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

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

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

StreetlightSim: a simulation environment to evaluate networked and adaptive street lighting

Sustaining the operation of street lights incurs substantial financial and environmental cost. Consequently, adaptive lighting systems have been proposed incorporating ad-hoc networking, sensing, and data processing, in order to better manage the street lights and their energy demands. Evaluating the efficiency and effectiveness of these complex systems requires the modelling of vehicles, road networks, algorithms, and communication systems, yet tools are not available to permit this. This paper proposes StreetlightSim, a novel simulation environment combining OMNeT++ and SUMO tools to model both traffic patterns and adaptive networked street lights. StreetlightSim’s models are illustrated through the simulation of a simple example, and a more complex scenario is used to show the potential of the tool and the obtainable results. StreetlightSim has been made open-source, and hence is available to the community

A Structured Hardware/Software Architecture for Embedded Sensor Nodes

Owing to the limited requirement for sensor processing in early networked sensor nodes, embedded software was generally built around the communication stack. Modern sensor nodes have evolved to contain significant on-board functionality in addition to communications, including sensor processing, energy management, actuation and locationing. The embedded software for this functionality, however, is often implemented in the application layer of the communications stack, resulting in an unstructured, top-heavy and complex stack. In this paper, we propose an embedded system architecture to formally specify multiple interfaces on a sensor node. This architecture differs from existing solutions by providing a sensor node with multiple stacks (each stack implements a separate node function), all linked by a shared application layer. This establishes a structured platform for the formal design, specification and implementation of modern sensor and wireless sensor nodes. We describe a practical prototype of an intelligent sensing, energy-aware, sensor node that has been developed using this architecture, implementing stacks for communications, sensing and energy management. The structure and operation of the intelligent sensing and energy management stacks are described in detail. The proposed architecture promotes structured and modular design, allowing for efficient code reuse and being suitable for future generations of sensor nodes featuring interchangeable components