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Major project 2 presentation
1.
2. TITLE OF PROPOSED SOFTWARE/SYSTEM
“PulsExpert”
Diagnostic Expert System for Pulses Crop
“Pulses for Nutritional Security & Agricultural Diversity”
3. WHAT IS AN EXPERT SYSTEM ?
“Special computer software capable of carrying out analysis with reasoning in narrowly
defined domain at proficiency levels of an expert.” (Mckinion & Lemmon, 1985)
“Computer program which apply expert knowledge to solve complex problems,
mimicking the reasoning skill of a human expert.”(Linko, 1998)
4. Develop a knowledge-based system for pulse agricultural
activities.
Develop a user-friendly diagnostic system and suggest appropriate
treatments.
Propose proper irrigation and fertilization schedule.
Propose most economic pulse crop based
on cost benefit analysis.
OBJECTIVES
5. Unavailability of domain experts at the nick of time
Expert’s knowledge is a scarce & expensive resource
Static information
Integration of knowledge and experiences of different area experts
Representation of all types of integrated knowledge/information sources such as
images and/or textual
The undocumented experience and knowledge of farmers and extension workers
Difficulties in increasing yield in pulse crops
6. Utility of expert systems in diagnosing pulse crop
diseases
Timely diagnosis and control of crop diseases leading cost effectiveness
New and more complex models to be used for proper identification of
diseases
More accurate disease identification using updated knowledge
Environmentally and socially balanced control measures
Assists farmers and extension workers as a Decision Support System
7. Expert System Development Process
Knowledge acquisition
Knowledge acquisition involves the acquisition of knowledge from sources (I.e.
human experts, books, documents, sensors, or computer files) and its transfer to
the knowledge base and sometimes to the inference engine
Knowledge may be specific to the problem domain or to the problem-solving
procedures, it may be general knowledge, or it may be metaknowledge
Knowledge representation
Organized knowledge
Knowledge validation and verification
Inferences
Software designed to pass statistical sample data to generalizations
User interface
10. Knowledge Acquisition Methods
Manual
Interviews
Experts’ Reports and Questionnaires
Observation
Interactive computer-based
Computer program that elicits knowledge from experts
Automatic knowledge base with minimal help from knowledge
engineer
11. 11
Manual Method of Knowledge Acquisition
Knowledge
base
Documented
knowledge
Experts
Coding
Knowledge
engineer
13. Knowledge Acquisition for
Pulse Crop Disease Identification
Develop a knowledge base about the plant damage symptoms due to
major diseases in Pulses
Develop an interactive knowledge acquisition system having facilities
of adding, viewing, modifying and deleting both types of knowledge
(i. e. textual and pictorial)
Assist the domain expert(s) and extension workers to feed knowledge
in the knowledge base in a structured form maintaining consistency of
the encoded knowledge
15. Knowledge types identification
Total five parameters were identified for describing all the plant damage symptoms which may
occur in the crop/plant at different stages In pulse crops disease diagnosis domain
crop parameters (crop name, disease type, disease name, crop location,
crop stage affected, planting space, crop sowing time, disease status in area,
and disease status in the previous crop)
field parameters (temperature, humidity and soil moisture)
symptom parameters (colours, shapes and sizes changes in leaves and other
plant parts)
Visible pictorial parameters (spot/holes in leaves, pods, flowers, stems, seeds
etc.)
Treatment parameters (resistant varieties, cultural practices & chemical
controls including fungicide name, dose & time of application etc.)
16. Knowledge Structure
Relational database structure is used to store the knowledge in the
form of tables and relations
The database has eight different tables viz., Login, Pulsemaster, Disease,
Pulse_question, Pulse_answer, Fig, Control_measures and Diagnosis
“Categories of knowledge”
Textual knowledge
Knowledge is actually a set of questions along with multiple
answers
Question is based on the identified parameters
Each question having a certainty criteria (Confirmatory, 50-75%
certain, 25-50% certain, 0-25% certain) for representing the
importance of question in identifying the particular disease
Pictorial knowledge
Knowledge contains pictures as well as full details of the required
symptoms
Options (“Yes”, “No” or “Unknown”) are used for answering the particular
question
18. Knowledge Representation
Knowledge can be simply expressed in the following rule format:
P1D1 (Q1(a11 or a12) and Q2(a21) and Q4(a42 or a43 or a44) and Q6(a62) and Q7(a72 or a73) and Q9(a91) )
P1D2 (Q1(a13) and Q2(a22 or a23) and Q3(a31) and Q5(a53 or a54) and Q6(a61 or a63) and Q8(a81 or a83) and
Q9(a91or a92) )
P1D3 (Q1(a14) and Q2(a22 or a24) and Q3(a32) and Q7(a71) and Q8(a82) and Q9(a91 or a93) )
19. Knowledge Acquisition Process
A domain expert enters the knowledge disease-by-disease for a pulse
crop in the form of questions and their expected answers and also enters
a certainty criteria for or a particular disease of a selected pulse crop “
how important is a question in diagnosing a particular disease?”
While entering the knowledge for other diseases of same crop, he/she
may select either form the entered set of questions through question
bank or enter new question
After entering the knowledge from an expert to build a structured
knowledge base, all the possible answers of a question are stored
together by the system
20. Knowledge Acquisition Process (Contd)
Knowledge base will have the different sets of questions for the
identification of each type of diseases in pulses
Some of the questions may be common but their possible answers may
or may not be
An option “Unknown” is added automatically by the system to give the
user facility in case he/she does not know the answer of particular
question
25. CONCLUSIONS
A task specific knowledge acquisition tool has been developed for agriculture domain to
solve the disease identification and control problems mainly for pulses. However, it may be
used for other crops also
The system provides user-friendly interface to domain expert for entering the knowledge
System enables the experts to input, view, modify and delete the information contained in the
database
It captures the knowledge of an expert through interactive sessions, distills the knowledge and
automatically generates tables used in decision making
Direct involvement of the domain expert increases the accuracy of the resulting knowledge
base eliminating the errors of communication and understanding
The system maintains the consistency and avoids redundancy by recognizing/showing similar
types of knowledge/information
Knowledge base of the system contains knowledge about the disease identification symptoms
& remedies of 19 diseases of major pulse crops (Chickpea, Pigeonpea, Mungbean & Urdbean)
26. FUTURE WORK
Extension of the system for other pulse agriculture areas (i.e. insect-pests
management, fertilizer management, variety selection, irrigation
management & cost benefit analysis)
Building a complete Expert System for identification and control of pulse
crops diseases having a knowledge base created using the proposed
acquisition tool
Facility to incorporate knowledge from multiple experts and refine it based
on feedback both from the expert and from potential users (i.e. farmers and
extension workers)
Finally, extension of the system for other crops (I.e. wheat, rice, maize etc.)