Showing papers in "IEEE Sensors Journal in 2011"

Lock-in Time-of-Flight (ToF) Cameras: A Survey

Abstract: This paper reviews the state-of-the art in the field of lock-in time-of-flight (ToF) cameras, their advantages, their limitations, the existing calibration methods, and the way they are being used, sometimes in combination with other sensors. Even though lock-in ToF cameras provide neither higher resolution nor larger ambiguity-free range compared to other range map estimation systems, advantages such as registered depth and intensity data at a high frame rate, compact design, low weight, and reduced power consumption have motivated their increasing usage in several research areas, such as computer graphics, machine vision, and robotics.

Graphene Sensors

Abstract: This paper reviews the potential of graphene as a material for fabricating various types of sensors. Graphene is a monolayer of carbon atoms which exhibits some remarkable electronic and mechanical properties and many of these properties lend themselves to sensor applications. The review attempts to be comprehensive in sensor types covering chemical and electrochemical sensors, magnetic and electric field sensors, optical sensors together with mass and strain sensors. The fact that graphene offers some advantages over this entire range of sensing modalities is an indication of its versatility and importance.

Atomic Sensors – A Review

Abstract: We discuss the basic physics and instrumentation issues related to high-performance physical and inertial sensors based on atomic spectroscopy. Recent work on atomic magnetometers, NMR gyroscopes, and atom interferometers is reviewed, with a focus on precision sensing of electromagnetic and gravitational fields and inertial motion. Atomic sensors have growing relevance to many facets of modern science and technology, from understanding the human brain to enabling precision navigation of moving platforms.

Energy-Efficient Distributed Spectrum Sensing for Cognitive Sensor Networks

Abstract: Reliability and energy consumption in detection are key objectives for distributed spectrum sensing in cognitive sensor networks. In conventional distributed sensing approaches, although the detection performance improves with the number of radios, so does the network energy consumption. We consider a combined sleeping and censoring scheme as an energy efficient spectrum sensing technique for cognitive sensor networks. Our objective is to minimize the energy consumed in distributed sensing subject to constraints on the detection performance, by optimally choosing the sleeping and censoring design parameters. The constraint on the detection performance is given by a minimum target probability of detection and a maximum permissible probability of false alarm. Depending on the availability of prior knowledge about the probability of primary user presence, two cases are considered. The case where a priori knowledge is not available defines the blind setup; otherwise the setup is called knowledge-aided. By considering a sensor network based on IEEE 802.15.4/ZigBee radios, we show that significant energy savings can be achieved by the proposed scheme.

A Robust, Adaptive, Solar-Powered WSN Framework for Aquatic Environmental Monitoring

Abstract: The paper proposes an environmental monitoring framework based on a wireless sensor network technology characterized by energy harvesting, robustness with respect to a large class of perturbations and real-time adaptation to the network topology. The fully designed and developed ad hoc system, based on clusters relying on a star topology, encompasses a sensing activity, a one-step local transmission from sensor nodes to the gateway, a remote data transmission from the gateway to the control center, data storage in a DB and real-time visualization. Hw and Sw modules have been either carefully selected or designed to guarantee a high quality of service, optimal solar energy harvesting, storage and energy awareness. A monitoring system integrating the outlined framework has been deployed in Queensland, Australia, for monitoring the underwater luminosity and temperature, information necessary to derive the health status of the coralline barrier. At the same time, acquired data can be used to provide quantitative indications related to cyclone formations in tropical areas.

Sensor Management: Past, Present, and Future

Abstract: Sensor systems typically operate under resource constraints that prevent the simultaneous use of all resources all of the time. Sensor management becomes relevant when the sensing system has the capability of actively managing these resources; i.e., changing its operating configuration during deployment in reaction to previous measurements. Examples of systems in which sensor management is currently used or is likely to be used in the near future include autonomous robots, surveillance and reconnaissance networks, and waveform-agile radars. This paper provides an overview of the theory, algorithms, and applications of sensor management as it has developed over the past decades and as it stands today.

Surface Crack Detection for Carbon Fiber Reinforced Plastic (CFRP) Materials Using Pulsed Eddy Current Thermography

Abstract: There is currently a requirement in many industries to inspect carbon fiber reinforced plastic (CFRP) components, such as those used in aircraft and for wind turbine blades to identify issues leading to potential failures. To detect surface cracks, pulsed eddy current (PEC) thermography is proposed as a powerful inspection technique, allowing the operator to observe the heating developed from the eddy current distribution in a structure using infrared imaging, detecting defects over a relatively wide area within a short time (of the order of milliseconds). In this paper, a PEC thermography inspection system for CFRP materials is studied and optimized. Using the system, the directional electrical conductivity of the CFRP material is observed through the surface heating pattern. Then, the normalized temperature rise and decay are investigated through the inspection of notches with varied depths and widths. The position invariance of the coil with respect to the notch along the fiber direction is also studied in the experiments. The work shows that PEC thermography can be used for defect detection and characterization through analysis of the surface heating pattern and the transient temperature change.

A Vibration-Based Electromagnetic Energy Harvester Using Mechanical Frequency Up-Conversion Method

Abstract: This paper presents a new vibration-based electromagnetic energy harvester using a mechanical frequency up-conversion method for harvesting energy from external low-frequency vibrations within a range of 1-10 Hz. The structure consists of a magnet placed on a diaphragm, a polystyrene cantilever carrying a pick-up coil, and a mechanical barrier which converts low-frequency vibrations to a higher frequency, hence increasing the efficiency of the system. The tested structure proved to generate 88.6 mV and 544.7 μW rms power output by up-converting 10-Hz external vibration to 394 Hz. The obtained power density is 184 μW/cm3, with a device volume of 2.96 cm3. An analytical model is developed to analyze the behavior of the energy harvester prototypes with various dimensions. The model predicts the performance parameters of the structures within 5% error range. The effect of scaling down the device dimensions is investigated through the developed model and fabricated prototypes. It is shown that the power density of the energy harvester is increased as its dimensions are scaled down, proving that the proposed structure is a good candidate to be used in low-power wireless microsystems operating at low-frequency vibrations.

Energy Harvesting and Remote Powering for Implantable Biosensors

Abstract: This paper reviews some popular techniques to harvest energy for implantable biosensors. For each technique, the advantages and drawbacks are discussed. Emphasis is placed on the inductive links that are able to deliver power wirelessly through the biological tissues and enable bidirectional data communication with the implanted sensors. Finally, high-frequency inductive links are described, focusing also on the power absorbed by the tissues.

Wide-Range Displacement Sensor Based on Fiber-Optic Fabry–Perot Interferometer for Subnanometer Measurement

Abstract: A displacement sensor with subnanometer resolution based on the fiber-optic Fabry-Perot interferometer is proposed. The Fabry-Perot cavity is formed between the fiber end face and a high reflectivity mirror, which effectively improved the contrast of the interference fringe. Meanwhile, since the measuring range and the demodulate resolution for Fabry-Perot sensor are difficult to be improved simultaneously, a novel demodulation method based on the combination of the Fourier transform method and the minimum mean square error estimation-based signal processing method has been presented, which is capable of providing subnanometer resolution and absolute measurement over a wide dynamic range. The experimental results show that the resolution of the sensor is up to 0.084 nm over a dynamic range of 3 mm.

Radio Frequency Time-of-Flight Distance Measurement for Low-Cost Wireless Sensor Localization

Abstract: Location-aware wireless sensor networks will enable a new class of applications, and accurate range estimation is critical for this task. Low-cost location determination capability is studied almost entirely using radio frequency received signal strength (RSS) measurements, resulting in poor accuracy. More accurate systems use wide bandwidths and/or complex time-synchronized infrastructure. Low-cost, accurate ranging has proven difficult because small timing errors result in large range errors. This paper addresses estimation of the distance between wireless nodes using a two-way ranging technique that approaches the Cramer-Rao Bound on ranging accuracy in white noise and achieves 1-3 m accuracy in real-world ranging and localization experiments. This work provides an alternative to inaccurate RSS and complex, wide-bandwidth methods. Measured results using a prototype wireless system confirm performance in the real world.

Wireless Magnetic Sensor Node for Vehicle Detection With Optical Wake-Up

Abstract: Vehicle detectors provide essential information about parking occupancy and traffic flow. To cover large areas that lack a suitable electrical infrastructure, wired sensors networks are impractical because of their high deployment and maintenance costs. Wireless sensor networks (WSNs) with autonomous sensor nodes can be more economical. Vehicle detectors intended for a WSN should be small, sturdy, low power, cost-effective, and easy to install and maintain. Currently available vehicle detectors based on inductive loops, ultrasound, infrared, or magnetic sensors do not fulfill the requirements above, which has led to the search for alternative solutions. This paper presents a vehicle detector which includes a magnetic and an optical sensor and is intended as sensor node for use with a WSN. Magnetic sensors based on magnetoresistors are very sensitive and can detect the magnetic anomaly in the Earth's magnetic field that results from the presence of a car, but their continuous operation would drain more than 1.5 mA at 3 V, hence limiting the autonomy of a battery-supplied sensor node. Passive, low-power optical sensors can detect the shadow cast by car that covers them, but are prone to false detections. The use of optical triggering to wake-up a magnetic sensor, combined with power-efficient event-based software, yields a simple, compact, reliable, low-power sensor node for vehicle detection whose quiescent current drain is 5.5 μA. This approach of using a low-power sensor to trigger a second more specific sensor can be applied to other autonomous sensor nodes.

High-Sensitivity Mach–Zehnder Interferometric Temperature Fiber Sensor Based on a Waist-Enlarged Fusion Bitaper

Abstract: An all-fiber high-sensitivity temperature fiber sensor based on a Mach-Zehnder interferometer in standard single-mode fibers (SMFs) is described. The interferometer consists of two concatenated waist-enlarged fusion bitapers which are fabricated simply by cleaving and fusion splicing. It is demonstrated that such an all-fiber Mach-Zehnder interferometer incorporates intermodal interference between the LP01 mode and a high-order cladding mode of LP07 mode. Its response to temperature is investigated and a high sensitivity of 0.070 nm/°C is obtained by a 7.5 mm interferometer. This simple, low-cost and easy-to-fabricate core-cladding modal interferometer with entire SMF-based structure also has great potential in diverse sensing applications.

In-Air Rangefinding With an AlN Piezoelectric Micromachined Ultrasound Transducer

Abstract: An ultrasonic rangefinder has a working range of 30 to 450 mm and operates at a 375-Hz maximum sampling rate. The random noise increases with distance and equals 1.3 mm at the maximum range. The range measurement principle is based on pulse-echo time-of-flight measurement using a single transducer for transmit and receive. The transducer consists of a piezoelectric AlN membrane with 400-μm diameter, which was fabricated using a low-temperature process compatible with processed CMOS wafers. The performance of the system exceeds the performance of other micromechanical rangefinders.

Inkjet Printed, Self Powered, Wireless Sensors for Environmental, Gas, and Authentication-Based Sensing

Abstract: In this paper, inkjet-printed flexible sensors fabricated on paper substrates are introduced as a system-level solution for ultra-low-cost mass production of UHF Radio Frequency Identification (RFID) Tags and wireless sensor nodes in a “green” approach that could be easily extended to other microwave and wireless applications. The authors briefly touch up the state-of-the-art area of fully integrated wireless sensor modules on paper and show several active and power scavenging platforms to power on wireless sensors that could potentially set the foundation for the truly convergent wireless sensor ad hoc networks of the future.

A Delay-Aware Data Collection Network Structure for Wireless Sensor Networks

Abstract: Wireless sensor networks utilize large numbers of wireless sensor nodes to collect information from their sensing terrain. Wireless sensor nodes are battery-powered devices. Energy saving is always crucial to the lifetime of a wireless sensor network. Recently, many algorithms are proposed to tackle the energy saving problem in wireless sensor networks. In these algorithms, however, data collection efficiency is usually compromised in return for gaining longer network lifetime. There are strong needs to develop wireless sensor networks algorithms with optimization priorities biased to aspects besides energy saving. In this paper, a delay-aware data collection network structure for wireless sensor networks is proposed. The objective of the proposed network structure is to minimize delays in the data collection processes of wireless sensor networks. Two network formation algorithms are designed to construct the proposed network structure in a centralized and a decentralized approach. Performances of the proposed network structure are evaluated using computer simulations. Simulation results show that, when comparing with other common network structures in wireless sensor networks, the proposed network structure is able to shorten the delays in the data collection process significantly.

Cognition in Wireless Sensor Networks: A Perspective

Abstract: Wireless Sensor Networks are believed to be the enabling technology for Ambient Intelligence. They hold the promise of delivering to a smart communication paradigm which enables setting up an intelligent network capable of handling applications that evolve from user requirements. Cognitive agents capable of making proactive decisions based on learning, reasoning and information sharing when interspersed in sensor networks, may help achieve end-to-end goals of the network even in the presence of multiple constraints and optimization objectives. Cognitive radio at the physical layer of such agents may enable the opportunistic use of the heterogeneous wireless environment. However, research efforts have been discrete and cognitive techniques have focused on improving specific aspects of the network or benefiting specific applications. The main contribution of this paper is providing the vision and advantage of a holistic approach to cognition in sensor networks, which can be achieved by incorporating learning and reasoning in the upper layers, and opportunistic spectrum access at the physical layer. Rather than providing an ostensive survey of cognitive architectures applicable to sensor networks, this paper provides the reader with a framework based on knowledge and cognition that can help achieve end-to-end goals of application-specific sensor networks.

Multisensor Fusion and Integration: Theories, Applications, and its Perspectives

Abstract: The decision-making processes in an autonomous mechatronic system rely on data coming from multiple sensors. An optimal fusion of information from distributed multiple sensors requires robust fusion approaches. The science of multisensor fusion and integration (MFI) is formed to treat the information merging requirements. MFI aims to provide the system a more accurate perception enabling an optimal decision to be made. The wide application spectrum of MFI in mechatronic systems includes industrial automation, the development of intelligent robots, military applications, biomedical applications, and microelectromechanical systems (MEMS)/nanoelectromechanical systems (NEMS). This paper reviews the theories and approaches of MFI with its applications. Furthermore, sensor fusion methods at different levels, namely, estimation methods, classification methods and inference methods, are the most frequently used algorithms. Future perspectives of MFI deployment are included in the concluding remarks.

Towards Tactile Sensing System on Chip for Robotic Applications

Abstract: This paper presents the research on tactile sensing system on chip. The tactile sensing chips comprise of 5 × 5 array of Piezoelectric Oxide Semiconductor Field Effect Transistor (POSFET) devices and temperature sensors. The POSFET devices are obtained by spin coating piezoelectric polymer, poly(vinylidene fluoride-trifluoroethylene) (P(VDF-TrFE)), films directly on to the gate area of Metal Oxide Semiconductor (MOS) transistors. The tactile sensing chips are able to measure dynamic contact forces and temperatures. The readout and the data acquisition system to acquire the tactile signals are also presented. The chips have been extensively tested over wide range of dynamic contact forces and temperatures and the experimental results are presented. The paper also reports the research on tactile sensing chips with POSFET array and the integrated electronics.

Ferrite Gas Sensors

Abstract: Soft ferrites are very important electronic materials because of their electrical and magnetic behavior. In last decade, remarkable efforts have been taken for the development of ferrite gas sensors in detection of toxic gas pollutants from vehicle exhaust, biological hazards, environment, and pollution monitoring. The parameters such as phase formation, crystallite size, particle size, grain size, dopants, surface area, sensitivity, selectivity, operating temperature, gas concentration, response time, and recovery time play an important role in development of ferrite gas sensors. These material for gas sensing covers number of gases such as carbon monoxide (CO), carbon dioxide (CO2 ), methane (CH4), ethyl alcohol (C2H5OH), hydrogen sulphide (H2S), C2H5COOH, oxygen (O2), hydrogen (H2), chlorine (Cl2), NH3, C4H10, CH3COOH , gasoline, acetylene, petrol, and liquefied petroleum gas (LPG). Different methods are used to prepare ferrite gas sensors. The prime requisite for developing a good quality ferrite gas sensor is optimization of preparation conditions, sintering temperature, operating temperatures, concentration of dopants, etc. It is observed that the gas sensitivity depends on kinds of semiconducting material, temperature, and test gases to be detected. This paper provides comprehensive survey of ferrites as gas sensors, such as nickel, copper, zinc, cadmium, cobalt, magnesium, manganese, and multi-component ferrites, prepared by various methods. The performance of these sensors including sensitivity, selectivity, stability, as well as response and recovery time, etc., are summarized in the table along with relevant references.

Denoising by Singular Value Decomposition and Its Application to Electronic Nose Data Processing

Abstract: This paper analyzes the role of singular value decomposition (SVD) in denoising sensor array data of electronic nose systems. It is argued that the SVD decomposition of raw data matrix distributes additive noise over orthogonal singular directions representing both the sensor and the odor variables. The noise removal is done by truncating the SVD matrices up to a few largest singular value components, and then reconstructing a denoised data matrix by using the remaining singular vectors. In electronic nose systems this method seems to be very effective in reducing noise components arising from both the odor sampling and delivery system and the sensors electronics. The feature extraction by principal component analysis based on the SVD denoised data matrix is seen to reduce separation between samples of the same class and increase separation between samples of different classes. This is beneficial for improving classification efficiency of electronic noses by reducing overlap between classes in feature space. The efficacy of SVD denoising method in electronic nose data analysis is demonstrated by analyzing five data sets available in public domain which are based on surface acoustic wave (SAW) sensors, conducting composite polymer sensors and the tin-oxide sensors arrays.

Performance Evaluation of Textile-Based Electrodes and Motion Sensors for Smart Clothing

Abstract: Development of textile-based electrodes and motion sensors is one of the main issues of recent smart textile research utilizing electronic textiles. Electrocardiogram (ECG) electrodes have been developed by various textile technologies such as sputtering or electroless-plating on the fabric surfaces, and embroidering or knitting with stainless steel yarns. In addition, two types of motion sensors have also been developed using piezo-resistive textiles. They were fabricated by knitting and braiding. To examine the usability of the ECG electrode, waveforms of the conventional AgCl electrode, and the new electrodes developed in our lab were compared. It was found that electrodes using metallic embroidering are more efficient when its substrate was a metal blended fabric. The electrolessly Cu/Ni plated fabrics obtained the best conductivity in textile-based electrodes. The first motion-measuring textile-based sensor was used to predict and measure the changes in electric resistances that accompany the angle changes in the elbow joint. An advanced piezo-resistive textile by braiding showed more accurate resistance changes and also better durability. Changes in its electrical resistance were mapped to changes in its length extension. From the relationship between the extension and the electrical resistance, movement or posture of human body was detected.

Detection of Cognitive Injured Body Region Using Multiple Triaxial Accelerometers for Elderly Falling

Abstract: This paper aimed to use several triaxial acceleration sensor devices for joint sensing of injured body parts, when an accidental fall occurs. The model transmitted the information fed by the sensors distributed over various body parts to the computer through wireless transmission devices for further analysis and judgment, and employed cognitive adjustment method to adjust the acceleration range of various body parts in different movements. The model can determine the possible occurrence of fall accidents, when the acceleration significantly exceeds the usual acceleration range. In addition, after a fall accident occurs, the impact acceleration and normal (habitual) acceleration can be compared to determine the level of injury. This study also implemented a sensing system for analysis. The area of the body parts that may sustain greater impact force are marked red in this system, so that more information can be provided for medical personnel for more accurate judgment.

Multifunctional Software-Defined Radar Sensor and Data Communication System

Abstract: Orthogonal frequency-division multiplexing (OFDM) signal coding and system architecture were implemented to achieve radar and data communication functionalities. The resultant system is a software-defined unit, which can be used for range measurements, radar imaging, and data communications. Range reconstructions were performed for ranges up to 4 m using trihedral corner reflectors with approximately 203 m of radar cross section at the carrier frequency; range resolution of approximately 0.3 m was demonstrated. Synthetic aperture radar (SAR) image of a single corner reflector was obtained; SAR signal processing specific to OFDM signals is presented. Data communication tests were performed in radar setup, where the signal was reflected by the same target and decoded as communication data; bit error rate of was achieved at 57 Mb/s. The system shows good promise as a multifunctional software-defined sensor which can be used in radar sensor networks.

Estimation of Tire-Road Friction Coefficient Using a Novel Wireless Piezoelectric Tire Sensor

Abstract: A tire-road friction coefficient estimation approach is proposed which makes use of the uncoupled lateral deflection profile of the tire carcass measured from inside the tire through the entire contact patch. The unique design of the developed wireless piezoelectric sensor enables the decoupling of the lateral carcass deformations from the radial and tangential deformations. The estimation of the tire-road friction coefficient depends on the estimation of slip angle, lateral tire force, aligning moment, and the use of a brush model. The tire slip angle is estimated as the slope of the lateral deflection curve at the leading edge of the contact patch. The portion of the deflection profile measured in the contact patch is assumed to be a superposition of three types of lateral carcass deformations, namely, shift, yaw, and bend. The force and moment acting on the tire are obtained by using the coefficients of a parabolic function which approximates the deflection profile inside the contact patch and whose terms represent each type of deformation. The estimated force, moment, and slip angle variables are then plugged into the brush model to estimate the tire-road friction coefficient. A specially constructed tire test rig is used to experimentally evaluate the performance of the developed estimation approach and the tire sensor. Experimental results show that the developed sensor can provide good estimation of both slip angle and tire-road friction coefficient.

Filter-Based Miniature Spectrometers: Spectrum Reconstruction Using Adaptive Regularization

Abstract: Miniature spectrometers provide a cost and size advantage over traditional spectrometers. However, unlike traditional spectrometers in which appropriate dispersive optics and/or interferometric devices are well-developed, miniature spectrometers usually do not have ideal (or close to ideal) wavelength-specific filtering mechanism to resolve the power of the input spectrum at specified wavelengths. Hence, the raw outputs from the filtering mechanism may not be adequate to represent spectra of measured objects. The nonideal filtering mechanism makes reconstruction process necessary. In this work, the method of Tikhonov regularization for stabilizing the solution of inverse problems is applied to a prototype filter-based nano-optic spectrum sensor from nanoLambda. L-curve criterion and generalized cross validation (GCV) criterion for adaptively selecting the regularization parameter are examined. Satisfactory results are obtained by exploiting non-negative constraints on the reconstructed spectrum, with the regularization parameter being selected by the L-curve criterion. As a result, low-cost miniature spectrometer on-a-chip can be realized.

Distributed Clustering-Based Aggregation Algorithm for Spatial Correlated Sensor Networks

Abstract: In wireless sensor networks, it is already noted that nearby sensor nodes monitoring an environmental feature typically register similar values. This kind of data redundancy due to the spatial correlation between sensor observations inspires the research of in-network data aggregation. In this paper, an α -local spatial clustering algorithm for sensor networks is proposed. By measuring the spatial correlation between data sampled by different sensors, the algorithm constructs a dominating set as the sensor network backbone used to realize the data aggregation based on the information description/summarization performance of the dominators. In order to evaluate the performance of the algorithm a pattern recognition scenario over environmental data is presented. The evaluation shows that the resulting network achieved by our algorithm can provide environmental information at higher accuracy compared to other algorithms.

The “Intelligent Container”—A Cognitive Sensor Network for Transport Management

Abstract: The “Intelligent Container” is a sensor network used for the management of logistic processes, especially for perishable goods such as fruit and vegetables. The system measures relevant parameters such as temperature and humidity. The concept of “cognitive systems” provides an adequate description of the complex supervision tasks and sensor data handling. The cognitive system can make use of several algorithms in order to estimate temperature related quality losses, detect malfunctioning sensors, and to control the sensor density and measurement intervals. Based on sensor data, knowledge about the goods, their history and the context, decentralized decision making is realized by decision support tools. The amount of communication between the container and the headquarters of the logistic company is reduced, while at the same time the quality of the process control is enhanced. The system is also capable of self-evaluation using plausibility checking of the sensor data.

A Novel Agent-Based Simulation Framework for Sensing in Complex Adaptive Environments

Abstract: In this paper, we present a novel formal agent-based simulation framework (FABS). FABS uses formal specification as a means of clear description of wireless sensor networks (WSNs) sensing a complex adaptive environment. This specification model is then used to develop an agent-based model of both the WSN as well as the environment. As proof of concept, we demonstrate the application of FABS to a boids model of self-organized flocking of animals monitored by a random deployment of proximity sensors.

A Localization Scheme for Wireless Sensor Networks Using Mobile Anchors With Directional Antennas

Abstract: This paper proposes a range-free localization scheme for wireless sensor networks (WSNs) using mobile anchor nodes equipped with four directional antennas. In the proposed approach, each mobile anchor node determines its position via GPS, and then broadcasts its coordinates as it moves through the WSN. The sensor nodes detect these beacon messages and utilize a simple processing scheme to determine their own coordinates based on those of the anchors. The proposed approach removes the requirement for specific ranging hardware on the sensor nodes, avoids the need for communications between the sensor nodes. Moreover, the scheme is robust toward the effects of variations in the transmission range of the anchor nodes and the presence of obstacles in the sensing environment. The performance of the proposed scheme is evaluated by conducting a series of simulations using the ns-2 network simulator. The results show that the proposed localization scheme achieves a reduced localization error and a lower energy consumption than existing range-free solutions based on mobile anchor nodes over a wide range of typical network conditions.