Energy-efficient data acquisition for accurate signal estimation in wireless sensor networks

Long-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

Flexible Integration of Alternative Energy Sources for Autonomous Sensing

Recent developments in energy harvesting and autonomous sensing mean that it is now possible to power sensors solely from energy harvested from the environment. Clearly this is dependent on sufficient environmental energy being present. The range of feasible environments for operation can be extended by combining multiple energy sources on a sensor node. The effective monitoring of their energy resources is also important to deliver sustained and effective operation. This paper outlines the issues concerned with combining and managing multiple energy sources on sensor nodes. This problem is approached from both a hardware and embedded software viewpoint. A complete system is described in which energy is harvested from both light and vibration, stored in a common energy store, and interrogated and managed by the node

An Instrumented Crutch for Monitoring Patients' Weight Distribution during Orthopaedic Rehabilitation

This paper discusses an instrumented forearm crutch that has been developed to monitor a patient’s weight bearing over the full period of their recovery, and that can potentially be used in a home environment. The crutch measures the applied weight, crutch tilt, and hand position on the grip. Data are transmitted wirelessly to a remote computer, where they are processed and visualized in LabVIEW. The results obtained from a successful pilot study highlight both the need for such an instrumented crutch and its ability to measure the weight being applied through a patient’s lower limb

Teaching old sensors New tricks: archetypes of intelligence

In this paper a generic intelligent sensor software architecture is described which builds upon the basic requirements of related industry standards (IEEE 1451 and SEVA BS- 7986). It incorporates specific functionalities such as real-time fault detection, drift compensation, adaptation to environmental changes and autonomous reconfiguration. The modular based structure of the intelligent sensor architecture provides enhanced flexibility in regard to the choice of specific algorithmic realizations. In this context, the particular aspects of fault detection and drift estimation are discussed. A mixed indicative/corrective fault detection approach is proposed while it is demonstrated that reversible/irreversible state dependent drift can be estimated using generic algorithms such as the EKF or on-line density estimators. Finally, a parsimonious density estimator is presented and validated through simulated and real data for use in an operating regime dependent fault detection framework

Use of the Extended Kalman Filter for State Dependent Drift Estimation in Weakly Nonlinear Sensors

A number of mechanisms are responsible for the generation of reversible or irreversible drift in the response of a sensor. In this letter, we discuss three approaches for the identification of reversible state dependent drift in sensors through the use of the Extended Kalman Filter. We compare their performance by simulation and demonstrate their validity by estimating the drift of an accelerometer, modeled as a weakly nonlinear system

Wireless Sensor Networks:A case study for Energy Efficient Environmental Monitoring

Energy efficiency is a key issue for wireless sensor networks, since sensors nodes can often be powered by non-renewable batteries. In this paper, we examine four MAC protocols in terms of energy consumption, throughput and energy efficiency. A forest fire detection application has been simulated using the well-known ns-2 in order to fully evaluate these protocols

Energy managed reporting for wireless sensor networks

In this paper, we propose a technique to extend the network lifetime of a wireless sensor network, whereby each sensor node decides its individual network involvement based on its own energy resources and the information contained in each packet. The information content is ascertained through a system of rules describing prospective events in the sensed environment, and how important such events are. While the packets deemed most important are propagated by all sensor nodes, low importance packets are handled by only the nodes with high energy reserves. Results obtained from simulations depicting a wireless sensor network used to monitor pump temperature in an industrial environment have shown that a considerable increase in the network lifetime and network connectivity can be obtained. The results also show that when coupled with a form of energy harvesting, our technique can enable perpetual network operatio

Resource Aware Sensor Nodes in Wireless Sensor Networks

Wireless sensor networks are continuing to receive considerable research interest due, in part, to the range of possible applications. One of the greatest challenges facing researchers is in overcoming the limited network lifetime inherent in the small locally powered sensor nodes. In this paper, we propose IDEALS, a system to manage a wireless sensor network using a combination of information management, energy harvesting and energy monitoring, which we label resource awareness. Through this, IDEALS is able to extend the network lifetime for important messages, by controlling the degradation of the network to maximise information throughput

A feasibility study on using inkjet technology, micropumps, and MEMs as fuel injectors for bipropellant rocket engines

Control over drop size distributions, injection rates, and geometrical distribution of fuel and oxidizer sprays in bi-propellant rocket engines has the potential to produce more efficient, more stable, less polluting rocket engines. This control also offers the potential of an engine that can be throttled, working efficiently over a wide range of output thrusts. Inkjet printing technologies, MEMS fuel atomizers, and piezoelectric injectors similar in concept to those used in diesel engines are considered for their potential to yield a new, more active injection scheme for a rocket engine. Inkjets are found to be unable to pump at sufficient pressures, and have possibly dangerous failure modes. Active injection is found to be feasible if high pressure drop along the injector plate are used. A conceptual design is presented and its basic behavior assessed