minor review 2[1] final processings.pptx

DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING
SCHOOL OF COMPUTING
10214CS601 MINOR PROJECT -1
SUMMER SEMESTER(2023-2024)
REVIEW-II
“AN EFFICIENT REAL TIME CROP RECOMMENDATION SYSYTEM FOR SOIL PROTECTION”
1.C. NAGA SAI MANIKANTA (VTU20343)(21UEDS0014)
2.P. SAI RANGA (VTU20408)(21UECM0178)
3.K. LIKHITHA (VTU20361)(21UECS0272)
PRESENTED BY
SUPERVISED BY
Mrs.P.Arivubrakan,ME
Associate Professor
1
DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING / PROJECT TITLE AN EFFICIENT REAL
TIME CROP RECOMMENDATION SYSYTEM FOR SOIL PROTECTION
January 4, 2024

January 4, 2024 DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING / PROJECT TITLE 2
OVERVIEW
ABSTRACT
OBJECTIVE
INTRODUCTION
LITERATURE REVIEW (SOFT COPY OF PAPERS TO BE LINKED AS HYPERLINK)
DESIGN AND METHODOLOGIES
IMPLEMENTATION
TESTING
INPUT AND OUTPUT
INCLUDE DEMO VIDEO-1 (Till REVEW-1)
INCLUDE DEMO VIDEO-2(Complete Implementation of Project)
CONCLUSION
WEB REFERENCES LINK (TILL REVIEW DATE ALL LINKS TO BE INCLUDED DAY WISE)
PLAGIARISM REPORT OF PPT
REFERENCES

ABSTRACT
 INTRODUCTION:
The introduction of the project outlines the development of a web-based platform aimed at efficiently processing
and analyzing soil testing reports. It highlights the significance of user-friendly interfaces for inputting crucial data
elements such as soil test components, location specifics, and crop information.
 PURPOSE:
The purpose of this platform is to streamline the analysis of soil testing reports by utilizing user-friendly interfaces
to input data efficiently. The ultimate goal is to generate comprehensive reports that offer detailed insights into soil
health, nutrient content, and compaction. Additionally, the platform aims to provide tailored recommendations for soil
improvement, crop suitability, and corrective measures, catering to diverse users such as individuals, farmers,
consultants, and industries relying on precise soil information.
 METHOD:
The method involves creating an intuitive and accessible web platform that efficiently processes and analyzes soil
test data. User-friendly interfaces will enable seamless input of diverse soil components, location data, and crop
information. The platform will employ algorithms or models to generate comprehensive reports, offering detailed
insights into various aspects of soil health and nutrient content. Recommendations for soil improvement and crop
suitability will be derived from the analysis of this data.

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DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING /
“AN EFFICIENT REAL TIME CROP RECOMMENDATION SYSYTEM FOR
SOIL PROTECTION
4
 RESULT:
The result will be a user-friendly platform providing in-depth insights into soil health parameters, nutrient content,
and recommendations for enhancing soil quality. By prioritizing user convenience, data security, and educational
resources, the platform aims to empower users with knowledge about sustainable soil management practices. Its
accessibility to a wide range of users, including individuals, farmers, consultants, and industries reliant on accurate soil
information, is expected to enhance decision-making processes related to soil health and agricultural practices.
 CONCLUSION:
In conclusion, the development of this web-based platform seeks to revolutionize the accessibility and analysis of
soil testing reports. By providing comprehensive insights and recommendations, the platform aims to support informed
decision-making and promote sustainable soil management practices among its diverse user base. Prioritizing user
needs and ensuring data security are central tenets of this project, envisioning a future where accurate soil information
is readily available and instrumental for various operations.

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SOIL PROTECTION
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AIM OF THE PROJECT:
Efficient Soil Testing Report Processing: The primary aim of this project is to create a web-based platform that
efficiently processes and analyzes soil testing reports.
Comprehensive Insight Generation: The platform intends to generate comprehensive reports by utilizing user-friendly
interfaces to input crucial data elements including soil test components, location data, and crop information.
Insights and Recommendations: Using the input data, the system aims to provide detailed insights into various aspects
of soil health, nutrient content, compaction, and more. It further aims to offer tailored recommendations for soil
improvement, crop suitability, and corrective measures based on this analysis.
Empowerment Through Education: Prioritizing user convenience and educational resources, the platform seeks to
empower users with knowledge about sustainable soil management practices.
SCOPE OF THE PROJECT:
User-Friendly Interfaces: The project scope includes designing and implementing user-friendly interfaces to ensure ease of
input for soil test components, location data, and crop information.
Data Processing and Analysis: The platform's scope involves employing algorithms or models to process input data
efficiently and generate comprehensive reports with detailed insights into soil health metrics and nutrient content.
Recommendation System: Incorporating a recommendation system within the platform to suggest soil improvement
strategies, crop suitability measures, and corrective actions based on the analysis.
User Prioritization: Ensuring user convenience, data security, and educational resources are core aspects within the scope
to cater to a diverse user base comprising individuals, farmers, consultants, and various industries reliant on accurate soil
information for their operations.
OBJECTIVES

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SOIL PROTECTION
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TIMELINE OF THE PROJECT
Task Name OCT 2023 NOV 2023 DEC 2023 JAN 2024
Planning
Research
Design
Implementation
Follow up

INTRODUCTION
"Unlocking the secrets hidden beneath our feet: a web platform designed to decode soil's story, empowering a
sustainable future for agriculture. How can a click revolutionize the way we cultivate the Earth?"
Revolutionizing Soil Testing: Creating a cutting-edge web platform for efficient soil testing report analysis.
Empowering Users: Prioritizing user-friendly interfaces to input crucial data elements effortlessly.
Insightful Reports: Generating comprehensive reports offering deep insights into soil health and nutrients.
Customized Recommendations: Providing tailored recommendations for soil improvement and crop suitability.
Fostering Sustainability: Prioritizing user convenience, data security, and educational resources to promote
sustainable soil management.
Multi-Sector Impact: Aimed at benefiting individuals, farmers, consultants, and various industries reliant on
precise soil information for operations.

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SOIL PROTECTION
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LITERATURE REVIEW
Author’s Name Paper name and
publication details
Year of publication Main content of the
paper
Adegbeye M J, Reddy P R Sustainability 2020 Sustainable agriculture
options for production,
greenhouse gasses and
pollution alleviation, and
nutrient recycling in emerging
and transitional nations
Mutuku E A, Roobroeck D,
Vanlauwe B,
Agricultural Methods 2018 Maize production under
combined conservation
agriculture and integrated soil
fertility management in the
sub-humid and semi-arid
regions of Kenya

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SOIL PROTECTION
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KiryushinV I, Soil Management System 2011 The management of soil
fertility andproductivity of
agrocenoses in adaptive-
landscape farmingsystems,
Eurasian Soil

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SOIL PROTECTION
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DESIGN AND METHODOLOGIES
MODULE 1: User Interface Design
MODULE 2: Interface Algorithm and Recommendation Generation Algorithm

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SOIL PROTECTION
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MODULE 1:User Interface Desing
Step:1 Collection of data
pH Levels: Obtained from soil tests, indicating soil acidity or alkalinity, influencing nutrient availability.
Nutrient Content: Includes levels of essential elements (nitrogen, phosphorus, potassium) vital for plant growth and
health.
Soil Texture: Indicates the composition of soil particles (silt, sand, clay) affecting drainage and nutrient retention.
Compaction: Measures soil density, crucial for root penetration, water infiltration, and aeration.
Moisture Content: Reflects the amount of water present in the soil, impacting plant hydration and growth.

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SOIL PROTECTION
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Step 2: Processing the data
.

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DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING / AN EFFICIENT REAL TIME CROP
RECOMMENDATION SYSYTEM FOR SOIL PROTECTION
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Module 2- Algorithm's
Input Data Handling Algorithm:
Step 1: Collect input data: Soil test components, location specifics, and crop information through user-friendly interfaces.
Step 2: Validate and preprocess data: Verify input accuracy, handle missing values, and format data for analysis.
Data Analysis and Insights Algorithm:
Step 3: Analyze soil components: Utilize algorithms/models to process the input data, analyzing soil health, nutrient
content, compaction, etc.
Step 4: Generate comprehensive reports: Present insights in easily understandable formats, including visualizations and
textual explanations.
Recommendation Generation Algorithm:
Step 5: Derive recommendations: Based on the analysis, create algorithms that suggest soil improvement strategies, crop
suitability measures, and corrective actions.
Step 6: Personalization: Tailor recommendations considering specific user needs or preferences, if applicable.
User Interface Algorithm:
Step 7: Design intuitive interfaces: Develop algorithms for user-friendly input systems, ensuring ease of data entry and
navigation.

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Step 8: Accessibility and customization: Implement algorithms allowing users to access and customize
data views based on their preferences.
Security and Privacy Algorithm:
Step 9: Ensure data security: Implement encryption algorithms, access controls, and secure user
authentication to protect sensitive soil-related data.
Educational Resource Algorithm:
Step 10: Integration of educational resources: Algorithms to embed educational materials within the
platform, providing guidance on sustainable soil management practices.
Feedback and Iterative Improvement Algorithm:
Step 11: Feedback mechanisms: Algorithms to collect user feedback within the platform, facilitating
continuous improvements based on user experiences.

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Step 3: Interface Algorithm and Recommendation Generation Algorithm

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Step 4: The output

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IMPLEMENTATION
Architecture Diagram
Data –Flow Diagram
Use Case Diagram
Class Diagram
Activity Diagram
Sequence Diagram
Collaboration Diagram(If applicable)
E-R Diagram
It’s a sample only and may vary according to the project

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Architecture Diagram
PH-level
Nutrient-
Content(NPK)
Moisture Content
Crop
Web Application
User Input
Crop Type
Suitable
Farming
Method
Quantity of Pesticides
or Fertilizers that we
have to use

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Data –Flow Diagram
Dataset Collection
Data Preprocessing
Web Application
User
Input Data
Crop Type , Suitable
Farming Method ,
Pesticide/Fertilizer Quantity
• It gets the input data from the user.
• The collected data is preprocessed and
stored in the data base.
• Base on the Processed data it gives the
output , that suggests the Suitable Farming
Method, Crop Type, etc.….

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Use Case Diagram
Get Dataset
Crop Type, Farming
Methods , Pesticides
Usage Quantity
Web Application
Preprocessor
Dataset
User Server

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USER
INTERFACE
COLLECT DATA
DISPLAY DATA
DATA HANDLER
VALLIDATA DATA
PROCESS DATA
REPORT
GENERATOR
GENERATE
REPORT
FORMAT REPORT
DATABASE
SAVE DATA
QUERY DATA
Class Diagram

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Activity Diagram

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Sequence Diagram

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E-R Diagram

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Collaboration Diagram

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UNIT TESTING
INTEGRATION TESTING
FUNCTIONAL TESTING
TESTING

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UNIT TESTING
Unit testing is a crucial aspect of software development, ensuring that individual components of your system work
as expected. In the context of a crop recommendation system, here are some guidelines and examples for unit
testing:
 Test Environment Setup:Use testing libraries such as JUnit, pytest, or NUnit depending on your programming
language.
 Isolate Components:Test each component or module of your crop recommendation system in isolation to
ensure that they function correctly on their own
 Error Handling:Ensure that the system handles errors gracefully. Test how the system responds to unexpected
situations and whether appropriate error messages or logging are in place.
 Performance Testing:Depending on the scale of your system, consider testing its performance. Ensure that the
crop recommendation system responds within acceptable time frames.
INTEGRATION TESTING
Integration is a critical aspect of a crop recommendation system, especially when it involves combining
various components, services, or external systems. Here are key points to consider when designing the
integration system for a crop recommendation system:
Data Sources Integration:Integrate with diverse data sources such as weather APIs, soil databases, and
historical crop data.
Ensure the system can handle different data formats and standards.
Scalability:Design the integration system to scale horizontally and vertically to accommodate
increasing data volume and user demand.

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FUNCTIONAL TESTING
Functional testing for a crop recommendation system involves evaluating the system's functionalities to ensure that
it performs as expected and meets the specified requirements. Here are key aspects and strategies for conducting
functional testing for a crop recommendation system
User Interface (UI) Testing:
Navigation: Ensure that users can navigate through the UI easily.
Input Fields: Verify the functionality of input fields for entering data like temperature, humidity, and rainfall.
Buttons and Forms: Test the functionality of buttons and forms used for submitting data and triggering
recommendations.
Validation Messages: Check if appropriate validation messages are displayed for invalid inputs.
 User Authentication and Authorization:
User Login: Ensure that the user authentication process works correctly.
User Roles: Verify that users have appropriate access levels and permissions based on their roles.
Documentation Verification:
User Manuals: Confirm that user manuals accurately reflect the current system functionalities.
API Documentation: Verify that documentation for APIs is up-to-date and aligns with the actual implementation.

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INPUT AND OUTPUT
Eg, DATASET IMAGE
It’s a sample only and may vary according to the project

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SOURCE CODE

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OUTPUT

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CONCLUSION
Problem Statement:The “AN EFFICIENT REAL TIME CROP RECOMMENDATION SYSYTEM FOR
SOIL PROTECTION " website project aims to the current agricultural landscape lacks an efficient and
technologically advanced crop recommendation system tailored to the diverse needs of farmers. Many
farmers struggle to make informed decisions about crop selection, leading to reduced yields, increased
resource wastage, and potential environmental degradation. Existing systems often fall short in providing
accurate recommendations based on real-time data, hindering sustainable farming practices.
Conclusion:
The website provides Crop Recommendation System represent a significant stride towards revolutionizing
modern agriculture by integrating advanced technologies and data-driven insights.
Addressing the challenges associated with traditional farming practices, this system aims to provide farmers
with valuable tools for making informed decisions about crop selection, optimizing yields, and promoting
sustainable agricultural practices.
It gives the perfect crop recommendation for the given soil .By this way farmers are getting good yield and
get profits.
The user-friendly interfaces and accessibility features incorporated into the system aim to bridge the gap
between technology and farmers, making the recommendations accessible to a broader audience

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Plagiarism Report of PPT
Plagiarism should be less than 10%.
Eg,

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Web references/video links
https://www.irjmets.com/uploadedfiles/paper//issue_5_may_2022/24775/final/fin_irjmets1654092174.pdf
https://github.com/topics/crop-recommendation
https://youtu.be/_R9Q_iuyvdc?si=VFASa9v-sNfdAiiA
https://youtu.be/K--brt_ADxA?si=99_RvYmBhKToi_NB

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REFERENCES
 Smith, J. A., Johnson, R. B., ”Soil Protection and Conservation Techniques,” Transactions on Environmental Science,
vol. 10, no. 3, pp. 123-136,March 2018
 Pretty, J., ”Impact of Cover Crops on Soil Erosion Control,” Transactions on Environmental Science, vol. 12, no. 1, pp.
45-58, January 2020
 Epstein, E., ”Evaluation of Sustainable Soil Management Practices,” in Proceedings of the International Conference
on Sustainable Agriculture, pp.210-215, September 2016.
 Lal, R., ”Effectiveness of Vegetative Barriers in Soil Conservation,” Journal of Soil Science, vol. 30, no. 2, pp. 175-188,
February 2021.
 McHugh, O. V., ”Assessing the Role of Microorganisms in Soil Health andProtection,” in Proceedings of the
International Symposium on Environmental Microbiology, pp. 340-345, June 2018.
Nair, P. K. R., ”Technological Advances in Precision Agriculture for SoilConservation,” Transactions on Sustainable
Agriculture, vol. 8, no. 4, pp.289-302, April 2017.
Richardson, C. J., Vepraskas, M. J., Wetland Soils: Genesis, Hydrology,Landscapes, and Classification,” in Proceedings
of the IEEE International Conference on Sustainable Agriculture, pp. 210-215, September 2015.
Sistani, K. R., Jn-Baptiste, M., ”Nutrient Management in Soils,” IEEE Transactions on Environmental Science, vol. 10,
no. 3, pp. 123-136, March 2021

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