Acoustical Ranging Techniques in Embedded Wireless Sensor Networked Devices

Location sensing provides endless opportunities for a wide range of applications in GPS-obstructed environments; where, typically, there is a need for higher degree of accuracy. In this article, we focus on robust range estimation, an important prerequisite for fine-grained localization. Motivated by the promise of acoustic in delivering high ranging accuracy, we present the design, implementation and evaluation of acoustic (both ultrasound and audible) ranging systems.We distill the limitations of acoustic ranging; and present efficient signal designs and detection algorithms to overcome the challenges of coverage, range, accuracy/resolution, tolerance to Doppler’s effect, and audible intensity. We evaluate our proposed techniques experimentally on TWEET, a low-power platform purpose-built for acoustic ranging applications. Our experiments demonstrate an operational range of 20 m (outdoor) and an average accuracy 2 cm in the ultrasound domain. Finally, we present the design of an audible-range acoustic tracking service that encompasses the benefits of a near-inaudible acoustic broadband chirp and approximately two times increase in Doppler tolerance to achieve better performance

Intelligent deployment strategies for passive underwater sensor networks

Passive underwater sensor networks are often used to monitor a general area of the ocean, a port or military installation, or to detect underwater vehicles near a high value unit at sea, such as a fuel ship or aircraft carrier. Deploying an underwater sensor network across a large area of interest (AOI), for military surveillance purposes, is a significant challenge due to the inherent difficulties posed by the underwater channel in terms of sensing and communications between sensors. Moreover, monetary constraints, arising from the high cost of these sensors and their deployment, limit the number of available sensors. As a result, sensor deployment must be done as efficiently as possible. The objective of this work is to develop a deployment strategy for passive underwater sensors in an area clearance scenario, where there is no apparent target for an adversary to gravitate towards, such as a ship or a port, while considering all factors pertinent to underwater sensor deployment. These factors include sensing range, communications range, monetary costs, link redundancy, range dependence, and probabilistic visitation. A complete treatment of the underwater sensor deployment problem is presented in this work from determining the purpose of the sensor field to physically deploying the sensors. Assuming a field designer is given a suboptimal number of sensors, they must be methodically allocated across an AOI. The Game Theory Field Design (GTFD) model, proposed in this work, is able to accomplish this task by evaluating the acoustic characteristics across the AOI and allocating sensors accordingly. Since GTFD considers only circular sensing coverage regions, an extension is proposed to consider irregularly shaped regions. Sensor deployment locations are planned using a proposed evolutionary approach, called the Underwater Sensor Deployment Evolutionary Algorithm, which utilizes two suitable network topologies, mesh and cluster. The effects of these topologies, and a sensor\u27s communications range, on the sensing capabilities of a sensor field, are also investigated. Lastly, the impact of deployment imprecision on the connectivity of an underwater sensor field, using a mesh topology, is analyzed, for cases where sensor locations after deployment do not exactly coincide with planned sensor locations

Connectivity-guaranteed and obstacle-adaptive deployment schemes for mobile sensor networks

Mobile sensors can relocate and self-deploy into a network. While focusing on the problems of coverage, existing deployment schemes largely over-simplify the conditions for network connectivity: they either assume that the communication range is large enough for sensors in geometric neighborhoods to obtain location information through local communication, or they assume a dense network that remains connected. In addition, an obstacle-free field or full knowledge of the field layout is often assumed. We present new schemes that are not governed by these assumptions, and thus adapt to a wider range of application scenarios. The schemes are designed to maximize sensing coverage and also guarantee connectivity for a network with arbitrary sensor communication/sensing ranges or node densities, at the cost of a small moving distance. The schemes do not need any knowledge of the field layout, which can be irregular and have obstacles/holes of arbitrary shape. Our first scheme is an enhanced form of the traditional virtual-force-based method, which we term the Connectivity-Preserved Virtual Force (CPVF) scheme. We show that the localized communication, which is the very reason for its simplicity, results in poor coverage in certain cases. We then describe a Floor-based scheme which overcomes the difficulties of CPVF and, as a result, significantly outperforms it and other state-of-the-art approaches. Throughout the paper our conclusions are corroborated by the results from extensive simulations

Miniaturized antenna and transponder based wireless sensors for internet of things in healthcare

Future medical and healthcare systems will be largely improved by the wide-spreading of internet of things (IoTs). One of the crucial challenges of IoTs for healthcare is at the wireless sensors. Miniaturization of sensor node profile, minimizing power consumption as well as lowering down design/production cost of antenna, RF circuits and sensor modules have become the key issues for realizing more exciting applications in medical and healthcare fields that never seemed to be possible before. In this dissertation work, we first focus on electrically small antenna (ESA) design and fabrication for medical telemetry. A comprehensive analysis of the radiation properties of a novel electrically small folded ellipsoidal ESA is presented, showing its ability to self-resonate and impedance match without external components. It will benefit various size-restricted applications especially with wireless medical implants. The second focus is on healthcare sensors using ESA as the sensing agent, which saves the power and cost by eliminating the need of extra sensing modules. Specifically, miniaturized helix ESAs are integrated with drug reservoirs to function as wireless transponder sensors for real-time drug dosage monitoring. We also introduce a system level innovation of a passive wireless harmonic transponder/harmonic sniffer/frequency hopped interrogator based sensing system. The μL- liquid level resolution and absolute-accuracy passive sensing is demonstrated in the presence of strong direct coupling, background scatters, distance variance as well as near-filed human body movement interference. Furthermore, we investigate how modern ubiquitous wireless sensor networks could take advantage of sensitive nanostructure materials for enhanced performance. Here we propose a new paradigm of chemically-gated mixed modulation on a single homogeneous graphene device in which the chemical exposure directly modulates an electrical carrier signal. To make the device ubiquitously reusable, a method of precisely tuning the charge neutrality point (Vcnp) is introduced by electrochemical calibration with gate voltage pulse sequence. Such chemically gated graphene modulator can be potentially used in a harmonic transponder as a passive ubiquitous sensor node for chemical and bio sensing applications. Overall the research work presented in the dissertation will help enable cost and power-efficient wireless sensor networks in future healthcare IoTs.Electrical and Computer Engineerin

Multi-TRxPs for Industrial Automation with 5G URLLC Requirements

The Fifth Generation (5G) Ultra Reliable Low Latency Communication (URLLC) is envisioned to be one of the most promising drivers for many of the emerging use cases, including industrial automation. In this study, a factory scenario with mobile robots connected via a 5G network with two indoor cells is analyzed. The aim of this study is to analyze how URLLC requirements can be met with the aid of multi-Transmission Reception Points (TRxPs), for a scenario, which is interference limited. By means of simulations, it is shown that availability and reliability can be significantly improved by using multi-TRxPs, especially when the network becomes more loaded. In fact, optimized usage of multi-TRxPs can allow the factory to support a higher capacity while still meeting URLLC requirements. The results indicate that the choice of the number of TRxPs, which simultaneously transmit to a UE, and the locations of the TRxPs around the factory, is of high importance. A poor choice could worsen interference and lower reliability. The general conclusion is that it is best to deploy many TRxPs, but have the UE receive data from only one or maximum two at a time. Additionally, the TRxPs should be distributed enough in the factory to be able to properly improve the received signal, but far enough from the TRxPs of the other cell to limit the additional interference caused

Minimum Energy Broadcast in Duty Cycled Wireless Sensor Networks

We study the problem of finding a minimum energy broadcast tree in duty cycled wireless sensor networks. In such networks, every node has a wakeup schedule and is awake and ready to receive packets or transmit in certain time slots during the schedule and asleep during the rest of the schedule. We assume that a forwarding node needs to stay awake to forward a packet to the next hop neighbor until the neighbor is awake. The minimum energy broadcast tree minimizes the number of additional time units that nodes have to stay awake in order to accomplish broadcast. We show that finding the minimum energy broadcast tree is NP-hard. We give two algorithms for finding energy-efficient broadcast trees in such networks. We performed extensive simulations to study the performance of these algorithms and compare them with previously proposed algorithms. Our results show that our algorithms exhibit the best performance in terms of average number of additional time units a node needs to be awake, as well as in terms of the smallest number of highly loaded nodes, while being competitive with previous algorithms in terms of the total number of transmissions and delay

SoundCompass: a distributed MEMS microphone array-based sensor for sound source localization

Sound source localization is a well-researched subject with applications ranging from localizing sniper fire in urban battlefields to cataloging wildlife in rural areas. One critical application is the localization of noise pollution sources in urban environments, due to an increasing body of evidence linking noise pollution to adverse effects on human health. Current noise mapping techniques often fail to accurately identify noise pollution sources, because they rely on the interpolation of a limited number of scattered sound sensors. Aiming to produce accurate noise pollution maps, we developed the SoundCompass, a low-cost sound sensor capable of measuring local noise levels and sound field directionality. Our first prototype is composed of a sensor array of 52 Microelectromechanical systems (MEMS) microphones, an inertial measuring unit and a low-power field-programmable gate array (FPGA). This article presents the SoundCompass's hardware and firmware design together with a data fusion technique that exploits the sensing capabilities of the SoundCompass in a wireless sensor network to localize noise pollution sources. Live tests produced a sound source localization accuracy of a few centimeters in a 25-m2 anechoic chamber, while simulation results accurately located up to five broadband sound sources in a 10,000-m2 open field