.

The Nanoporous RP-20 Carbon Electrode As a Model for Energy Storage and Conversion Systems – Studied with µ CT, SAXS and SANS Methods

There is no doubt that the electrochemical energy storage and conversion devices are the key components in future’s smart energy grids enabling on-demand and efficient energy usage. During the last thirty years, various carbon based materials have been studied and used in the energy storage and conversion devices: supercapacitors, fuel cells and batteries. Despite the efforts made so far, there is still a strong need for better understanding of processes related to the mass transport properties of electrolyte ions inside of the porous electrode materials driven by their morphology [1,2]. It is obvious that electrochemical performance (durability/efficiency) of such a device depends on the rate of the charging and discharging processes inside the electrodes that in turn are strongly influenced by the properties of the carbon material and electrolyte used (i.e., the specific surface area, pore shape, size/volume, wettability, ionophilicity/ionophobicity, dielectrical permittivity and polarizability, ect.) [3,4]. It has been recognized that different carbon materials exhibit different properties such as the surface area, hierarchical porosity, electrical and ionic conductivity, water uptake rate as well as the electrocatalytic activity [5,6]. The scientific goal of this study is in depth understanding of the fundamental properties of the carbon materials and their functionality at the molecular and atomic level under non-polarized conditions. For this purpose the nanoporous carbon RP-20 [7] as a main electrode component has been used and correlation between morphology (i.e., pore shape, size of the pores) and instance wetting (filling density) of the carbon material matrix with the solvent was determined. Keeping in mind real application requirements, the primarily used 1M NaClO4 solution in dimethyl carbonate (DMC) and ethylene carbonate (EC) (1:1 wt%) solvent mixture as an electrolyte [3] has been studied. Several independent methods – x-ray microcomputed tomography (µCT) [8], small-angle neutron scattering (SANS) [9], and small-angle x-ray scattering (SAXS) [10-12] were applied for characterization of the following systems: RP-20 1MNaClO4 in EC:DMC; RP-20 in EC:DMC or RP-20 1MNaClO4 in D2O. It is rather difficult to simultaneously determine/distinguish the structure or dynamic effects on the efficiency and durability of the electrochemical devices (i.e., inhomogeniously/randomly distributed pores filled with electrolyte contributing during the charge and discharge cycling processes), therefore the above listed methods have contributed to an improved awareness of the nature of complex systems in steady state (non-polarized) conditions. Based on the µCT measurements, the linear attenuation coefficient values and filling densities were obtained and calculated. To determine the shape and size of the pores for nanoporous RP-20 electrode and to observe the influence/interaction of the electrolyte ions dissolved in aqueous and non-aqueous solvent (i.e., differences in filling of the pores) SANS method was applied. SAXS measurements were performed in order to collect quantitative morphological and structural information for nanoporous RP-20 powder and RP-20 electrode material (e.g., surface area, pore size, pore structure, binder effect).

Semantic localization

Improvements in sensor and wireless network enable accurate, automated, instant determination and dissemination of a user’s or objects position. The new enabler of location-based services (LBSs) apart from the current ubiquitous networking infrastructure is the enrichment of the different systems with semantics information, such as time, location, individual capability, preference and more. Such semantically enriched system-modeling aims at developing applications with enhanced functionality and advanced reasoning capabilities. These systems are able to deliver more personalized services to users by domain knowledge with advanced reasoning mechanisms, and provide solutions to problems that were otherwise infeasible. This approach also takes user’s preference and place property into consideration that can be utilized to achieve a comprehensive range of personalized services, such as advertising, recommendations, or polling. This paper provides an overview of indoor localization technologies, popular models for extracting semantics from location data, approaches for associating semantic information and location data, and applications that may be enabled with location semantics. To make the presentation easy to understand, we will use a museum scenario to explain pros and cons of different technologies and models. More specifically, we will first explore users’ needs in a museum scenario. Based on these needs, we will then discuss advantages and disadvantages of using different localization technologies to meet these needs. From these discussions, we can highlight gaps between real application requirements and existing technologies, and point out promising localization research directions. By identifying gaps between various models and real application requirements, we can draw a roadmap for future location semantics research.

Colorimetric Biosensor for Detection of Cancer Biomarker by Au Nanoparticle-Decorated Bi2Se3 Nanosheets.

The colorimetric biosensors have attracted intensive interest; however, their relatively low sensitivity limits their applications in clinic detection. Herein, we develop an effective colorimetric biosensor based on highly catalytic active Au nanoparticle-decorated Bi2Se3 (Au/Bi2Se3) nanosheets. Au/Bi2Se3 nanosheets are facilely synthesized by simply sonicating Au precursor with the as-synthesized Bi2Se3 nanosheets in aqueous solution. Because of the low redox potential and typical topological insulating properties, Bi2Se3 nanosheets is capable of providing and accumulating electrons on its surface. Such unique properties of Bi2Se3 nanosheets contribute to strong synergistic catalytic effects with Au nanoparticles, particularly when Au/Bi2Se3 nanosheets are utilized for catalyzing the reduction of 4-nitrophenol (4-NP) by NaBH4 (K = 386.67 s-1g-1). The excellent catalytic activity of Au/Bi2Se3 nanosheets can be "switched off" upon treatment of antibody of cancer biomarker such as anticarcinoembryonic antibody (anti-CEA). Addition of the corresponding antigen such as cancer biomarker carcinoembryonic antibody (CEA) can successively help "switch on" the catalytic activity of Au/Bi2Se3 nanosheets, where the resuming degree however depends on the antigen concentration. This cancer biomarker depended catalytic behavior therefore allows Au/Bi2Se3 nanosheets to be employed as a colorimetric sensor for detection of a particular cancer biomarker, for the reduction of 4-nitrophenol (4-NP) by NaBH4 itself involves apparent color change. The sensor shows high sensitivity and selectivity for the cancer biomarker, even for a concentration as low as 160 pg/mL for CEA, which fully satisfies the requirement for real clinical applications. The developed colorimetric sensor shows good generality for detection of different types of cancer biomarkers, such as α-fetoprotein (AFP) and prostate-specific antigen (PSA). Furthermore, real clinic sample analyzing result shows that the prepared biosensor is efficient for detection of CEA, providing an alternative method in cancer diagnosis.

Fast Algorithm for Multimodal Image Registration with DTCWT

Objective: To perform image registration with sub band features computed using dual tree complex wavelets and reducing the computation time in registration. Methods/Statistical Analysis: The input images are preprocessed with Gaussian filters; features are extracted from dual tree sub bands. The dominant features are retained with feature selection process to minimize complexity in registration. Translation of images based on similar features is carried out using singular value decomposition. A refinement phase further registers the images considering similarities in features. The proposed algorithm is modeled in MATLAB, registration processes are modeled from fundamental equations. Test images are considered for validation. The test images are geometrically transformed with knows sets of translation, scale and rotational parameters. The two images are registered and the corresponding transformation parameters are compared. Critical points in the images are considered as reference points for validation. Findings: The proposed algorithm performs registration of all images with less than 10% error. The PSNR computed for all sets of data base is greater than 32dB. With dual tree sub bands, the unique features with 150, 450 and 750 orientations are captured thus the features are twice more compared with DWT features. The feature selection algorithm considers the orientations in all three directions thus improving registration process. SVD algorithm optimizes the complexity in transformation process and refinement phase. Elimination of false features and use of appropriate sub band features has reduced the registration time by 76% thus meeting the requirement for real time applications in micro air vehicles. Application/Improvements: The improvement in computation time and registration accuracy of this algorithm is suitable for MAVs moving with speed of 20-30kmph. Multilevel decomposition will further improve the registration process, hardware accelerators can reduce computation time to few milliseconds.

3D Visual Tracking of an Articulated Robot in Precision Automated Tasks.

The most compelling requirements for visual tracking systems are a high detection accuracy and an adequate processing speed. However, the combination between the two requirements in real world applications is very challenging due to the fact that more accurate tracking tasks often require longer processing times, while quicker responses for the tracking system are more prone to errors, therefore a trade-off between accuracy and speed, and vice versa is required. This paper aims to achieve the two requirements together by implementing an accurate and time efficient tracking system. In this paper, an eye-to-hand visual system that has the ability to automatically track a moving target is introduced. An enhanced Circular Hough Transform (CHT) is employed for estimating the trajectory of a spherical target in three dimensions, the colour feature of the target was carefully selected by using a new colour selection process, the process relies on the use of a colour segmentation method (Delta E) with the CHT algorithm for finding the proper colour of the tracked target, the target was attached to the six degree of freedom (DOF) robot end-effector that performs a pick-and-place task. A cooperation of two Eye-to Hand cameras with their image Averaging filters are used for obtaining clear and steady images. This paper also examines a new technique for generating and controlling the observation search window in order to increase the computational speed of the tracking system, the techniques is named Controllable Region of interest based on Circular Hough Transform (CRCHT). Moreover, a new mathematical formula is introduced for updating the depth information of the vision system during the object tracking process. For more reliable and accurate tracking, a simplex optimization technique was employed for the calculation of the parameters for camera to robotic transformation matrix. The results obtained show the applicability of the proposed approach to track the moving robot with an overall tracking error of 0.25 mm. Also, the effectiveness of CRCHT technique in saving up to 60% of the overall time required for image processing.

PEN: a power law–enhanced network design for high efficiency multicore architecture

SummaryWe propose a heterogeneous on‐chip interconnection aiming at high efficiency multicore processors. An ideal on‐chip interconnection should have low latency, high throughput, low power consumption, and high scalability. However, these metrics are usually contradictory with each other. Besides, a design should focus on the requirements of real applications. We investigate the characteristics of several parallel applications. It is found that the distribution of traffic is similar as the power law. We also discovered hot spot traffic, as well as bursty traffic from applications. Meanwhile, the average injection rate of parallel applications is relatively low. The proposed network is based on a dual‐net concentrated mesh, where 2 physical networks are implemented for processing different messages and improve throughput. A diagonal interconnection is used in the central part of the network for alleviating the traffic hot spot without significant hardware overhead. We evaluate the proposed design with synthetic traffic and real applications by using a simulator. Results indicate that, on average for 8 applications, the network latency of the proposed design has reduced by 32% compared with regular mesh. Concerning efficiency when executing applications, the average energy delay product of the proposed design is 52.7% and 29.7% better than mesh and concentrate mesh, respectively.

Redundancy Allocation for Multistate Systems With Component Dependencies and Load Sharing

Binary-state and component independent assumptions will lead to doubtful and misleading redundancy allocation schemes which may not satisfy the reliability requirements for real engineering applications. Most published works proposed methods to remove the first assumption by studying the degradation cases where multiple states of a component are from the best state to the degradation states then to the completely failed state. Fewer works focused on removing the second assumption and they only discussed dependent failures which are only a special case of component dependency. This work uses the Semi-Markov process to describe a two-component system for redundancy allocation. In this work, multiple states of a component are represented by multiple output levels, which are beyond the scope of degradation, and the component dependency is not limited to failure dependency only. The load sharing is also taken care of in the proposed work. The optimal redundancy allocation scheme is obtained by solving the corresponding redundancy allocation optimization problem with the reliability measure, the system availability, obtained through the Semi-Markov process model being constraint. Two case studies are presented, demonstrating the applicability of the propose method.

Trapping and attenuating broadband vibroacoustic energy with hyperdamping metamaterials

We introduce a class of engineered metamaterials for the purpose of attenuating and trapping spectrally broadband vibration and acoustic energy. The physical phenomenon realized to effect such wideband energy dissipation performance is termed hyperdamping since it is the consequence of eliminating fundamental stiffness contributions within the material system so as to asymptotically enhance damping properties. A strategically sculpted elastomer topology is geometrically constrained and embedded in a poroelastic matrix to realize the metamaterial platform. Finite element model analyses guide design of the embedded hyperdamping inclusions while experimental studies on dynamic force transmissibility and acoustical absorption coefficient provide conclusive evidence that hyperdamping phenomena facilitate wideband energy dissipation in a lightweight material system that is not subject to the limitations of conventional resonance- or bandgap-based attenuation effects. The hyperdamping metamaterials thus meet the often conflicting performance requirements of real applications where broadband vibrations and noise must be abated using lightweight material solutions.

In Vivo Lighted Fluorescence via Fenton Reaction: Approach for Imaging of Hydrogen Peroxide in Living Systems.

By virtue of its high sensitivity and rapidity, Fenton reaction has been demonstrated as a powerful tool for in vitro biochemical analysis; however, in vivo applications of Fenton reaction still remain to be exploited. Herein, we report, for the first time, the design, formation and testing of Fenton reaction for in vivo fluorescence imaging of hydrogen peroxide (H2O2). To realize in vivo fluorescence imaging of H2O2 via Fenton reaction, a functional nanosphere, Fc@MSN-FDNA/PTAD, is fabricated from mesoporous silica nanoparticle (MSN), a Fenton reagent of ferrocene (Fc), ROX-labeled DNA (FDNA), and a cationic perylene derivative (PTAD). The ferrocene molecules are locked in the pore entrances of MSN, and exterior of MSN is covalently immobilized with FDNA. As a key part, PTAD acts as not only the gatekeeper of MSN but also the efficient quencher of ROX. H2O2 can permeate into the nanosphere and react with ferrocene to product hydroxyl radical (·OH) via Fenton reaction, which cleaves FDNA to detach ROX from PTAD, thus in turn, lights the ROX fluorescence. Under physiological condition, H2O2 can be determined from 5.0 nM to 1.0 μM with a detection limit of 2.4 nM. Because of the rapid kinetics of Fenton reaction and high specificity for H2O2, the proposed method meets the requirement for real applications. The feasibility of Fc@MSN-FDNA/PTAD for in vivo applications is demonstrated for fluorescence imaging of exogenous and endogenous H2O2 in cells and mice. We expect that this work will not only contribute to the H2O2-releated studies but also open up a new way to exploit in vivo Fenton reaction for biochemical research.

Fabrication and Characterization of Vibration and Wind Energy Harvesters Using Multilayer Free-Standing Piezoelectric Thick Films

This article demonstrates the feasibility of fabricating energy harvesters based on piezoelectric cantilevers with a free-standing thick-film structure. Demonstrator devices have been designed, built, and evaluated in a range of mechanical coupling configurations to harvest energy from machinery vibrations and weak air flow. In terms of wideband vibration energy harvesters, arrays of the individual harvesters were assembled onto plastic test circuit boards integrated with diode bridge rectifiers. The harvesters were designed with different dimensions, and various tip masses were attached on the tip of the cantilevers to individually tune the resonant frequencies. The assembled harvesters were tested under harmonic vibration conditions. Great potential of harvesting vibration energy and broadening working bandwidth has been exhibited. In terms of the harvester for weak air flow, two individual cantilever devices were assembled on the chassis of a free-spinning fan. Permanent magnets were fixed on the blades of the fan as well as on the cantilevers. The device was tested in an open fluidic environment. The air flow was successfully transferred to axial oscillations, thus driving the cantilevers bending up and down. Possibilities of such devices being optimized to meet the requirements of real applications of self-powered wireless sensor networks can be foreseen.

An Overview of Location Semantics Technologies and Applications

A localization system is a coordinate system for describing the world, organizing the world, and controlling the world. Without a coordinate system, we cannot specify the world in mathematical forms; we cannot regulate processes that may involve spatial collisions; we cannot even automate a robot for physical actions. This paper provides an overview of indoor localization technologies, popular models for extracting semantics from location data, approaches for associating semantic information and location data, and applications that may be enabled with location semantics. To make the presentation easy to understand, we will use a museum scenario to explain the pros and cons of different technologies and models. More specifically, we will first explore users' needs in a museum scenario. Based on these needs, we will then discuss advantages and disadvantages of using different localization technologies to meet these needs. From these discussions, we can highlight gaps between real application requirements and existing technologies, and point out promising localization research directions. Similarly, we will also discuss context information required by different applications and explore models and ontologies for connecting users, objects, and environment factors with semantics. By identifying gaps between various models and real application requirements, we can draw a roadmap for future location semantics research.

Fabrication and Characterisation of Vibration and Wind Energy Harvesters Using Multi-layer Free-standing Piezoelectric Thick-films

This paper demonstrates the feasibility of fabricating energy harvesters based on piezoelectric cantilevers with a free-standing thick-film structure. Demonstrator devices have been designed, built and evaluated in a range of mechanical coupling configurations, in order to harvest energy from machinery vibrations and weak air flow. In terms of wideband vibration energy harvesters, arrays of the individual harvesters were assembled onto plastic test circuit boards integrated with diode bridge rectifiers. The harvesters were designed with different dimensions and various tip masses were attached on the tip of the cantilevers in order to individually tune the resonant frequencies. The assembled harvesters were tested under harmonic vibration conditions. Great potential of harvesting vibration energy and broadening working bandwidth has been exhibited. In terms of the harvester for weak air flow, two individual cantilever devices were assembled on the chassis of a free-spinning fan. Permanent magnets were fixed on the blades of the fan as well as the cantilevers. The device was tested in an open fluidic environments. The air flow has been successfully transferred to axial oscillations thus driving the cantilevers bending up and down. Possibilities of such devices being optimised to meet the requirements of real applications of self-powered wireless sensor networks can be foreseen.