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Ensuring different types of coverage is an important problem in many wireless sensor applications. In this paper, we address the problem of maintaining support coverage in the presence of sensor failures. Given a placement of n sensors in an area A, and any two points i and f in A, the support value of any path between i and f is the maximum distance of any point on the path from its closest sensor. The path with the minimum support value is called the maximal support path. The support value of a path may increase if a sensor fails. Given a maximal support path with a support value ψ, we first present two centralized approximation algorithms that, on failure of a single sensor, compute a new path with a support value close to ψ by moving exactly one nearby sensor. The first algorithm assumes that the sensors are allowed to move in any direction, and the second one assumes that the sensors are constrained to move in any of the four directions east, west, north, and south. Both the support value for the new path computed and the movement necessary are shown to be within a constant-factor of the initial support value. We then show that even in case of multiple sensor failures, a new path with a bounded support value can be computed. Detailed simulation results are provided to show that the algorithms result in significant improvement in many cases in practice, and the improvements obtained are significantly better than the worst case bounds given by the analysis. We also discuss distributed implementations of the algorithms.

Sensor networks that can support time-critical operations pose challenging problems for tracking events of interest. We propose an architecture for a sensor network that autonomously adapts in real-time to data fusion requirements so as not to miss events of interest and provides accurate real-time mobile target tracking. In the proposed architecture, the sensed data is processed in an abstract space called Information Space and the communication between nodes is modeled as an abstract space called Network Design Space. The two abstract spaces are connected through an interaction interface called InfoNet, that seamlessly translates the messages between the two. The proposed architecture is validated experimentally on a laboratory testbed for multiple scenarios.

In this paper, we propose a localization simulator based on the random walk/waypoint mobility model and a hybrid-type location–compensation algorithm using the Mean kShift/Kalman filter (MSKF) to enhance the precision of the estimated location value of mobile modules. From an analysis of our experimental results, the proposed algorithm using the MSKF can better compensate for the error rates, the average error rate per estimated distance moved by the mobile node (Err_ Rate_DV) and the error rate per estimated trace value of the mobile node (Err_Rate_TV) than the Mean shift or Kalman filter up to a maximum of 29% in a random mobility environment for the three scenarios.

In passive location systems on the ground, the judgment and location of multi-target is more challenging compared with the case of single target. In this paper, we propose a method for multi-target identification and location in an arbitrary structure with three base stations (BSs). First of all, we discuss the scene of multi-targets judgment based on geometric dilution of precision (GDOP) value. Secondly, we propose an algorithm that calculates the system coverage radius based on arbitrary three BS structures. The algorithm helps to identify the number of targets for unsupervised learning. Finally, we locate each target individually located again based on the linear constrained minimum variance (LCMV) beam former and time difference of arrival (TDOA) algorithm. In the simulations, we analyzed the location dispersion under different signal-to-noise ratio (SNR), then calculated the termination threshold of the k-means algorithm under different SNR. The simulation results show that, compared to the probability hypothesis density (PHD) filter and TDOA-angle-of-arrival (AOA) joint algorithm, the proposed method can increase more than 12.5% and 15.6% points. With the increase of the number of targets, the running time of our algorithm is controllable with better stability.

Smart image sensors with low data rate output are well fitted for security and surveillance tasks, since at lower data rates, power consumption is reduced and the image sensor can be operated with limited energy resources such as solar panels. In this paper, a new data transfer scheme is presented to reduce the data rate of the pixels which have undergone value change. Although different pixel difference detecting architectures have been previously reported but it is shown that the given method is more effective in terms of power dissipation and data transfer rate reduction. The proposed architecture is evaluated as a $100\times 160$-pixel sensor in a standard CMOS technology and comparison with other data transfer approaches is performed in the same process and configuration.

In this paper, a monitoring technique based on the wireless sensor network is investigated. The sensor nodes used for monitoring are developed in a simulation environment. Accordingly, the structure and workflow of wireless sensor network nodes are designed. Time-division multiple access (TDMA) protocol has been chosen as the medium access technique to ensure that the designed technique operates in an energy-efficient manner and packet collisions are not experienced. Fading channels, i.e., no interference, Ricean and Rayleigh, are taken into consideration. Energy consumption is decreased with the help of ad-hoc communication of sensor nodes. Throughput performance for different wireless fading channels and energy consumption are evaluated. The simulation results show that the sensor network can quickly collect medium information and transmit data to the processing center in real time. Besides, the proposed technique suggests the usefulness of wireless sensor networks in the terrestrial areas.

In order to improve the intelligent informatization level of electric power production safety and reduce the accidents, the paper constructs a dynamic perception scheme of electric power production site that utilizes multi-dimensional information such as personnel location, equipment status, and image information. This method uses a multi-sensor network to realize the real-time perception of the image and position information of dynamic power work objects, then uses object identification and intelligent analysis to acquire the dynamic factors. Static factors are selected through questionnaire and historical data, and variable precision fuzzy theory is used to calculate the weight of static factors at dynamic power operation sites. A comprehensive evaluation is established to perceive risk and estimate security probability based on static factors and dynamic scene information. The application system can present the situation of the operation scene, and then realize safety assessment and early warning of the dangerous situation in the case of dynamic power monitoring. This method can prevent safety accidents and enhance the overall safety of power operations.

This paper proposes a framework for the development of sensor node software for various operating systems in a sensor network environment. The proposed development framework consists of attributes, code templates and development support tool. Sensor node software is developed, based on the framework through four steps —sensor network modeling, PIM design, PSM design and code generation. Accordingly, this paper presents the methods for attributes design, code templates design, PIM-to-PSM mapping, and source code generation. Through the proposed technique, reusability of sensor network software will be increased since models, attributes and code templates can be reused for various operating systems through the framework. Productivity of software development will be increased, because software design is easily performed using attributes and software codes for all nodes in the sensor network can be generated at once from a model. Also, expandability of sensor network software will be increased, since new functions of existing operating systems or new operating systems can be added through the framework and sensor network software can be rebuilt by applying the added functions or operating systems.

In this paper, first, we discuss the status quo of research and development of intelligent speech technology and analyze the problems existing in today’s education. The second is to explain the related concepts of intelligent speech technology, and, at the same time, to conduct in-depth research on the intelligent speech technology tools used in the experimental research and the related functions of the educational applications cited in this research, and briefly describe the correlation between information education and language learning basic knowledge. Then we summarize the structure, attributes, scope and existing solutions to solve the energy efficiency of the sensor network, focus on the classification and analysis of the existing routing protocols of the wireless sensor network, and summarize the characteristics of the protocol. In addition, this paper conducts extensive research on the relationship between LEACH protocol cluster division and energy consumption. This paper focuses on the shortcomings of the mainstream virtual reality (VR) system creation method, and proposes a method of interactive design, which significantly reduces the threshold for creating VR content and improves the efficiency of VR creation. Wisdom teaching technology not only mobilizes the enthusiasm of students in learning, but also helps to improve the teaching effect. Finally, it summarizes the specific work and importance of the research, and shows the application and development prospects of intelligent teaching technology in future education. Through the research of intelligent voice technology and sensor network, this paper applies it to the VR intelligent teaching system, and promotes the development of the VR intelligent teaching system in future education.

One of the fundamental issues in sensor networks is the coverage problem, which reflect-show well a sensor network is monitored or tracked by sensors. In this paper, we formulate this problem as a decision problem, whose goal is to determine whether every point in the servicearea of the sensor network is covered by at least α sensors, where ff is a given parameter andthe sensing regions of sensors are modeled by balls (not necessarily of the same radius). This problem in a 2D space is solved in [10] with an efficient polynomial-time algorithm (in termsof the number of sensors). In this paper, we show that tackling this problem in a 3D space is still feasible within polynomial time. Further, the proposed solution can be easily translated intoan efficient polynomial-time distributed protocol. We demonstrate an application of the derived result by proposing an energy-conserving scheduling protocol.

The security of wireless sensor networks is a significant concern and can be achieved by the application of cryptographic algorithms. The symmetric key encryption techniques are widely used cryptographic mechanisms for the security of sensor networks due to its low computational complexity. A symmetric key encryption technique requires a secret key to be shared between both parties for confidential communication. In a wireless sensor network, it is difficult to know which node is going to be in its communication range at the deployment phase. If prior knowledge of sensor location exists, it is an added advantage and helps in the distribution of secret keys among nodes. Even if with the expected location information, distributing the keys properly among the nodes is a challenging task. A proper algorithm must be used so that it gives the adequate utilization of the distributed keys with a minimal number of keys per sensor node. In this paper, we propose a location-dependent key distribution scheme. We use Delaunay Triangulation for the efficient distribution of keys among sensor nodes. The method gives a high probability of secure communication links among nodes with high resilience to the network.

The concept of smart aggregates, a distributed intelligent multi-purpose sensor network for civil structures, has been implemented to address three important issues including early-age concrete strength monitoring, impact detection and evaluation, and structural health monitoring. This paper presents mainly the employment of smart aggregates' active sensing property to form feedback in a sensor network to reduce damage-location detection time for lower power cost. Firstly, the concept of smart aggregates and the principle of a smart-aggregate-based sensor network are outlined. Next, the data pretreatment methods, including the sensor observation estimation model and the wavelet-packet-based signal processing algorithm, are proposed. A crucial concept using the damage index is also introduced. Moreover, the concept of the geometry structure matching method with the knowledge of an expert system is presented to determine which sensor is the optimal actuator. Finally, the data pretreatment algorithm and the geometry structure matching method are evaluated for a two-story concrete frame instrumented with smart aggregates as a testing object by means of actual experiments. The testing results demonstrate that the proposed algorithms are feasible and perform well in selecting optimal actuators of the sensor network for detecting damage locations.

In this paper, a system supporting behavioral therapy for autistic children is presented. The system consists of sensors network, base station and a brooch indicating person's emotional states. The system can be used to measure values of physiological parameters that are associated with changes in the emotional state. In the future, it can be useful to inform the autistic child and the therapist about the emotional state of the interlocutor objectively, on the basis of performed measurements. The selected physiological parameters were chosen during the experiment which was designed and conducted by authors. In this experiment, a group of volunteers under controlled conditions was exposed to a stressful situation caused by the picture or sound. For each of the volunteers, a set of physiological parameters, was recorded, including: skin conductance, heart rate, peripheral temperature, respiration rate and electromyography. The bio-statistical analysis allowed us to discern the proper physiological parameters that are most associated to changes due to emotional state of a patient, such as: skin conductance, temperatures and respiration rate. This allowed us to design electronic sensors network for supporting behavioral therapy for children with autism.

In this paper, we present a new proof for a well-known inequality, conjectured by Zassenhaus in 1947 and proved independently by Groemer in 1960 and Oler in 1961. The inequality gives an upper bound for the number of nonoverlapping unit discs whose centers can be packed into a compact convex region, and recently obtains a lot of applications in study of sensor networks.

As for the extremely unpredictable factors of Distributed Sensor Networks (DSNs) with constrained resources operating in an unattended mode in uncertain dynamic environments, the behavior evaluation of sensor-network nodes is vital to architecture of autonomic and fault-tolerant DSNs. Because of Bayesian probability incapability of capturing epistemic uncertainty (uncertainty with little prior-knowledge), one evaluation scheme based on Dempster Evidence Theory (DST) is proposed with coarsening and refining combining algorithm by Fast Möbius Transform (FMT). This method offers an efficient framework for uncertainty quantifying and partial knowledge processing with sharply decreasing computation complexity. Simulation verified this ubiquitous low-cost computation appropriate to flexible Wireless Sensor Network Management Protocol (SNMP) for prolonging live-time of sensor network.

Wireless sensor network has broad applications in target tracking and locating, especially fit for military detection or guard. By establishing a tracking cluster, this article proposes a Tracking Cluster Rekeying Protocol (TCRP). Sensors can locate the moving object in the monitored area based on given sensitivity and form a tracking cluster around it. This tracking cluster can follow the target logically, process detected data and report to the sink node, and thus achieve the tracking function. To improve its security and applicability, cluster session key is used for data exchange. And pre-established encrypt links are used to guarantee the whole system's security.

This paper generalizes the information coverage from probability space to Sugeno measure space, and proposes a notion of g_λ random coverage based on non-additive measure. The simulation results show that g_λ random coverage is a more general coverage analysis for information coverage in wireless sensor networks. It can be transformed to probability coverage on one hand; it can also satisfy different requirements of non-additive information coverage on the other hand.

The key objective of wireless sensor networks (WSNS) is to use the restricted embedded resource efficiently and to maximize their life time. Quality of service (QoS) routing is one of the key technologies to provide differential services and utilize the whole resource effectively for WSNS. We present a new energy best routing method which could meet the requirements of QoS bandwidth and has longer network life time.

This method Constructed the Node Selection Model, Energy Assessing Model. The genetic quantum Algorithm (QGA) which utilizes the set of the available nodes was used to construct the route. The Markov chain proved the algorithm that is strong convergence and also the convergence speed is exponent. In addition, the choosing intervals of the controlling parameters proposed by the QGA algorithm have been determined based on the simulations and the analysis results. It has been shown from the experiments that the energy best routing method has better adaptability and longer lifetime.

The sensing abilities of networked sensors are affected by environmental factors and their own degeneration such that the sensing abilities reduce to a smaller value, then a fuzzy annulus is formed. So it is fuzzy to anticipate this sensing behavior. We investigate the coverage issues in sensor networks based on fuzzy theory and propose a new notion of fuzzy geometric coverage. Based on this model, we define the best and worst-case fuzzy geometric coverage, and construct the Delaunay diagram and Voronoi diagram to solve the problem. The analysis and simulation results show that the proposed model has a good performance in solving fuzzy coverage problem in sensor networks.

This paper discusses the design of a sensor network for the security infrastructure of power system applications. The architecture of the whole system is designed in detail. And the implementation of software and hardware is described. IEC 61850 is adopted as the communication protocol in this system and IEEE 1451 as the interface. The whole system is actively synchronized with the combination of GPS and IEEE 1588 protocol.