M.Sc Agriculture Extension Education, ICTs for Agricultural Extension and Advisory Service Course.

1.  Expert System
- S.SRISABARI
 Management Information System
Lecture - 18

2.  Expert System

3. Meaning
 Expert System designed to provide,
 Expert-level knowledge
 Advice and
 Recommendation
to decision-maker in solving complex problem.
 Expert System also called as,
 Knowledge Based System (KBS).

4. TNAU Expert
Systems
Paddy
Expert
System
Coconut
Expert
System
Banana
Expert
System
Sugarcane
Expert
System
Ragi
Expert
System

8. Definition
 A computer program designed to,
 Model the problem solving ability of a human expert.
 A system that uses human knowledge captured in,
a computer to solve problem.
⁕ By Durkin,

9. Concept
 Replicate the problem-solving capabilities of,
 Human experts.
 Capturing their knowledge and expertise,
 Organizations can benefit consistent
 Even in the absence of human experts.

10. Components of Expert System
• Knowledge Base
• User Interface
• Inference Engine

11. i. Knowledge Base
 It is the database,
where expert knowledge is stored.
 Knowledge engineers gather knowledge
from the experts and
keep it in the knowledge base.

12. ii. User Interface
 It is the method,
which the expert system
interacts with a user.

13. iii. Inference Engine
 Inference Engine is,
mind of the expert system.
 It has all the predefined rules,
to use the information
from the knowledge base.
 It takes user input from,
user interface and
it can find a solution for the problem.

14. Components of Expert System

15. Crop Doctor
 Crop doctor is an important component in the expert system.
 Act as Artificial Intelligence.
 Crop doctor is image based program.
 Use the crop doctor for,
diagnosing the field related problem
and
get the solution for the problem.

16. Crop Doctor
 Diagnosis of pests / diseases / nematode / nutrition disorders
are possible in the crop doctor.
 Available in Tamil, English, Malayalam, Kannada and
all the Regional languages of India.
 Information with images of damage and
symptoms are available in the crop doctor.
 Management practices are available in
the control measure components.
Plantix

17.  Management Information System

18. Meaning
 Management Information System is,
Computer Based System
that makes information available to user.
 Used for collecting, processing, storing and
disseminating data to carry out a farm's operations.
 MIS is consisting of,
people, machines, procedures,
databases and data models.

19. Objectives of MIS
 Capturing and processing data
 Storage of information
 Retrieval of information and
 Disseminating the information

20. Types of MIS
i. Sales and Marketing
 Execute and track the company’s marketing functions and sales.
ii. Human Resource Management
 Keeps the track of employees and their recruitment.
iii. Accounting and Finance
 Track the investments and assets of a company.

21. iv. Decision support system
 It helps the manager to make a decision when a situation arises.
v. Transaction process system
 The activities are orders, payment deposits or reservation.
vi. School information system
 Enable a school to run day to day activities of a school (attendance)
in an efficient way.
vii.Local database
 Provide in-depth information about the communities.

22. MIS Approaches
Top Down approach
Bottom up approach
Integrative approach
Traditional approach
Systematic approach

23. a) Top Down approach
 Top management takes the lead in,
formulating objectives, policies and plans.
b) Bottom up approach
 Individual applications are planned separately.
 Files of various functional applications are integrated.
c) Integrative approach
 This approach permits managers at all levels,
to influence the design of MIS.

24. d) Traditional approach
 Separate information system,
for each business function.
e) Systematic approach
 Identify requirements,
 Locate, evaluate and secure software development,
 Locate, evaluate and secure hardware,
 Implement the systems.

25. MIS Development Protocol
Knowledge Acquisition
Knowledge Representation
Inference Engine Design
Testing and Validation
Integration
Maintenance

26. i. Knowledge Acquisition
 The first step in developing an expert system is,
to acquire the necessary domain-specific knowledge
(through interviews, document analysis).

27. ii. Knowledge Representation
 The acquired knowledge needs to be,
organized and represented in a suitable format
that the expert system can understand.

28. iii. Inference Engine Design
 It is the core of the expert system and performs,
reasoning and decision making processes.
 It applies the rules,
searches for relevant cases or
trains the neural network to provide,
accurate recommendations.

29. iv. Testing and Validation
 The expert system should undergoes testing,
to ensure its accuracy, reliability and performance.
 The system's outputs are compared against expected results.
 Validation involves verifying,
the system's effectiveness.

30. v. Integration
 Once the expert system has been tested and validated,
it needs to be integrated into the overall
MIS infrastructure.
 This may involve integrating with
other systems, databases or
user interfaces.

31. vi. Maintenance
 Expert systems require ongoing maintenance,
to keep the knowledge base
up to date, address system issues and
incorporate new knowledge or rules as
the domain evolves.