Habitat monitoring with sensor networks

Szewczyk, Robert; Osterweil, Eric; Polastre, Joseph; Hamilton, Michael; Mainwaring, Alan; Estrin, Deborah

doi:10.1145/990680.990704

Cited by 546 publications

(269 citation statements)

References 8 publications

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“…Local computational capabilities on the individual sensor node allow complex filtering and triggering functions, and application or sensor-specific data compression algorithms. The application of sensor networks for animal monitoring was addressed by Szewczyk et al (2004), Wang et al (2006), Bishop-Hurley et al (2007), Nadimi et al (2007) and Schwager et al (2007).…”

Section: Introductionmentioning

confidence: 99%

ZigBee-based wireless sensor networks for monitoring animal presence and pasture time in a strip of new grass

Nadimi

Søgaard

Bak

et al. 2008

Computers and Electronics in Agriculture

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ZigBee-based wireless sensor networks for monitoring animal presence and pasture time in a strip of new grass Nadimi, Esmaeil; Søgaaard, Henning T.; Bak, Thomas; Oudshoorn, Frank W. General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.? Users may download and print one copy of any publication from the public portal for the purpose of private study or research. ? You may not further distribute the material or use it for any profit-making activity or commercial gain ? You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us at vbn@aub.aau.dk providing details, and we will remove access to the work immediately and investigate your claim.Downloaded from vbn.aau.dk on: May 08, 2018 c o m p u t e r s a n d e l e c t r o n i c s i n a g r i c u l t u r e 6 1 ( 2 0 0 8 ) The problem of online monitoring of cows' presence and pasture time in an extended area covered by a strip of new grass using wireless sensor networks has been addressed. The total pasture time in the extended area was estimated by measuring the pasture time in a specific part of that area called the gateway connectivity area where sensor nodes mounted on the cows could communicate directly with a gateway. Packet loss causes a node that was present in the connectivity range of the gateway frequently to be classified as an absent node. Therefore, a moving average window with optimal window length and threshold was designed to minimize the misclassification. As the measured pasture time in the gateway connectivity area was an underestimation of the total pasture time in the extended area, an area-based correction factor, same for all individual animals was applied.As only 23% of the animals in a herd were equipped to be monitored by sensor nodes, investigations to evaluate if the monitored number of animals could represent the whole herd were of great importance. To accomplish the investigations, the number of monitored cows by sensor nodes and the total number of cows (with and without sensor nodes) in the extended area were counted manually each minute over a period of 3 h during 3 days.Pearson chi-square test of goodness of fit showed that the number of cows in the extended area was normally distributed. Furthermore, a statistical test showed that the mean number of monitored cows in the extended area and the mean of total number of cows in the extended area corresponded with the percentage of monitored cows by sensor nodes in the herd (23%).

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Section: Introductionmentioning

confidence: 99%

ZigBee-based wireless sensor networks for monitoring animal presence and pasture time in a strip of new grass

Nadimi

Søgaard

Bak

et al. 2008

Computers and Electronics in Agriculture

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“…As stated before, A can be estimated from the relation between shared neighbors S ij to total neighbors N i which can be computed locally using Equation (1).…”

Section: Distributed Geometric Distance Estimation (Geode)mentioning

confidence: 99%

“…In addition, GPS does not help in indoor or underwater scenarios. Nevertheless, location-awareness plays an important role such as for the allocation of event reporting in a monitoring sensor network [1][2][3], location dependent routing [4][5][6][7][8] assistance of group querying [9], pattern formation [10,11] and many more. For that reason, alternative localization techniques were proposed to derive the location of each device in the network (cf.…”

Section: Introductionmentioning

confidence: 99%

Distributed Geometric Distance Estimation in Ad Hoc Networks

Merkel

Mostaghim

Schmeck

2012

Ad-Hoc, Mobile, and Wireless Networks

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Abstract. Distributed localization algorithms for nodes in ad hoc networks are essential for many applications. A major task when localizing nodes is to accurately estimate distances. So far, distance estimation is often based on counting the minimum number of nodes on the shortest routing path (hop count) and presuming a fixed width for one hop. This is prone to error as the length of one hop can vary significantly. In this paper, a distance estimation method is proposed, which relies on the number of shared communication neighbors and applies geometric properties to the network structure. It is shown that the geometric approach provides reliable estimates for the distance between any two adjacent nodes in a network. Experiments reveal that the estimation has less relative percentage error compared to a hop based algorithm in networks with different node distributions.

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“…Communications in a WSN typically takes place in an ad hoc manner [2]. Applications of WSNs include surveillance and agriculture, habitat, traffic, and civil infrastructure monitoring [3][4][5][6][7]. One of the major tasks of a WSN is to detect events occurring in the sensing field.…”

Section: Introduction and Problem Statementmentioning

confidence: 99%

Using event detection latency to evaluate the coverage of a wireless sensor network

Wang¹,

Cheng²,

Tseng³

2007

Computer Communications

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A wireless sensor network (WSN) consists of many tiny and low-power devices deployed in a sensing field. One of the major tasks of a WSN is to monitor the surrounding environment and to detect events occurring in the sensing field. Given an event appearing in a WSN, the event detection latency is to model the time that it takes for the WSN to be aware of the event.In this work, we analyze the latency using a probabilistic approach under an any-sensor-detection and a k-sensor-detection models, where k > 1 is an integer. Such an analysis can be used as an index to evaluate a WSN's coverage and thus can help guide the deployment of a WSN. We also develop simulations to verify our analytical results.

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Habitat monitoring with sensor networks

Abstract: These networks deliver to ecologists data on localized environmental conditions at the scale of individual organisms to help settle large-scaleland-use issues affecting animals, plants, and people.

Cited by 546 publications

References 8 publications

ZigBee-based wireless sensor networks for monitoring animal presence and pasture time in a strip of new grass

ZigBee-based wireless sensor networks for monitoring animal presence and pasture time in a strip of new grass

Distributed Geometric Distance Estimation in Ad Hoc Networks

Using event detection latency to evaluate the coverage of a wireless sensor network

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