Know and understand characteristics, uses and purpose of expert systems including mineral prospecting, car engine fault diagnosis, medical diagnosis, chess games, financial planning, route scheduling for delivery vehicles, plant and animal identifica

Published by Patrick Mutisya · 14 days ago

ICT 0417 – 6 ICT Applications: Expert Systems

6 ICT Applications – Expert Systems

Learning Objective

Know and understand the characteristics, uses and purpose of expert systems, with particular reference to the following applications:

  • Mineral prospecting

  • Car engine fault diagnosis

  • Medical diagnosis

  • Chess games

  • Financial planning

  • Route scheduling for delivery vehicles

  • Plant and animal identification

What is an Expert System?

An expert system is a computer program that mimics the decision‑making ability of a human expert. It consists of three main components:

  1. Knowledge base – facts and rules about a specific domain.

  2. Inference engine – applies logical reasoning to the knowledge base to draw conclusions.

  3. User interface – allows users to input data and receive advice or solutions.

Key Characteristics

  • Domain‑specific knowledge captured from experts.

  • Rule‑based reasoning (if‑then statements) or case‑based reasoning.

  • Ability to explain its reasoning (transparent decision making).

  • Consistent performance – no fatigue or emotional bias.

  • Can be updated as new knowledge becomes available.

Common Purposes

  • Assist professionals in complex decision making.

  • Provide expert advice where human experts are scarce.

  • Increase speed and accuracy of problem solving.

  • Reduce costs associated with trial‑and‑error approaches.

Applications of Expert Systems

ApplicationDomainHow the Expert System WorksBenefits
Mineral ProspectingGeology / MiningAnalyzes geological data (rock types, seismic readings, chemical assays) using rule‑based models to predict locations with high mineral potential.Reduces costly exploratory drilling; focuses resources on most promising sites.
Car Engine Fault DiagnosisAutomotive EngineeringReceives sensor readings and driver symptoms, matches them against a knowledge base of fault patterns, and suggests probable causes and repairs.Speeds up repair time; assists less‑experienced technicians.
Medical DiagnosisHealthcareCollects patient symptoms, test results and medical history, then applies diagnostic rules to propose possible conditions and recommended investigations.Supports clinicians in rare or complex cases; improves diagnostic accuracy.
Chess GamesArtificial Intelligence / GamingUses a large database of opening moves, end‑game tables, and evaluation functions to select optimal moves based on board position.Provides strong opponent for learners; demonstrates strategic thinking.
Financial PlanningFinance / Personal AdvisoryInputs client goals, income, expenses and risk tolerance; applies financial rules to generate investment, savings and retirement plans.Offers personalized advice; helps users make informed financial decisions.
Route Scheduling for Delivery \cdot ehiclesLogistics / TransportProcesses delivery addresses, vehicle capacities and traffic data; uses optimization algorithms to produce efficient routes.Reduces fuel costs; improves delivery timeliness.
Plant and Animal IdentificationBiology / EcologyAsks the user a series of characteristic questions (leaf shape, habitat, etc.) and matches answers to a database of species.Assists students, researchers and the public in accurate species identification.

Example: Reasoning Process (Medical Diagnosis)

The inference engine typically follows a forward‑chaining approach:

  1. Collect patient data (symptoms, test results).

  2. Match each datum against the rule set (e.g., If fever ≥ 38°C and cough = true then consider respiratory infection).

  3. Accumulate supporting evidence for possible conditions.

  4. Rank diagnoses by confidence level and present the most likely options.

Advantages and Limitations

  • Advantages: Consistency, speed, availability 24/7, ability to handle large knowledge bases.

  • Limitations: Dependence on quality of knowledge base, difficulty handling ambiguous or incomplete data, limited creativity compared with human experts.

Suggested Diagram

Suggested diagram: Block diagram of an expert system showing the Knowledge Base, Inference Engine, User Interface and Data Flow.

Review Questions

  1. What are the three main components of an expert system and what does each do?

  2. Explain how an expert system can improve mineral prospecting.

  3. Identify two benefits and two drawbacks of using expert systems in medical diagnosis.

  4. Describe how route scheduling expert systems use optimisation techniques.

  5. Give an example of how a plant identification expert system interacts with the user.