EXPERT SYSTEM FOR HUMAN NUTRITION ANALYSIS. A RESEARCH PROJECT MATERIAL ON COMPUTER SCIENCE EDUCATION
CHAPTER ONE
1.0 Introduction
Expert system for human nutrition analysis is an expert system for diagnosing, controlling, and monitoring human nutrition. The system assesses the physical characteristics of the user to determine their nutritional status and makes recommendations for reaching nutritional requirements and a balanced diet, as a consequence generating a knowledge database with the nutritional status and dietary habits for the user. The system generates challenges, alerts, and constantly motivates the user to use the application and improve their nutritional habits. The expert system is implemented using the C++ Expert System Shell, libraries (Laboratories 2012) and the C++ programming language running as a Web Service on a Window Web Server. The system calculates the BMI, Body Mass Index, as in Eq. 1 (OMS 2012), the ideal weight and physical contexture, frame size (Rivas 1991) and uses dietary information from (Bermudez 2012). This is our base for nutritional diagnosis on the proposed system. This system will be developed for all users as a tool to improve their eating habits and nutritional wellbeing. The goal is to incorporate the use of this application into their daily lives and help them acquire and maintain healthier eating habits.
1.1 Background of Study
An expert system or electronic diagnose system is a software hardware system that attempts to reproduce the performance of one or more human experts, most commonly in a specific problem domain, and is a traditional application and/or subfield of artificial intelligence.
A wide variety of methods can be used to simulate the performance of the expert however common to most or all are
1) The creation of a so-called “knowledgebase” which uses some knowledge representation formalism to capture the subject matter experts (SME) knowledge and
2) A process of gathering that knowledge from the SME and codifying it according to the formalism, which is called knowledge engineering. Expert systems may or may not have learning components but a third common element is that once the system is developed it is proven by being placed in the same real world problem solving situation as the human SME, typically as an aid to human workers or a supplement to some information system.
As a premiere application of computing and artificial intelligence, the topic of expert systems has many points of contact with general systems theory, operations research, business process reengineering and various topics in applied mathematics and management science.
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