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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

Regions with available hydrodynamic models explored in this paper: (a) South East Tasmania; (b) Macquarie Harbour; and (c) Moreton Bay.
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f1-sensors-12-02874: Regions with available hydrodynamic models explored in this paper: (a) South East Tasmania; (b) Macquarie Harbour; and (c) Moreton Bay.

Mentions: The hydrodynamic model is based on Herzfeld’s general purpose model for estuaries to regional ocean domains [14]. The main model is for South-East Tasmania (43.1°S, 147.5°E), but models are also applied at Macquarie Harbour (42.3°S, 145.4°E), Moreton Bay (27.2°S, 153.2°E), and the Great Barrier Reef (20.1°S, 149.9°E). The three regions explored in this paper are shown in Figure 1. The model provides three-dimensional distributions of temperature, salinity, current velocity, density, passive tracers, mixing coefficients and sea level. From inputs such as wind, pressure, surface heat and tides, the model calculates momentum, continuity, and conservation of heat and salt. The model is based on the primitive equations and employs the hydrostatic and Boussinesq assumptions on currents [15]. The grid itself is non-uniform and curvilinear with grid spacing between approximately 200 m and 800 m. There is higher resolution upriver and in coastal regions, and relatively low resolution further out to sea.


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

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

Regions with available hydrodynamic models explored in this paper: (a) South East Tasmania; (b) Macquarie Harbour; and (c) Moreton Bay.
© Copyright Policy
Related In: Results  -  Collection

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

f1-sensors-12-02874: Regions with available hydrodynamic models explored in this paper: (a) South East Tasmania; (b) Macquarie Harbour; and (c) Moreton Bay.
Mentions: The hydrodynamic model is based on Herzfeld’s general purpose model for estuaries to regional ocean domains [14]. The main model is for South-East Tasmania (43.1°S, 147.5°E), but models are also applied at Macquarie Harbour (42.3°S, 145.4°E), Moreton Bay (27.2°S, 153.2°E), and the Great Barrier Reef (20.1°S, 149.9°E). The three regions explored in this paper are shown in Figure 1. The model provides three-dimensional distributions of temperature, salinity, current velocity, density, passive tracers, mixing coefficients and sea level. From inputs such as wind, pressure, surface heat and tides, the model calculates momentum, continuity, and conservation of heat and salt. The model is based on the primitive equations and employs the hydrostatic and Boussinesq assumptions on currents [15]. The grid itself is non-uniform and curvilinear with grid spacing between approximately 200 m and 800 m. There is higher resolution upriver and in coastal regions, and relatively low resolution further out to sea.

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