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Relocatable, automated cost-benefit analysis for marine sensor network design.

D'Este C, de Souza P, Sharman C, Allen S - Sensors (Basel) (2012)

Bottom Line: We describe a novel automated method for generating and combining cost and benefit values to decide on the best sensor locations using information about the specific constraints available in most coastal locations.Benefits in maximum coverage and reducing overall error are also determined using model output.This method demonstrates equivalent accuracy at predicting the whole system to expert-chosen locations, whilst significantly reducing the estimated costs.

View Article: PubMed Central - PubMed

Affiliation: Tasmanian ICT Centre, CSIRO, Castray Esplanade, Hobart, TAS 7000, Australia. Claire.DEste@csiro.au

ABSTRACT
When designing sensor networks, we need to ensure they produce representative and relevant data, but this must be offset by the financial cost of placing sensors. We describe a novel automated method for generating and combining cost and benefit values to decide on the best sensor locations using information about the specific constraints available in most coastal locations. Costs in maintenance, negotiation, equipment, exposure and communication are estimated using hydrodynamic models and Electronic Navigation Charts. Benefits in maximum coverage and reducing overall error are also determined using model output. This method demonstrates equivalent accuracy at predicting the whole system to expert-chosen locations, whilst significantly reducing the estimated costs.

No MeSH data available.


Related in: MedlinePlus

Cost structure at coordinates 42.9745°S, 147.762°E in South East Tasmania.
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f19-sensors-12-02874: Cost structure at coordinates 42.9745°S, 147.762°E in South East Tasmania.

Mentions: Figure 19 gives an example of a cost structure at 42.9745°S, 147.762°E in Norfolk Bay in South East Tasmania. This point lies on a shipping channel, so this makes up the greatest part of the cost for this location in the negotiation. The next biggest contribution is from the exposure, as there is a high current. It is also reasonably far from our laboratory giving it a fair cost in maintenance. It does not appear to be particularly deep or shallow at this location, so there is little impact from the equipment cost.


Relocatable, automated cost-benefit analysis for marine sensor network design.

D'Este C, de Souza P, Sharman C, Allen S - Sensors (Basel) (2012)

Cost structure at coordinates 42.9745°S, 147.762°E in South East Tasmania.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3376612&req=5

f19-sensors-12-02874: Cost structure at coordinates 42.9745°S, 147.762°E in South East Tasmania.
Mentions: Figure 19 gives an example of a cost structure at 42.9745°S, 147.762°E in Norfolk Bay in South East Tasmania. This point lies on a shipping channel, so this makes up the greatest part of the cost for this location in the negotiation. The next biggest contribution is from the exposure, as there is a high current. It is also reasonably far from our laboratory giving it a fair cost in maintenance. It does not appear to be particularly deep or shallow at this location, so there is little impact from the equipment cost.

Bottom Line: We describe a novel automated method for generating and combining cost and benefit values to decide on the best sensor locations using information about the specific constraints available in most coastal locations.Benefits in maximum coverage and reducing overall error are also determined using model output.This method demonstrates equivalent accuracy at predicting the whole system to expert-chosen locations, whilst significantly reducing the estimated costs.

View Article: PubMed Central - PubMed

Affiliation: Tasmanian ICT Centre, CSIRO, Castray Esplanade, Hobart, TAS 7000, Australia. Claire.DEste@csiro.au

ABSTRACT
When designing sensor networks, we need to ensure they produce representative and relevant data, but this must be offset by the financial cost of placing sensors. We describe a novel automated method for generating and combining cost and benefit values to decide on the best sensor locations using information about the specific constraints available in most coastal locations. Costs in maintenance, negotiation, equipment, exposure and communication are estimated using hydrodynamic models and Electronic Navigation Charts. Benefits in maximum coverage and reducing overall error are also determined using model output. This method demonstrates equivalent accuracy at predicting the whole system to expert-chosen locations, whilst significantly reducing the estimated costs.

No MeSH data available.


Related in: MedlinePlus