DocumentCode
497703
Title
Process refinement using Biosensor location problem
Author
Sambhoos, Kedar ; Temel, Melih ; Pan, Feng ; Sudit, Moises
Author_Institution
CUBRC, Buffalo, NY, USA
fYear
2009
fDate
6-9 July 2009
Firstpage
256
Lastpage
263
Abstract
Complex biological sensor performance drives the decisions of which sensors to include into the tiered testing approach of a combined sensor system to achieve high confidence results. The goal is to decrease the ldquotime to confirmationrdquo while increasing confidence in the test results. This research develops a mathematical formulation for solving the Biosensor location problem derived with an Ontological approach toward Sensor Management. Initially an Integer Programming formulation is developed in order to obtain an optimal sensor allocation for a given area utilizing the Ontology information of the biosensors. However, due to the combinatorial nature of the problem, the storage and solution time requirement to solve the IP Model grows exponentially with the size of the problem. We have developed two heuristic models to obtain good solutions to the sensor location problem. Then we have statistically analyzed the various parameters on sensor locating cost and heuristic running time.
Keywords
biosensors; computerised instrumentation; integer programming; ontologies (artificial intelligence); sensor fusion; biosensor location problem; integer programming; ontological approach; optimal sensor allocation; process refinement; sensor management; Biosensors; Costs; Linear programming; Ontologies; Refining; Sensor fusion; Sensor systems; Statistical analysis; System testing; Systems engineering and theory; Biosensor Location Problem; Design of Experiment (DOE); Heuristic; Ontology; Process Refinement; Statistical Analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Fusion, 2009. FUSION '09. 12th International Conference on
Conference_Location
Seattle, WA
Print_ISBN
978-0-9824-4380-4
Type
conf
Filename
5203797
Link To Document