Monitoring volcanic eruptions with a wireless sensor network

Werner-Allen, G.; Johnson, Jeff; Ruiz, Mario; Lees, Jonathan M.; Welsh, Matt

doi:10.1109/ewsn.2005.1462003

Cited by 346 publications

(209 citation statements)

References 20 publications

Supporting

Mentioning

198

Contrasting

Unclassified

Order By: Relevance

“…The definitions of events in previous literature fall into two categories: thresholdbased [5,4,3] and non-threshold-based [1,6], the methods of which are discussed in the following two paragraphs correspondingly.…”

Section: Related Workmentioning

confidence: 99%

“…Once a tuple is satisfied, a report is returned. [3] develops a local event detection method -exponentially weighted moving average(EWMA) without collecting neighbors' readings, while still maintaining certain reliability in the presence of reading errors. It calculates short-term and long-term moving averages with different gain parameters and compares the ratio of the short-term average to the long-term average with a predefined threshold to decide whether an event has occurred.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Reliable and Fast Detection of Gradual Events in Wireless Sensor Networks

Peng

Gao

et al. 2008

Wireless Algorithms, Systems, and Applications

View full text Add to dashboard Cite

Abstract. Event detection is among the most important applications of wireless sensor networks. Due to the fact that sensor readings do not always represent the true attribute values, previous literatures suggested threshold-based voting mechanism which involves collecting votes of all neighbors to disambiguate node failures from events, instead of reporting an event directly based on the judgement of single sensor node. Although such mechanism significantly reduces false positives, it inevitably introduces false negatives which lead to a detection delay under the scenario of gradual events. In this paper, we propose a new detection method -the bit-string match voting (BMV), which provides a response time close to that of the direct reporting method and a false positive rate even lower than that of the threshold-based voting method. Furthermore, BMV is able to avoid repeated and redundant reports of the same event, thus prolongs the life of the network. Extensive simulations are given to demonstrate and verify the advantages of BMV.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Reliable and Fast Detection of Gradual Events in Wireless Sensor Networks

Peng

Gao

et al. 2008

Wireless Algorithms, Systems, and Applications

View full text Add to dashboard Cite

show abstract

“…The tracking of mobile targets is one typical task for geosensor networks [16,18]. Other applications have included observing hazards [19], monitoring seismic activity [20,21], or managing traffic flow [11]. When the sensor nodes are deployed to moving entities in a dynamic scenario, we refer to a mobile wireless sensor network (mWSN).…”

Section: Mobile Wireless Sensor Networkmentioning

confidence: 99%

Decentralized Movement Pattern Detection amongst Mobile Geosensor Nodes

Laube

Duckham

Wolle

2008

Geographic Information Science

View full text Add to dashboard Cite

Abstract. Movement patterns, like flocking and converging, leading and following, are examples of high-level process knowledge derived from lowlevel trajectory data. Conventional techniques for the detection of movement patterns rely on centralized "omniscient" computing systems that have global access to the trajectories of mobile entities. However, in decentralized spatial information processing systems, exemplified by wireless sensor networks, individual processing units may only have access to local information about other individuals in their immediate spatial vicinity. Where the individuals in such decentralized systems are mobile, there is a need to be able to detect movement patterns using collaboration between individuals, each of which possess only partial knowledge of the global system state. This paper presents an algorithm for decentralized detection of the movement pattern flock, with applications to mobile wireless sensor networks. The algorithm's reliability is evaluated through testing on simulated trajectories emerging from unconstrained random movement and correlated random walk.

show abstract

“…These constraints appear in terms of energy constraints, available memory constraints [9], and, in some scenarios, delay constraints [2,[11][12][13]. Accordingly, we desire to reduce the energy overhead due to communications as much as possible, while keeping memory and delay requirements as low as possible.…”

Section: Wsn: Why Is Analysis Difficult?mentioning

confidence: 99%

“…Finally, but most importantly, in many applications, both the packet size and data transmission rate will be likely to be very small: for example, 36 bytes in [10], 32 bytes data in [13], up to 16 bits in [14], few of tens of bits in most medical applications [15], etc. In terms of transmission rate, Mica2 (19.2 kbps) and MicaZ (250 kbps) are well-known examples.…”

Section: Application Typesmentioning

confidence: 99%

Error resilient data transport in sensor network applications: A generic perspective

Agarwal

Popovici

Sala

et al. 2008

Circuit Theory & Apps

View full text Add to dashboard Cite

SUMMARYThe error recovery problem in wireless sensor networks is studied from a generic resource-constrained energy-optimization perspective. To characterize the features of error recovery schemes that suit the majority of applications, an energy model is developed and inferences are drawn based on a suitable performance metric. For applications that require error control coding, an efficient scheme is proposed based on an interesting observation related to shortened Reed-Solomon (RS) codes for packet reliability. It is shown that multiple instances ( ) of RS codes defined on a smaller alphabet combined with interleaving results in smaller resource usage, while the performance exceeds the benefits of a shortened RS code defined over a larger alphabet. In particular, the proposed scheme can have an error correction capability of up to times larger than that of the conventional RS scheme without changing the rate of the code with much lower power, timing and memory requirements. Implementation results show that such a scheme is 43% more power efficient compared with the RS scheme with the same code rate. Besides, such an approach results in 46% faster computations and 53% reduction in memory requirements.

show abstract

Monitoring volcanic eruptions with a wireless sensor network

Cited by 346 publications

References 20 publications

Reliable and Fast Detection of Gradual Events in Wireless Sensor Networks

Reliable and Fast Detection of Gradual Events in Wireless Sensor Networks

Decentralized Movement Pattern Detection amongst Mobile Geosensor Nodes

Error resilient data transport in sensor network applications: A generic perspective

Contact Info

Product

Resources

About