DocumentCode :
1568475
Title :
Using artificial intelligence and a graphical network database to improve service quality in Telecom Australia´s customer access network
Author :
Mcintyre, John R.
Author_Institution :
Telecom Australia, Melbourne, Vic., Australia
fYear :
1992
Firstpage :
1549
Abstract :
The systems used for Telecom Australia´s customer access network (CAN) maintenance largely determine the ability to respond to customer service problems. With increasing use of electronic equipment and optical fiber transmission in the CAN, an integrated maintenance approach has become essential. Access to real-time network status and network data is a prerequisite for an integrated system. Telecom Australia is currently capturing its network plans in a network database. CAN service quality can be enhanced by using these data with artificial intelligence systems at both the fault analysis level and at the customer interface. Coupled to a graphical display environment, these systems can assist in anticipation and clearance of CAN service failures before they affect the customer´s services. CAN faults, the network database, CAN systems, the expert system, the graphical interface, and customer support are discussed
Keywords :
expert systems; graphical user interfaces; maintenance engineering; optical links; subscriber loops; telecommunication network management; telecommunications computing; CAN; CANES expert system; Telecom Australia; artificial intelligence; customer access network; customer support; graphical interface; graphical network database; integrated maintenance approach; optical fiber transmission; service quality; Artificial intelligence; Australia; Customer service; Databases; Displays; Electronic equipment; Expert systems; Optical fibers; Real time systems; Telecommunications;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, 1992. ICC '92, Conference record, SUPERCOMM/ICC '92, Discovering a New World of Communications., IEEE International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-0599-X
Type :
conf
DOI :
10.1109/ICC.1992.267982
Filename :
267982
Link To Document :
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