https://www.science.smith.edu/~jcardell/Courses/EGR328/Readings/WSNSurvey2.pdf

Wireless sensor network survey

We present the design, implementation, and evaluation of BeepBeep, a high-accuracy acoustic-based ranging system. It operates in a spontaneous, ad-hoc, and device-to-device context without leveraging any pre-planned infrastructure. It is a pure software-based solution and uses only the most basic set of commodity hardware -- a speaker, a microphone, and some form of device-to-device communication -- so that it is readily applicable to many low-cost sensor platforms and to most commercial-off-the-shelf mobile devices like cell phones and PDAs. It achieves high accuracy through a combination of three techniques: two-way sensing, self-recording, and sample counting. The basic idea is the following. To estimate the range between two devices, each will emit a specially-designed sound signal ("Beep") and collect a simultaneous recording from its microphone. Each recording should contain two such beeps, one from its own speaker and the other from its peer. By counting the number of samples between these two beeps and exchanging the time duration information with its peer, each device can derive the two-way time of flight of the beeps at the granularity of sound sampling rate. This technique cleverly avoids many sources of inaccuracy found in other typical time-of-arrival schemes, such as clock synchronization, non-real-time handling, software delays, etc. Our experiments on two common cell phone models have shown that we can achieve around one or two centimeters accuracy within a range of more than ten meters, despite a series of technical challenges in implementing the idea.

BeepBeep: a high accuracy acoustic ranging system using COTS mobile devices

Summary 1. Animals produce sounds for diverse biological functions such as defending territories, attracting mates, deterring predators, navigation, finding food and maintaining contact with members of their social group. Biologists can take advantage of these acoustic behaviours to gain valuable insights into the spatial and temporal scales over which individuals and populations interact. Advances in bioacoustic technology, including the development of autonomous cabled and wireless recording arrays, permit data collection at multiple locations over time. These systems are transforming the way we study individuals and populations of animals and are leading to significant advances in our understandings of the complex interactions between animals and their habitats. 2. Here, we review questions that can be addressed using bioacoustic approaches, by providing a primer on technologies and approaches used to study animals at multiple organizational levels by ecologists, behaviourists and conservation biologists. 3. Spatially dispersed groups of microphones (arrays) enable users to study signal directionality on a small scale or to locate animals and track their movements on a larger scale. 4. Advances in algorithm development can allow users to discriminate among species, sexes, age groups and individuals. 5. With such technology, users can remotely and non-invasively survey populations, describe the soundscape, quantify anthropogenic noise, study species interactions, gain new insights into the social dynamics of sound-producing animals and track the effects of factors such as climate change and habitat fragmentation on phenology and biodiversity. 6. There remain many challenges in the use of acoustic monitoring, including the difficulties in performing signal recognition across taxa. The bioacoustics community should focus on developing a

/pdf/acoustic-monitoring-in-terrestrial-environments-using-56nw251vd9.pdf

Acoustic monitoring in terrestrial environments using microphone arrays: applications, technological considerations and prospectus

Recent advances in radio and embedded systems have enabled the proliferation of wireless sensor networks. Wireless sensor networks are tremendously being used in different environments to perform various monitoring tasks such as search, rescue, disaster relief, target tracking and a number of tasks in smart environments. In many such tasks, node localization is inherently one of the system parameters. Node localization is required to report the origin of events, assist group querying of sensors, routing and to answer questions on the network coverage. So, one of the fundamental challenges in wireless sensor network is node localization. This paper reviews different approaches of node localization discovery in wireless sensor networks. The overview of the schemes proposed by different scholars for the improvement of localization in wireless sensor networks is also presented. Future research directions and challenges for improving node localization in wireless sensor networks are also discussed.

/pdf/localization-algorithms-in-wireless-sensor-networks-current-22qk6i0z4i.pdf

Localization Algorithms in Wireless Sensor Networks: Current Approaches and Future Challenges

Over the past decade we have witnessed the evolution of wireless sensor networks, with advancements in hardware design, communication protocols, resource efficiency, and other aspects. Recently, there has been much focus on mobile sensor networks, and we have even seen the development of small-profile sensing devices that are able to control their own movement. Although it has been shown that mobility alleviates several issues relating to sensor network coverage and connectivity, many challenges remain. Among these, the need for position estimation is perhaps the most important. Not only is localization required to understand sensor data in a spatial context, but also for navigation, a key feature of mobile sensors. In this paper, we present a survey on localization methods for mobile wireless sensor networks. We provide taxonomies for mobile wireless sensors and localization, including common architectures, measurement techniques, and localization algorithms. We conclude with a description of real-world mobile sensor applications that require position estimation.

/pdf/a-survey-on-localization-for-mobile-wireless-sensor-networks-dnh83kqrru.pdf

A survey on localization for mobile wireless sensor networks

We present a novel radio interference based sensor localization method for wireless sensor networks. The technique relies on a pair of nodes emitting radio waves simultaneously at slightly different frequencies. The carrier frequency of the composite signal is between the two frequencies, but has a very low frequency envelope. Neighboring nodes can measure the energy of the envelope signal as the signal strength. The relative phase offset of this signal measured at two receivers is a function of the distances between the four nodes involved and the carrier frequency. By making multiple measurements in an at least 8-node network, it is possible to reconstruct the relative location of the nodes in 3D. Our prototype implementation on the MICA2 platform yields an average localization error as small as 3 cm and a range of up to 160 meters. In addition to this high precision and long range, the other main advantage of the Radio Interferometric Positioning System (RIPS) is the fact that it does not require any sensors other than the radio used for wireless communication.

/pdf/radio-interferometric-geolocation-1t27bc3ate.pdf

Radio interferometric geolocation

An ad-hoc wireless sensor network-based system is presented that detects and accurately locates shooters even in urban environments. The localization accuracy of the system in open terrain is competitive with that of existing centralized countersniper systems. However, the presented sensor network-based solution surpasses the traditional approach because it can mitigate acoustic multipath effects prevalent in urban areas and it can also resolve multiple simultaneous shots. These unique characteristics of the system are made possible by employing novel sensor fusion techniques that utilize the spatial and temporal diversity of multiple detections. In this article, in addition to the overall system architecture, the middleware services and the unique sensor fusion algorithms are described. An analysis of the experimental data gathered during field trials at US military facilities is also presented.

/pdf/countersniper-system-for-urban-warfare-klva8kb7rb.pdf

Countersniper system for urban warfare

Experiences developing a sensor network-based acoustic shooter localization system are presented. The system is able to localize the position of a shooter and the trajectory of the projectile using observed acoustic events, such as the muzzle blast and the ballistic shockwave. The network consists of a large number of cheap sensors communicating through an ad-hoc wireless network, which enables the system to resolve multiple simultaneous acoustic sources, eliminate multipath effects, tolerate multiple sensor failures while providing good coverage and high accuracy, even in such challenging environment as urban terrain. The paper describes the hardware and software platform developed for this application and summarizes the lessons learned during the development of the system.

/pdf/multiple-simultaneous-acoustic-source-localization-in-urban-2rr4mney5v.pdf

Multiple simultaneous acoustic source localization in urban terrain

http://www.math.u-szeged.hu/~mmaroti/pdf/2005%20Software%20composition%20and%20verification%20in%20SN.pdf

Software composition and verification for sensor networks

A method for radio interference based sensor localization. In one embodiment, the method has the steps of creating an interference signal from a first transmitter and a second transmitter, measuring phase offsets of the interference signal received by a first receiver and a second receiver, respectively, and determining the locations of the first and second transmitters and the first and second receivers from the measured phase offsets.

Sebestyén Dóra

Papers

Radio interferometric geolocation

Countersniper system for urban warfare

Multiple simultaneous acoustic source localization in urban terrain

Software composition and verification for sensor networks

System and methods of radio interference based localization in sensor networks