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Site Assessment of Multiple-Sensor Approaches for Buried Utility Detection
Author(s) -
Alexander Royal,
Phil Atkins,
M.J. Brennan,
David N. Chapman,
Huanhuan Chen,
Anthony G. Cohn,
Kae Y. Foo,
K.F. Goddard,
Russell Hayes,
Tong Hao,
P. L. Lewin,
Nicole Metje,
Jen M. Muggleton,
A. W. Naji,
Giovanni Orlando,
S.R. Pennock,
Miles Redfern,
Adrian J. Saul,
S.G. Swingler,
Wang Ping,
C. D. F. Rogers
Publication year - 2011
Publication title -
international journal of geophysics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.253
H-Index - 19
eISSN - 1687-8868
pISSN - 1687-885X
DOI - 10.1155/2011/496123
Subject(s) - carriageway , trenchless technology , computer science , sensor fusion , position (finance) , wireless sensor network , data mining , systems engineering , engineering , artificial intelligence , transport engineering , pipeline transport , computer network , finance , environmental engineering , economics
The successful operation of buried infrastructure within urban environments is fundamental to the conservation of modern living standards. Open-cut methods are predominantly used, in preference to trenchless technology, to effect a repair, replace or install a new section of the network. This is, in part, due to the inability to determine the position of all utilities below the carriageway, making open-cut methods desirable in terms of dealing with uncertainty since the buried infrastructure is progressively exposed during excavation. However, open-cut methods damage the carriageway and disrupt society's functions. This paper describes the progress of a research project that aims to develop a multi-sensor geophysical platform that can improve the probability of complete detection of the infrastructure buried beneath the carriageway. The multi-sensor platform is being developed in conjunction with a knowledge-based system that aims to provide information on how the properties of the ground might affect the sensing technologies being deployed. The fusion of data sources (sensor data and utilities record data) is also being researched to maximize the probability of location. This paper describes the outcome of the initial phase of testing along with the development of the knowledge-based system and the fusing of data to produce utility maps.

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