A Wireless Sensor Network (WSN) for Structural Health Monitoring (SHM) is designed, implemented, deployed and tested on the 4200 ft long main span and the south tower of the Golden Gate Bridge (GGB). Ambient structural vibrations are reliably measured at a low cost and without interfering with the operation of the bridge. Requirements that SHM imposes on WSN are identified and new solutions to meet these requirements are proposed and implemented. In the GGB deployment, 64 nodes are distributed over the main span and the tower, collecting ambient vibrations synchronously at 1 kHz rate, with less than 10 mus jitter, and with an accuracy of 30 muG. The sampled data is collected reliably over a 46-hop network, with a bandwidth of 441 B/s at the 46th hop. The collected data agrees with theoretical models and previous studies of the bridge. The deployment is the largest WSN for SHM.

http://glaser.berkeley.edu/glaserdrupal/pdf/EECS-2006-121.pdf

Health monitoring of civil infrastructures using wireless sensor networks

We present a science-centric evaluation of a 19-day sensor network deployment at Reventador, an active volcano in Ecuador. Each of the 16 sensors continuously sampled seismic and acoustic data at 100 Hz. Nodes used an event-detection algorithm to trigger on interesting volcanic activity and initiate reliable data transfer to the base station. During the deployment, the network recorded 229 earthquakes, eruptions, and other seismoacoustic events.The science requirements of reliable data collection, accurate event detection, and high timing precision drive sensor networks in new directions for geophysical monitoring. The main contribution of this paper is an evaluation of the sensor network as a scientific instrument, holding it to the standards of existing instrumentation in terms of data fidelity (the quality and accuracy of the recorded signals) and yield (the quantity of the captured data). We describe an approach to time rectification of the acquired signals that can recover accurate timing despite failures of the underlying time synchronization protocol. In addition, we perform a detailed study of the sensor network's data using a direct comparison to a standalone data logger, as well as an investigation of seismic and acoustic wave arrival times across the network.

/pdf/fidelity-and-yield-in-a-volcano-monitoring-sensor-network-28r68uycla.pdf

Fidelity and yield in a volcano monitoring sensor network

This book primarily discusses issues related to the mining aspects of data streams and it is unique in its primary focus on the subject This volume covers mining aspects of data streams comprehensively: each contributed chapter contains a survey on the topic, the key ideas in the field for that particular topic, and future research directions The book is intended for a professional audience composed of researchers and practitioners in industry This book is also appropriate for advanced-level students in computer science

Data Streams: Models and Algorithms

Appearing in 1st IEEE International Workshop on Sensor Net Protocols and Applications (SNPA). Anchorage, Alaska, USA. May 11, 2003. RMST: Reliable Data Transport in Sensor Networks Fred Stann, John Heidemann Abstract – Reliable data transport in wireless sensor networks is a multifaceted problem influenced by the physical, MAC, network, and transport layers. Because sensor networks are subject to strict resource constraints and are deployed by single organizations, they encourage revisiting traditional layering and are less bound by standardized placement of services such as reliability. This paper presents analysis and experiments resulting in specific recommendations for implementing reliable data transport in sensor nets. To explore reliability at the transport layer, we present RMST (Reliable Multi- Segment Transport), a new transport layer for Directed Diffusion. RMST provides guaranteed delivery and fragmentation/reassembly for applications that require them. RMST is a selective NACK-based protocol that can be configured for in-network caching and repair. Second, these energy constraints, plus relatively low wireless bandwidths, make in-network processing both feasible and desirable [3]. Third, because nodes in sensor networks are usually collaborating towards a common task, rather than representing independent users, optimization of the shared network focuses on throughput rather than fairness. Finally, because sensor networks are often deployed by a single organization with inexpensive hardware, there is less need for interoperability with existing standards. For all of these reasons, sensor networks provide an environment that encourages rethinking the structure of traditional communications protocols. The main contribution is an evaluation of the placement of reliability for data transport at different levels of the protocol stack. We consider implementing reliability in the MAC, transport layer, application, and combinations of these. We conclude that reliability is important at the MAC layer and the transport layer. MAC-level reliability is important not just to provide hop-by-hop error recovery for the transport layer, but also because it is needed for route discovery and maintenance. (This conclusion differs from previous studies in reliability for sensor nets that did not simulate routing. [4]) Second, we have developed RMST (Reliable Multi-Segment Transport), a new transport layer, in order to understand the role of in- network processing for reliable data transfer. RMST benefits from diffusion routing, adding minimal additional control traffic. RMST guarantees delivery, even when multiple hops exhibit very high error rates. 1 Introduction Wireless sensor networks provide an economical, fully distributed, sensing and computing solution for environments where conventional networks are impractical. This paper explores the design decisions related to providing reliable data transport in sensor nets. The reliable data transport problem in sensor nets is multi-faceted. The emphasis on energy conservation in sensor nets implies that poor paths should not be artificially bolstered via mechanisms such as MAC layer ARQ during route discovery and path selection [1]. Path maintenance, on the other hand, benefits from well- engineered recovery either at the MAC layer or the transport layer, or both. Recovery should not be costly however, since many applications in sensor nets are impervious to occasional packet loss, relying on the regular delivery of coarse-grained event descriptions. Other applications require loss detection and repair. These aspects of reliable data transport include the provision of guaranteed delivery and fragmentation/ reassembly of data entities larger than the network MTU. Sensor networks have different constraints than traditional wired nets. First, energy constraints are paramount in sensor networks since nodes can often not be recharged, so any wasted energy shortens their useful lifetime [2]. This work was supported by DARPA under grant DABT63-99-1-0011 as part of the SCAADS project, and was also made possible in part due to support from Intel Corporation and Xerox Corporation. Fred Stann and John Heidemann are with USC/Information Sciences Institute, 4676 Admiralty Way, Marina Del Rey, CA, USA E-mail: fstann@usc.edu, johnh@isi.edu. 2 Architectural Choices There are a number of key areas to consider when engineering reliability for sensor nets. Many current sensor networks exhibit high loss rates compared to wired networks (2% to 30% to immediate neighbors)[1,5,6]. While error detection and correction at the physical layer are important, approaches at the MAC layer and higher adapt well to the very wide range of loss rates seen in sensor networks and are the focus of this paper. MAC layer protocols can ameliorate PHY layer unreliability, and transport layers can guarantee delivery. An important question for this paper is the trade off between implementation of reliability at the MAC layer (i.e. hop to hop) vs. the Transport layer, which has traditionally been concerned with end-to-end reliability. Because sensor net applications are distributed, we also considered implementing reliability at the application layer. Our goal is to minimize the cost of repair in terms of transmission.

RMST: Reliable Data Transport in Sensor Networks

/pdf/environmental-sensor-networks-a-revolution-in-the-earth-1gkgkhzefh.pdf

Environmental Sensor Networks: A revolution in the earth system science?

Structural monitoring---the collection and analysis of structural response to ambient or forced excitation--is an important application of networked embedded sensing with significant commercial potential. The first generation of sensor networks for structural monitoring are likely to be data acquisition systems that collect data at a single node for centralized processing. In this paper, we discuss the design and evaluation of a wireless sensor network system (called Wisden for structural data acquisition. Wisden incorporates two novel mechanisms, reliable data transport using a hybrid of end-to-end and hop-by-hop recovery, and low-overhead data time-stamping that does not require global clock synchronization. We also study the applicability of wavelet-based compression techniques to overcome the bandwidth limitations imposed by low-power wireless radios. We describe our implementation of these mechanisms on the Mica-2 motes and evaluate the performance of our implementation. We also report experiences from deploying Wisden on a large structure.

/pdf/a-wireless-sensor-network-for-structural-monitoring-5028lt76o3.pdf

A wireless sensor network For structural monitoring

A Wireless Sensor Network For Structural Monitoring ∗ Ning Xu Sumit Rangwala Alan Broad Krishna Kant Chintalapudi Deepak Ganesan Ramesh Govindan Deborah Estrin ABSTRACT Structural monitoring—the collection and analysis of structural re- sponse to ambient or forced excitation–is an important application of networked embedded sensing with signiﬁcant commercial po- tential. The ﬁrst generation of sensor networks for structural mon- itoring are likely to be data acquisition systems that collect data at a single node for centralized processing. In this paper, we dis- cuss the design and evaluation of a wireless sensor network sys- tem (called Wisden) for structural data acquisition. Wisden in- corporates two novel mechanisms, reliable data transport using a hybrid of end-to-end and hop-by-hop recovery, and low-overhead data time-stamping that does not require global clock synchroniza- tion. We also study the applicability of wavelet-based compression techniques to overcome the bandwidth limitations imposed by low- power wireless radios. We describe our implementation of these mechanisms on the Mica-2 motes and evaluate the performance of our implementation. We also report experiences from deploying Wisden on a large structure. General Terms Reliability, Design Keywords Sensor Network, Structural Health Monitoring, Wisden INTRODUCTION Categories and Subject Descriptors C.2.1 [Computer Communication Networks]: Wireless commu- nication; C.3 [Special-Purpose and Application-Based Systems]: Embedded Systems ∗ This material is based upon work supported by the National Sci- ence Foundation under Grants No. 0121778 (Center for Embedded Networked Systems) and 0325875 (ITR: Structural Health Moni- toring Using Local Excitations and Dense Sensing). Any opinions, ﬁndings and conclusions or recomendations expressed in this ma- terial are those of the author(s) and do not necessarily reﬂect the views of the National Science Foundation (NSF). † Computer Science Department, University of Southern California, {nxu, srangwal, chintala, ramesh}@usc.edu ‡ Current Afﬁliation - Center for Embedded Networked Sensing, Los Angeles § Computer Science Department, University of California, Los An- geles {deepak, destrin}@cs.ucla.edu ¶ Crossbow Technology Inc. abroad@xbow.com Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for proﬁt or commercial advantage and that copies bear this notice and the full citation on the ﬁrst page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior speciﬁc permission and/or a fee. SenSys’04, November 3–5, 2004, Baltimore, Maryland, USA. Copyright 2004 ACM 1-58113-879-2/04/0011 ... $ 5.00. Structural health monitoring systems seek to detect and local- ize damage in buildings, bridges, ships, and aircraft. The design of such systems is an active and well-established area of research. When built, such systems would infer the existence and location of damage by measuring structural response to ambient or forced excitation. Wireless sensor networks are a natural candidate for structural health monitoring systems, since they enable dense in- situ sensing and simplify deployment of instrumentation. However, techniques for damage assessment are quite complex, and practical wireless networked structural health monitoring systems are sev- eral years away. Wireless sensor networks do have a more immediate role to play in structural monitoring. Advances in structural engineering de- pend upon the availability of many detailed data sets that record the response of different structures to ambient vibration (caused, for example, by earthquakes, wind, or passing vehicles) or forced excitation (delivered by large special-purpose shakers). Currently, structural engineers use wired or single-hop wireless data acqui- sition systems to acquire such data sets. These systems consist of a device that collects and stores vibration measurements from a small number of sensors. However, power and wiring constraints imposed by these systems can increase the cost of acquiring these data sets, impose signiﬁcant setup delays, and limit the number and location of sensors. Wireless sensor networks can help address these issues. In this paper, we describe the design of Wisden, a wireless sen- sor network system for structural-response data acquisition. Wis- den continuously collects structural response data from a multi-hop network of sensor nodes, and displays and stores the data at a base station. Wisden can be thought of as a ﬁrst-generation wireless structural monitoring system; it incorporates some in-network pro- cessing, but later systems will move more processing into the net- work once the precise structural monitoring applications are better understood. In being essentially a data collection system, Wisden resembles other early sensor networks such as those being deployed for habitat monitoring [10]. While the architecture of Wisden is simple—a base station cen- trally collecting data—its design is a bit more challenging than that of other sensor networks built till date. Structural response data is generated at higher data rates than most sensing applications

A Wireless Sensor Network for Structural Monitoring

A plurality of modules interact to form an adaptive network in which each module transmits and receives data signals indicative of proximity of objects. A central computer accumulates the data produced or received and relayed by each module for analyzing proximity responses to transmit through the adaptive network control signals to a selectively-addressed module to respond to computer analyses of the data accumulated from modules forming the adaptive network. Interactions of local processors in modules that sense an intrusion determine the location and path of movements of the intruding object and control cameras in the modules to retrieve video images of the intruding object. Multiple operational frequencies in adaptive networks permit expansions by additional networks that each operate at separate radio frequencies to avoid overlapping interaction. Additional modules may be introduced into operating networks without knowing the operating frequency at the time of introduction. Remote modules operating as leaf nodes of the adaptive network actively adapt to changed network conditions upon awaking from power-conserving sleep mode. New programs are distributed to all or selected modules under control of the base station.

Adaptive network and method

A plurality of modules interact to form an adaptive network in which each module transmits and receives data signals indicative of radio-frequency identification signals, and indicative of proximity sensing at the module. A central computer accumulates the data produced or received and relayed by each module for analyzing inventory, pricing and customer responses to transmit through the adaptive network signals representative of information to be displayed at selectively-addresses modules in response to computer analyses of the data accumulated from modules forming an adaptive network.

Adaptive sensing network

A method and system updates a network of sensors remotely through the use of a communication link. The sensors to be updated as well as data files to perform the updating are selected at a base station. The selected sensors are notified of the upcoming update by the base station and may accept or reject the update. The sensors that approve the update then receive data files through the communication link. The sensors notify the base station of any missing data files, which are then retransmitted to all sensors that may be missing data files from the first transmission. After the sensors receive all data files, the update is initiated.

Alan S. Broad

Papers

A wireless sensor network For structural monitoring

A Wireless Sensor Network for Structural Monitoring

Adaptive network and method

Adaptive sensing network

System and method for updating a network of remote sensors