Respiratory protection expert system

Pao Yue-kong Library Electronic Theses Database

Respiratory protection expert system


Author: Yung, Kin-wai
Title: Respiratory protection expert system
Degree: M.Sc.
Year: 1996
Subject: Expert systems (Computer science)
Respiratory organs -- Diseases -- Prevention
Breathing apparatus -- Testing -- Data processing
Hong Kong Polytechnic University -- Dissertations
Department: Multi-disciplinary Studies
Pages: viii, 290 leaves : ill. ; 30 cm
Language: English
InnoPac Record:
Abstract: Because of the increase in awareness of the importance of respiratory protection, there is a great need of respiratory protection equipment. Choosing respiratory protection equipment is a rather complicated process, many factors, such as concentration of airborne contaminants, form of contaminant, chemical nature of contaminant, and so on, are need to be considered. To avoid misusing respiratory protection equipment, qualified experts, such as industrial hygienist, are recommended to be advised. For those small scale factories, they may not be able to afford qualified experts for such safety issue. On the other hand, even with experts, workplaces' evaluation may take a very long time. In addition, number of workplaces is much greater than qualified experts. Hence, there is a need for another tools to help people choosing suitable respiratory protection equipment. Expert system would be a good tool to help people choosing the right respiratory protection equipment. There are some expert systems helping user to choose respiratory protection equipment in the market. However, all of them are only running on traditional rule-based algorithm. To get recommendation from the system, unless user can input all the required information by the system, no recommendation can be obtained from the system. However, in real life, most users usually do not know all the required information. Hence, these expert systems may not be helpful to users. To handle the problem, an expert system, besides traditional rule-based algorithm, with some artificial intelligent elements is developed. The system provides two functions to user: respirator recommendation and organic vapour filter media service life estimation. To get recommendation from the system, users are required to input oxygen content, identity (name or CAS number) of the airborne contaminant, country standard that user is following, and concentration of the contaminant. Base on the input, if the input substance is in the system database, by rule-based algorithm, recommendation will be given out. However, if user does not know the identity of airborne contaminant, the system will let user choose one of the listed occupations that is closest to user's job nature, by heuristic matching, recommendation still can be given out. On the other hand, if the contaminant identity cannot be found in the system database, it will be treated as a new organic chemical. The system will estimate its service life with organic vapour filter media with the same algorithm as service life estimation function. User is required to input the chemical natures and working environment parameters into the system. During the input phase, user can input incomplete information. With fuzzy logic, the system can help user estimate contaminant concentration, workplace temperature, and workplace relative humidity. With rule-based reasoning, the system can help user guess the saturated vapour pressure of contaminant from information about structure of the substance. With the help of all these AI elements, if complete data is still not available, generic algorithm and case-based reasoning will be employed. By comparing with past cases in database, similar case in the database will be modified as recommendation for the new case.

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