A Robust Steered Response Power Localization Method for Wireless Acoustic Sensor Networks in an Outdoor Environment

Acoustic source localization has been an hot research topic with widespread applications in many fields. In the noisy environment or when the reverberation is considerable, the source localization problem becomes challenging and many existing algorithms deteriorate. The paper proposes a robust algorithm which combines the RANdom SAmple Consensus (RANSAC) algorithm, and the Generalized Cross-Correlation (GCC) based Time Difference of Arrival (TDOA). Experiments in real world data show that the proposed algorithm has significantly better performance than the traditional algorithm.

Using wireless sensor networks (WSNs) in delay and reliability critical environments is highly desired due to their unique advantages such as low cost, ease of deployment, and redundancy. However, successful deployment of resource-limited WSNs in such applications requires strict quality-of-service (QoS) provisioning techniques to meet the desired latency and reliability targets of those applications. Implementation of QoS techniques in WSNs is significantly challenging since WSNs have been initially devised for low-data-rate non-real-time applications. Therefore, WSN designers and developers resort to different cross-layer interaction and optimization techniques to provision QoS in WSNs. In this paper, we present a survey on the state of the art of cross-layer QoS approaches in wireless terrestrial sensor networks to achieve delay and reliability bounds in critical applications. Our paper provides a unique classification of cross-layer QoS approaches in WSNs that allows surveying a large amount of studies with utmost clarity. Furthermore, we highlight the main challenges of implementing QoS protocols in WSNs and present an overview of QoS-aware WSN applications.

Wireless industrial sensor networks are wireless sensor networks which have been adapted to industrial applications. Most techniques for wireless sensor networks can be applied to wireless industrial sensor networks. However, for industrial applications of wireless industrial sensor networks, new requirements such as real-time, reliable delivery need to be considered. In this paper, we propose EARQ, which is a novel routing protocol for wireless industrial sensor networks. It provides real-time, reliable delivery of a packet, while considering energy awareness. In EARQ, a node estimates the energy cost, delay and reliability of a path to the sink node, based only on information from neighboring nodes. Then, it calculates the probability of selecting a path, using the estimates. When packet forwarding is required, it randomly selects the next node. A path with lower energy cost is likely to be selected, because the probability is inversely proportional to the energy cost to the sink node. To achieve real-time delivery, only paths that may deliver a packet in time are selected. To achieve reliability, it may send a redundant packet via an alternate path, but only if it is a source of a packet. Experimental results show that EARQ is suitable for industrial applications, due to its capability for energy efficient, real-time, reliable communications.

The deployment of the nodes in a Wireless Sensors and Actuators Network (WSAN) is typically restricted by the sensing and acting coverage. This implies that the locations of the nodes may be, and usually are, not optimal from the point of view of the radio communication. And also when the transmission power is tuned for those locations, there are other unpredictable factors that can cause connectivity failures, like interferences, signal fading due to passing objects, and of course, radio irregularities. A control based self-adaptive system is a typical solution to improve the energy consumption while keeping a good connectivity. In this paper, we explore how the communication range for each node evolves along the iterations of an energy saving self-adaptive transmission power controller when using different parameter sets in an outdoor scenario, providing a WSAN that automatically adapts to surrounding changes keeping a good connectivity. The results obtained in this paper show how the parameters with the best performance keep a k-connected network, where k is in the range of the desired node degree plus or minus a specified tolerance value. In addition, the worst performance shows how a bad parameters choice can create isolated islands, groups of nodes disconnected from the rest of the network.

Wireless sensor networks have received a lot of attention in recent years due to their wide spectrum of applications. Localization a technique used in ubiquitous sensor networks. Most localization techniques apply RSSI-based ranging techniques to compute the location of the object in a wireless sensor network. However, a wireless sensor network is a fading-signal environment that has noise, which causes RSSI to become unstable and leads to abrupt distance estimates. In this paper, we propose the Verification-Based Localization Method (VBLM) to alleviate the effect of unstable signals to provide high-accuracy location estimates in wireless sensor environments. VBLM filters noisy signals in the localization process. The sensor node uses a neighboring beacon to help verify the quality of received signal under acceptable communication cost. Noisy signals can thus be removed to decrease localization error. A set of experiments was conducted in an outdoor environment. The experimental results show that VBLM reduces the localization error in unstable signal sensor networks better than is possible with other localization methods.

This paper addresses the problem of direct-path passive broadband localization of a shallow-water acoustic source with a sparsely distributed set of sensors in the presence of uncertain multipath propagation. The classical approach to broadband source localization with sensors spaced many wavelengths apart involves time delay estimation (TDE) via generalized cross-correlation (GCC) methods. In shallow-water scenarios, however, multipath arrivals yield spurious peaks in cross-correlation outputs resulting in anomalous estimates of source location. In this paper, cross-correlations are normalized by an expected direct-path delay and geometrically averaged over multiple array orientations in order to disambiguate multipath returns from direct-path arrivals. In shallow-water channels, this allows for more robust estimates of the intersensor time delay due to direct-path propagation. Simulation results indicate a significant improvement in source localization performance over GCC methods operating in multipath environments.

Wireless sensor and actuator networks (WSANs) are heterogeneous networks composed of many different nodes that can cooperatively sense the environment, determine an appropriate action to take, then change the environment’s state after acting on it. As a natural extension of wireless sensor networks (WSNs), WSANs inherit from them a variety of research challenges and bring forth many new ones. These challenges are related to dealing with imprecise and vague information, solving complicated optimization problems or collecting and processing data from multiple sources. Computational intelligence (CI) is an overarching term denoting a conglomerate of biologically and linguistically inspired techniques that provide robust solutions to NP-hard problems, reason in imprecise terms and yield high-quality yet computationally tractable approximate solutions to real-world problems. Many researchers have consequently turned to CI in hope of finding answers to a plethora of WSAN-related challenges. This paper reviews the application of several methodologies under the CI umbrella to the WSAN field. We describe and categorize existing works leaning on fuzzy systems , neural networks , evolutionary computation , swarm intelligence , learning systems , and their hybridizations to well-known or emerging WSAN problems along five major axes: 1) actuation; 2) communication; 3) sink mobility; 4) topology control; and 5) localization. The survey offers informative discussions to help reason through all the studies under consideration. Finally, we point to future research avenues by: 1) suggesting suitable CI techniques to specific problems; 2) borrowing concepts from WSNs that have yet to be applied to WSANs; or 3) describing the shortcomings of current methods in order to spark interest on the development of more refined models.

Wireless sensor networks (WSNs) are among the most promising technologies of the new millennium. The opportunities afforded by being able to program networks of small, lightweight, low-power, computation- and bandwidth-limited nodes have attracted a large community of researchers and developers. However, the unique set of capabilities offered by the technology produces an exciting but complex design space, which is often difficult to negotiate in an application context. Deploying sensing physical environments produces its own set of challenges, and can push systems into failure modes, thus revealing problems that can be difficult to discover or reproduce in simulation or the laboratory.Sustained efforts in the area of wireless networked sensing over the last 15 years have resulted in a large number of theoretical developments, substantial practical achievements, and a wealth of lessons for the future. It is clear that in order to bridge the gap between (on the one hand) visions of very large scale, autonomous, randomly deployed networks and (on the other) the actual performance of fielded systems, we need to view deployment as an essential component in the process of developing sensor networks: a process that includes hardware and software solutions that serve specific applications and end-user needs. Incorporating deployment into the design process reveals a new and different set of requirements and considerations, whose solutions require innovative thinking, multidisciplinary teams and strong involvement from end-user communities.This special feature uncovers and documents some of the hurdles encountered and solutions offered by experimental scientists when deploying and evaluating wireless sensor networks in situ, in a variety of well specified application scenarios.The papers specifically address issues of generic importance for WSN system designers: (i) data quality, (ii) communications availability and quality, (iii) alternative, low-energy sensing modalities and (iv) system solutions with high end-user added value and cost benefits. The common thread is deployment and deployment evaluation. In particular, satisfaction of application requirements, involvement of the end-user in the design and deployment process, satisfactory system performance and user acceptance are concerns addressed in many of the contributions. The contributions form a valuable set, which help to identify the priorities for research in this burgeoning area: Robust, reliable and efficient data collection in embedded wireless multi-hop networks are essential elements in creating a true deploy-and-forget user experience. Maintaining full connectivity within a WSN, in a real world environment populated by other WSNs, WiFi networks or Bluetooth devices that constitute sources of interference is a key element in any application, but more so for those that are safety-critical, such as disaster response. Awareness of the effects of wireless channel, physical position and line-of-sight on received signal strength in real-world, outdoor environments will shape the design of many outdoor applications. Thus, the quantification of such effects is valuable knowledge for designers. Sensors' failure detection, scalability and commercialization are common challenges in many long-term monitoring applications; transferable solutions are evidenced here in the context of pollutant detection and water quality. Innovative, alternative thinking is often needed to achieve the desired long-lived networks when power-hungry sensors are foreseen components; in some instances, the very problems of wireless technology, such as RF irregularity, can be transformed into advantages. The importance of an iterative design and evaluation methodology—from analysis to simulation to real-life deployment—should be well understood by all WSN developers. The value of this is highlighted in the context of a challenging WPAN video-surveillance application based on a novel Nomadic Access Mechanism. Cost benefits to be drawn from devising a WSN based solution to classic application areas such as surveillance are often a prime motivator for WSN designers; an example is offered here based on the use of intelligent agents for intrusion monitoring. Last but not least, the practicality and usability of the WSN solutions found for novel applications is key to their adoption. This is particularly true when the end-users of the developed technology are medical patients. The importance of feedback, elegant hardware encapsulation and extraction of meaning from data is presented in the context of novel orthopedic rehabilitation aids.Overall, this feature offers wide coverage of most issues encountered in the process of design, implementation and evaluation of deployable WSN systems. We trust that designers and developers of WSN systems will find much work of value, ranging from lessons learned, through solutions to known hurdles, to novel developments that enhance applications. Finally, we would like to thank all authors for their valuable contributions!

Moisture sensor acquires data of moisture content and water height of farmland; the data are transmitted by wireless sensor network and stored in data server to provide data mining and decision support for users, the utilization of wireless moisture sensor network could facilitate the excellent growth of crops and sustainable development of water resources. Based on self-design moisture sensor and actual monitoring needs of farmland moisture, this paper presents the architecture of wireless moisture sensor network and format of moisture data packet, designs the mechanisms of hierarchical storage, hierarchical error control and retransmission. Especially, the paper analyzes and simulates the mechanism of error control from respects of consuming time and correcting error ability, simulation results show that BCH coding is more suitable for wireless moisture sensor network than RS coding.

Congestion in Wireless Sensor Network (WSN) occurs when traffic load allocated to any sensor node is beyond its capacity. It is necessary to control the congestion traffic to support traditional quality of service (such as packet loss ratios, packet delay, wasting energy and throughput) especially, multimedia application of Wireless Multimedia Sensor Network (WMSN). Congestion control in WSN has been shown to be very effective with respect to extending lifespan of system. Hence to avoid the congestion in WSN, we proposed an efficient protocol called Priority-based Congestion Control Protocol (PCCP) which prevents an upstream congestion in WSN. The PCCP creates priority table based an importance of each node, and then sends this information to all the nodes within the network. Secondly, the major function of PCCP is to measure congestion level in the network using ratio of packet inter-arrival time along over packet service time. PCCP uses to control upstream congestion along with congestion degree and packet table. PCCP is hop-by-hop upstream congestion control protocol for WSN. PCCP provides work for packet-based computation to optimize congestion control. It can work under both single path & multipath routing. PCCP ensures guarantee of packet loss as well as delay, resulting each node can avoid unfairness and achieve flexible throughput. In this paper, we have proposed that PCCP provides better QoS by controlling network recourse management and network traffic to consuming efficient energy.

Wireless sensor networks (WSNs) are used to collect large amounts of data over a wide area. However, the sensor nodes used in WSNs have a short lifespan because they are generally battery-operated. Research is actively underway to increase the lifespan of WSNs via techniques such as energy harvesting and wireless power transfer (WPT). This study proposes a scheme for clustering and adjusting the WSN data collection rate to alleviate the hotspot problem and improve network connectivity. The proposed scheme is targeted at WSNs in which the sensor nodes harvest solar energy. In addition, an unmanned aerial vehicle (UAV) traverses along a given path and delivers energy to sensor nodes using WPT, while collecting data as a sink node. In this scheme, the number of cluster heads is determined by considering the number of nodes at each hop distance and the maximum amount of data that can be transferred with the available energy. Further, sensor nodes limit the amount of data they collect to reduce the relay load on intermediate nodes. To achieve this, nodes consider the amount of data transferred by parent nodes, especially nodes in the hotspot, and the number of child nodes. The sink node traverses along a given path, and collects the data accumulated in the cluster head while supplying its remaining energy to the cluster head. The amount of energy it transfers is determined by considering the number of cluster heads. Consequently, nodes in the hotspot are prevented from becoming blacked out from a lack of energy, and the energy harvesting efficiency is increased. Simulation results indicate that the proposed scheme reduces the number of blackout nodes in the hotspot areas near cluster heads. Furthermore, the data collection and monitoring performance increases with the increase in network connectivity.

In recent years, there has been intense research and considerable progress in solving numerous wireless sensor networking challenges. However, the key problem of enabling real-time quality-aware multimedia transmission over wireless sensor networks is largely unexplored. The large amount of data generated by most multimedia applications (compared to traditional scalar sensor networks), along with the higher QoS requirements make it difficult to meet the low energy use requirements of practical sensor networks. We explore the use of compressed sensing (aka “compressive sampling”) to reduce the energy required to encode and transmit high quality video in a severely resource-constrained environment. In this chapter, we will examine some of the major challenges of wireless multimedia sensor network (WMSN) implementation. Specifically, we examine what it would take to develop a WMSN that has similar performance (and restrictions) as a traditional scalar wireless sensor network (WSN). We then examine how we can use the new paradigm of compressed sensing (CS) to solve many of these problems.KeywordsSensor NodeWireless Sensor NetworkDiscrete Cosine TransformVideo QualityCompress SenseThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

The use of wireless multimedia sensor networks (WMSNs) for surveillance applications has attracted the interest of many researchers. As with traditional sensor networks, it is easy to deploy and operate WMSNs. With inclusion of multimedia devices in wireless sensor networks, it is possible to provide data to users that is more meaningful than that provided by scalar sensor-based systems alone; however, producing, storing, processing, analyzing, and transmitting multimedia data in sensor networks requires consideration of additional constraints, including energy, processing power, storage capacity, and communication. Furthermore, as multimedia sensors produce much more data than scalar sensors, more manpower is required to analyze multimedia data. To overcome these constraints and challenges, this paper aimed to propose a system architecture and a set of procedures for WMSNs that facilitate automatic classification of moving objects using scalar and multimedia sensors. Methods and standards for detecting and classifying a moving object, as well as transmission of the results, are described in detail. The hardware for each sensor node includes a built-in camera, a passive infrared motion sensor, a vibration sensor, and an acoustic sensor. An application using our proposed methods was developed and embedded in the multimedia sensor node. In addition, a sink station was set up and the data produced by the sensor network was collected by this server. The classification performance of the application was tested using video recorded by the sensor node. The effect of the proposed methods on power consumption was also tested and measured. The experimental results show that the proposed approach is sufficiently lightweight to be used for real-world surveillance applications.

The appearance of wireless sensor networks has attracted worldwide attention. Wireless Sensor Networks (WSNs) and Wireless Multimedia Sensor Networks (WMSNs) consist of wirelessly interconnected sensor nodes organised arbitrarily or deterministically in an environmental area which can gather, distribute and route information in different application areas. Power consumption in these networks is the foremost problem. WSNs are a recent generation of sensor networks, have an ample range of applications, their expansion and application will convey about extensive impact in human life and construction of all areas. Some of the applications include disaster management, landslide detection, glacial monitoring, wildlife tracking, healthcare, military applications, environmental monitoring, security surveillance, industrial process control and a large number of applications to robotics and Internet of Things (IOT) projects. This paper will demonstrate the elementary description of WSN followed by different energy-efficient power consumption protocols. Here we have performed the comparative performance analysis of different energy-efficient protocols. In our work we have compared MODLEACH with TSEP followed by TSEP with RELSEP.

Applying multimedia to Wireless Sensor Network (WSN) adds more challenges due to WSN resource constraints and the strict Quality of Service (QoS) requirements for multimedia transmission. Different multimedia applications may have different QoS requirements, so routing protocols designed for Wireless Multimedia Sensor Network (WMSN) should be conversant of these requirements and challenges in order to ensure the efficient use of resources to transfer multimedia packets in an utmost manner. The majority of solutions proposed for WMSN depends on traditional layered based mechanisms which are inefficient for multimedia transmission. In this paper we propose a cross-layer Ant based Routing Protocol for WMSN (CARPM) by using modified ant colony optimization (ACO) technique to enhance the routing efficiency. The proposed protocol uses an improved ACO to search for the best path that are satisfied with the multimedia traffic requirements. While making best decision the weightage is given to energy consumption, and queuing delay. The proposed cross layer scheme works between the routing, MAC, and physical layers. Since, the remaining power and timestamp metrics are exchanged from physical layer to network layer. Dynamics duty cycle assignment is proposed at MAC layer which changes according to traffic rate. The presented algorithm is simulated using NS2 and is proven to satisfy its goals through a series of simulations.