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Model and placement optimization of a sky surveillance visual sensor network
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.ORCID iD: 0000-0002-3429-273X
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Technology and Media.
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2011 (English)In: Proceedings - 2011 International Conference on Broadband and Wireless Computing, Communication and Applications, BWCCA 2011, IEEE Computer Society, 2011, 357-362 p.Conference paper, Published paper (Refereed)
Abstract [en]

Visual Sensor Networks (VSNs) are networks which generate two dimensional data. The major difference between VSN and ordinary sensor network is the large amount of data. In VSN, a large number of camera nodes form a distributed system which can be deployed in many potential applications. In this paper we present a model of the physical parameters of a visual sensor network to track large birds, such as Golden Eagle, in the sky. The developed model is used to optimize the placement of the camera nodes in the VSN. A camera node is modeled as a function of its field of view, which is derived by the combination of the lens focal length and camera sensor. From the field of view and resolution of the sensor, a model for full coverage between two altitude limits has been developed. We show that the model can be used to minimize the number of sensor nodes for any given camera sensor, by exploring the focal lengths that both give full coverage and meet the minimum object size requirement. For the case of large bird surveillance we achieve 100% coverage for relevant altitudes using 20 camera nodes per km2 for the investigated camera sensors.

Place, publisher, year, edition, pages
IEEE Computer Society, 2011. 357-362 p.
Keyword [en]
sensor networks, coverage, camera placement, surveillance, deployment optimization
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:miun:diva-15663DOI: 10.1109/BWCCA.2011.56Scopus ID: 2-s2.0-84855849512Local ID: STCISBN: 978-1-4577-1455-9 (print)OAI: oai:DiVA.org:miun-15663DiVA: diva2:473253
Conference
6th International Conference on Broadband and Wireless Computing, Communication and Applications, BWCCA-2011;Barcelona, Catalonia;26 October 2011through28 October 2011;Category numberE4532;Code88069
Available from: 2012-01-05 Created: 2012-01-05 Last updated: 2016-10-19Bibliographically approved
In thesis
1. Modelling and optimization of sky surveillance visual sensor network
Open this publication in new window or tab >>Modelling and optimization of sky surveillance visual sensor network
2012 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

A Visual Sensor Network (VSN) is a distributed system of a largenumber of camera sensor nodes. The main components of a camera sensornode are image sensor, embedded processor, wireless transceiver and energysupply. The major difference between a VSN and an ordinary sensor networkis that a VSN generates two dimensional data in the form of an image, whichcan be exploited in many useful applications. Some of the potentialapplication examples of VSNs include environment monitoring, surveillance,structural monitoring, traffic monitoring, and industrial automation.However, the VSNs also raise new challenges. They generate large amount ofdata which require higher processing powers, large bandwidth requirementsand more energy resources but the main constraint is that the VSN nodes arelimited in these resources.This research focuses on the development of a VSN model to track thelarge birds such as Golden Eagle in the sky. The model explores a number ofcamera sensors along with optics such as lens of suitable focal length whichensures a minimum required resolution of a bird, flying at the highestaltitude. The combination of a camera sensor and a lens formulate amonitoring node. The camera node model is used to optimize the placementof the nodes for full coverage of a given area above a required lower altitude.The model also presents the solution to minimize the cost (number of sensornodes) to fully cover a given area between the two required extremes, higherand lower altitudes, in terms of camera sensor, lens focal length, camera nodeplacement and actual number of nodes for sky surveillance.The area covered by a VSN can be increased by increasing the highermonitoring altitude and/or decreasing the lower monitoring altitude.However, it also increases the cost of the VSN. The desirable objective is toincrease the covered area but decrease the cost. This objective is achieved byusing optimization techniques to design a heterogeneous VSN. The core ideais to divide a given monitoring range of altitudes into a number of sub-rangesof altitudes. The sub-ranges of monitoring altitudes are covered by individualsub VSNs, the VSN1 covers the lower sub-range of altitudes, the VSN2 coversthe next higher sub-range of altitudes and so on, such that a minimum cost isused to monitor a given area.To verify the concepts, developed to design the VSN model, and theoptimization techniques to decrease the VSN cost, the measurements areperformed with actual cameras and optics. The laptop machines are used withthe camera nodes as data storage and analysis platforms. The area coverage ismeasured at the desired lower altitude limits of homogeneous as well asheterogeneous VSNs and verified for 100% coverage. Similarly, the minimumresolution is measured at the desired higher altitude limits of homogeneous aswell as heterogeneous VSNs to ensure that the models are able to track thebird at these highest altitudes.

Place, publisher, year, edition, pages
Sundsvall: Mid Sweden University, 2012
Series
Mid Sweden University licentiate thesis, ISSN 1652-8948 ; 86
National Category
Embedded Systems
Identifiers
urn:nbn:se:miun:diva-17123 (URN)STC (Local ID)978-91-87103-25-4 (ISBN)STC (Archive number)STC (OAI)
Supervisors
Available from: 2012-10-02 Created: 2012-10-02 Last updated: 2016-10-20Bibliographically approved
2. Modelling, optimization and design of visual sensor networks for sky surveillance
Open this publication in new window or tab >>Modelling, optimization and design of visual sensor networks for sky surveillance
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Place, publisher, year, edition, pages
Sundsvall: Mid Sweden University, 2013. 210 p.
Series
Mid Sweden University doctoral thesis, ISSN 1652-893X ; 166
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:miun:diva-21022 (URN)978-91-87557-11-8 (ISBN)
Supervisors
Available from: 2014-01-13 Created: 2014-01-13 Last updated: 2014-04-24Bibliographically approved

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Ahmad, NaeemLawal, NajeemO'Nils, MattiasOelmann, BengtImran, MuhammadKhursheed, Khursheed
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