1,191 research outputs found
A Feasibility Study on Body-Worn Inertial Energy Harvesting during Walking and Running.
No full textThe ability to self-power electronic devices from the movement of the human body has application in a number of fields, including defence, sport and healthcare. To realise this vision, sufficient movement has to be experienced by such an energy harvester. In this poster, we present the results of a study that collected acceleration data from 10 people walking and running on a treadmill for 30 seconds each. Each participant was instrumented with six wireless tri-axial accelerometers at key locations around the body. This dataset was used to analyse the magnitude and frequency distribution of accelerations present on the human body, and subsequently estimate the theoretical maximum output power that can be obtained using an energy harvester
Design of a linearized magnetic spring for body-worn inertial energy harvesters
No full textA potential method for powering body-worn sensors is that of inertial energy harvesting; extracting energy from the movement of the human body. However, the frequencies typically present are <5 Hz, hence requiring physically large devices. A promising solution utilizes a magnetic spring, but these exhibit a non-linear relationship between force (and hence resonant frequency) and displacement. This paper describes a design for implementing a linearized magnetic spring. Finite element analysis is used to model this device and compare against those reported in the literature. Simulation results indicate that, compared to the state-of-the-art, this design exhibits improved linearity (2%) across a wider displacement range (±25 mm). A prototype has been fabricated, and the simulation results experimentally validated
Energy-Efficient Data Acquisition in Wireless Sensor Networks through Spatial Correlation
No full textThe application of Wireless Sensor Networks (WSNs) is restrained by their often-limited lifetime. A sensor node's lifetime is fundamentally linked to the volume of data that it senses, processes and reports. Spatial correlation between sensor nodes is an inherent phenomenon to WSNs, induced by redundant nodes which report duplicated information. In this paper, we report on the design of a distributed sampling scheme referred to as the 'Virtual Sampling Scheme' (VSS). This scheme is formed from two components: an algorithm for forming virtual clusters, and a distributed sampling method. VSS primarily utilizes redundancy of sensor nodes to get only a subset to sense the environment at any one time. Sensor nodes that are not sensing the environment are in a low-power sleep state, thus conserving energy. Furthermore, VSS balances the energy consumption amongst nodes by using a round robin method
Energy-Aware Simulation for Wireless Sensor Networks
No full textEnergy-aware sensor nodes are usually tightly energy-constrained, execute energy-efficient algorithms, have the ability to interrogate and control the devices used for storing and consuming energy, and often feature one or more sources of energy harvesting. Due to the cost, time and expertise required to deploy a Wireless Sensor Network (WSN), simulation is currently the most widely adopted evaluation method. Network simulation is well established for mobile ad hoc networks, using simulators such as the popular ns2. However, the differing characteristics and performance criteria of WSNs introduce additional simulation requirements, and this has resulted in a number of simulators and simulator extensions developed specifically for this purpose. This paper investigates the suitability of a number of state-of-the-art simulators for evaluating energy-aware WSNs, and subsequently proposes a novel structure for simulating energy-aware WSNs. The proposed structure provides diverse, flexible and extensible hardware and environment models, and integrates a structured architecture for embedded software to enhance the design of energy-aware sensor nodes. To illustrate an implementation of the structure, details of – and observations obtained using – an in-house simulator (WSNsim) are presented
Energy-efficient data acquisition for accurate signal estimation in wireless sensor networks
No full textLong-term monitoring of an environment is a fundamental requirement for most wireless sensor networks. Owing to the fact that the sensor nodes have limited energy budget, prolonging their lifetime is essential in order to permit long-term monitoring. Furthermore, many applications require sensor nodes to obtain an accurate estimation of a point-source signal (for example, an animal call or seismic activity). Commonly, multiple sensor nodes simultaneously sample and then cooperate to estimate the event signal. The selection of cooperation nodes is important to reduce the estimation error while conserving the network’s energy. In this paper, we present a novel method for sensor data acquisition and signal estimation, which considers estimation accuracy, energy conservation, and energy balance. The method, using a concept of ‘virtual clusters,’ forms groups of sensor nodes with the same spatial and temporal properties. Two algorithms are used to provide functionality. The ‘distributed formation’ algorithm automatically forms and classifies the virtual clusters. The ‘round robin sample scheme’ schedules the virtual clusters to sample the event signals in turn. The estimation error and the energy consumption of the method, when used with a generalized sensing model, are evaluated through analysis and simulation. The results show that this method can achieve an improved signal estimation while reducing and balancing energy consumption
Human-powered inertial energy harvesters: the effect of orientation, location and activity on obtainable power
No full textInertial energy harvesting is an emerging technology that can power electronic devices using energy scavenged from the motion of the human body. Owing to the relatively low frequencies associated with body motion (<3 Hz), the generated electrical power is typically in the range of a few µW; hence transduction must be optimized. Previous studies have investigated the effect of activity and harvester location on the obtained power; this work evaluates how power is also affected by the harvester’s orientation. Ten participants performed walking and running exercises, while tri-axial acceleration data were sampled at five locations on the body. The results show consistency in the optimal orientation of the harvester between people, but this orientation is not aligned with the axes of the body and limbs. During walking, the power harvested from the upper and lower body differs by an order of magnitude; however, this difference is less significant when running
Energy Devices for Sensor Networks: Properties for Simulation and Deployment
No full textRecent developments in microcontroller, radio transceiver, and energy harvesting device design now permit wireless sensor nodes to operate indefinitely from power scavenged from their environment. Many algorithms for conventional sensor networks assume that nodes run directly from non-rechargeable batteries and therefore attempt to conserve energy rather than carefully exploiting it when available. Effectively incorporating energy harvesting into wireless sensor network deployments, and simulations, poses unique problems related to energy-awareness and performance optimization. This paper presents a characterization of energy devices for sensor nodes and outlines their use in simulation and deployment. A case study of an energy-aware sensor node operating from a photovoltaic module and supercapacitor is explored. This paper also presents a modular software and hardware architecture which encourages energy-aware algorithm design and allows the automatic configuration of energy-aware sensor nodes
Energy Controlled Reporting for Industrial Monitoring Wireless Sensor Networks
No full textThis paper proposes a technique to extend the lifetime of a wireless sensor network through a combination of energy management and information control. Each sensor node locally decides its own network involvement as a result of balancing available energy resources with the information content of each packet. The information content is ascertained through a system of rules which describe prospective events in the sensed environment. These rules specify when reporting should occur, and the importance of each packet. While energy management and information content have been individually considered elsewhere, our technique utilizes a combination of both to incur greater benefits. Results obtained from a simulation depicting an industrial Wireless Sensor Network (WSN) monitoring a water pumping station have shown that a considerable increase in lifetime and connectivity can be obtained. In addition, when coupled with energy harvesting, our technique permits sustained operation
Augmenting forearm crutches with wireless sensors for lower limb rehabilitation
No full textForearm crutches are frequently used in the rehabilitation of an injury to the lower limb. The recovery rate is improved if the patient correctly applies a certain fraction of their body weight (specified by a clinician) through the axis of the crutch, referred to as partial weight bearing (PWB). Incorrect weight bearing has been shown to result in an extended recovery period or even cause further damage to the limb. There is currently no minimally invasive tool for long-term monitoring of a patient's PWB in a home environment. This paper describes the research and development of an instrumented forearm crutch that has been developed to wirelessly and autonomously monitor a patient's weight bearing over the full period of their recovery, including its potential use in a home environment. A pair of standard forearm crutches are augmented with low-cost off-the-shelf wireless sensor nodes and electronic components to provide indicative measurements of the applied weight, crutch tilt and hand position on the grip. Data are wirelessly transmitted between crutches and to a remote computer (where they are processed and visualized in LabVIEW), and the patient receives biofeedback by means of an audible signal when they put too much or too little weight through the crutch. The initial results obtained highlight the capability of the instrumented crutch to support physiotherapists and patients in monitoring usage
Energy-efficient street lighting through embedded adaptive intelligence
No full textStreetlights place a heavy demand on electricity usage, providing significant financial and environmental burdens. Consequently, initiatives to reduce energy consumption have been proposed, usually by turning off or dimming the streetlight. In this paper, we propose an adaptive lighting scheme based on traffic sensing, which adaptively adjusts streetlight brightness based on current traffic conditions. The algorithm has been validated through simulation using the SUMO and OMNeT++ tools and, for two different geographical locations, the energy consumption evaluated with respect to traffic speed and volume. The simulation results presented indicate that the proposed lighting scheme can consume up to 30% less energy when compared to the state-of-the-art
- …
