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“A Research to Construct the
Interactive Platform for Integrated
Information of Agricultural Products”
Contents
 Introduction
 Problem statement
 Literature Survey
 Existing System
 Objectives
 Proposed Model
 Algorithm
 Mathematical Model
• UML Diagrams
• Advantage
• Limitation
• Future Scope
• Conclusion
• Reference
• Publication
Introduction
 The blockchain technology enables the traceability of information in
the food supply chain and thus helps improve food safety.
 It provides a secure way of storing and managing data, which facilitates the development and
use of data-driven innovations for smart farming and smart index-based agriculture insurance.
 The problem of yield prediction is a major problem that can be solved based on past data/dataset.
 During the cultivation of crops, the amount of fertilizers, insecticides, fungicides and its related
information are analyzed using E-Commerce platform and Informatics.
 It will be beneficial if farmers could use the technique to predict the future crop productivity and
consequently adopt alternative adaptive measures to maximize yield by using weather
forecasting data.
Problem Statement
 Block chain as well as informatics is an emerging field of research in Information Technology as
well as in agriculture. Agrarian sector in India is facing rigorous problem to maximize the crop
productivity. The present study focuses on the applications of data mining techniques in yield
prediction in the face of climatic change to help the farmer in taking decision for farming and
achieving the expected economic return. The problem of yield prediction and as per
productivity market is a major problem that can be solved based on available data.
 Hence to address these problems we proposed a system “A Research to Construct the
Interactive Platform for Integrated Information of Agricultural Products”, so in that we proposed
both problems solution that is first E-Commerce of agriculture products and agriculture crop
disease fertilizers & pesticides and second is Informatics about weather information, crop
information, etc.
Literature Review
Sr.
No.
Paper name Author Publication Description
01 A Research to
Construct the
Interactive Platform for
Integrated Information
of Agricultural
Products in China
Xinjiang
Yuan Li, and
Zhigang Li
IFIP International
Federation for
Information Processing
2011
Proposing an interactive platform for
integrated information of agricultural
products which combines farm
production, supply and marketing of
Xinjiang
agricultural products.
02 Artificial Intelligence
Based
Recommendation
System for Farmers
G.
Ramyalakshmi, A.
Deeksha, M.
Sumana
International Journal of
Computer Trends and
Technology ( IJCTT ) 2019
In this paper, the farmer / beginner will
predict the crop cultivation based on
their weather, monsoon and soil type
along with their pH level.
03 Affordable Smart
Farming Using IoT and
Machine Learning
Reuben
Varghese,
Smarita Sharma
Proceedings of the
Second International
Conference on Intelligent
Computing and Control
Systems (ICICCS 2018)
In this paper, we develop an affordable
system which when deployed will give
an insight into the real time condition
of the crop. The system leverages IoT
and Machine learning to produce an
affordable smart farming module.
Literature Review (Cont…)
Sr.
No
Paper name Author Publication Description
04 An Overview of Internet
of Things (IoT) and Data
Analytics in Agriculture:
Benefits and Challenges
Olakunle Elijah,
Tharek Abdul
Rahman, Igbafe
Orikumhi, Chee
Yen Leow, and
MHD Nour
Hindia
IEEE Internet of
Things Journal 2018
In this paper, several benefits and
challenges of IoT have been identified. We
present the IoT ecosystem and how the
combination of IoT and
DA is enabling smart agriculture.
05 Internet of Things
Monitoring System of
Modern Eco-agriculture
Based on
Cloud Computing.
Shubo Liu, Liqing
Guo, Heather
Webb, Xiao Yao,
Xiao Chang
IEEE Access 2019 In this paper, Based on the new generation
of information technology (IT), an
integrated framework system platform
incorporating Internet of Things (IoT), cloud
computing, data mining and other
technologies is investigated and a new
proposal for its application in the field of
modern agriculture is offered.
06 Research on the Quality
Supervision System of
Agricultural Product
Based on Big Data.
Yitang Zeng Journal of Physics:
Conference Series
(ICCSCT 2020)
This paper systematically analyzes the role
of big data in the quality supervision system
of agricultural products and its innovative
driving mechanism for operation mode
Existing System
 India is one among the oldest countries which is still practicing agriculture.
But in recent times the trends in agriculture has drastically evolved due to
globalization. Various factors have affected the health of agriculture in India.
Many new technologies have been evolved to regain the health. One such
technique is precision agriculture.
 The problem of yield as well as disease prediction is a major problem that
can be solved based on available data. Hence we proposed an system
Prediction of “A Research to Construct the Interactive Platform for Integrated
Information of Agricultural Products”.
OBJECTIVES OF WORK
In this proposed model we are going to implement following things:
 To make better use of Information Technology in forecasting the crops.
 To provide as well as predict the crop cultivation process based on their weather.
 To present the agriculture ecosystem and how the combination of E-Commerce and
Informatics is enabling smart agriculture.
 To help farmers to improve decision making quality.
 To suggest farmers to get high yield crops.
 To extract the information from a dataset and transform it into understandable
structure for further use.
Proposed Model
ALGORITHM
 Algorithm 1: K-Nearest Neighbor.
 Algorithm 2: K-Means Clustering.
 Algorithm 3: Google API (Open Weather Map)
 Algorithm 4: Classification Rule
Advantages
 Proposed System present the agriculture ecosystem and how the
combination of E-Commerce and Informatics is enabling smart agriculture.
 Suggest farmers to get high yield crops.
 Required less time.
 The experimental result shows that our application is as accurate as a
reference device.
 We perform a detailed security analysis and performance evaluation of the
proposed data.
 Increase Efficiency and accuracy.
Limitation
 Required proper project plan
 System required i.e. PC, Laptop.
 Internet Connection required
 Database required.
Future Scope
 Future work includes extending the performance prediction to
elective diseases and using the prediction results to recommend
fertilizers and precautions to prevent disease.
 This project can be used in any scientific organization, college as
analysis purpose.
Conclusion
 This system first analyzes Agriculture E-Commerce data. Then, an agricultural
Ecommerce platform based on data mining technology was established. Three
modules were designed in the overall architecture: E-Commerce module,
Informatics module, and data acquisition module by administration. Data such as
soil moisture content, temperature and humidity, light intensity, crop growth status,
and weather factors were obtained from the farmland. The data are then
transmitted to the server through agriculture department and the 3G network, and
the data are directly imported into the neural network model for processing the
data through the Web Service.
 Finally, by comparing the prediction results with the actual data, it is found that the
prediction error of the model designed in this system is within 1% and the
agricultural data are highly predictable, which helps efficiently in agricultural
production and to help farmers for better productivity cost.
References
 [1] Yuan Li, and Zhigang Li, “A Research to Construct the Interactive Platform for Integrated
Information of Agricultural Products in China Xinjiang.” IFIP International Federation for
Information Processing 2011.
 [2] G. Ramyalakshmi, A. Deeksha, M. Sumana, “Artificial Intelligence Based Recommendation
System for Farmers ,” International Journal of Computer Trends and Technology ( IJCTT ) .
 [3] Reuben Varghese, Smarita Sharma, “Affordable Smart Farming Using IoT and Machine
Learning” Proceedings of the Second International Conference on Intelligent Computing and
Control Systems (ICICCS 2018).
References (Cont..)
 [4] Olakunle Elijah, Tharek Abdul Rahman, Igbafe Orikumhi, Chee Yen Leow, and MHD Nour
Hindia, “An Overview of Internet of Things (IoT) and Data Analytics in Agriculture: Benefits
and Challenges,” IEEE Internet of Things Journal 2018.
 [5] YShubo Liu, Liqing Guo, Heather Webb, Xiao Yao, Xiao Chang, “Internet of Things
Monitoring System of Modern Eco-agriculture Based on Cloud Computing,” IEEE Access
2019.
 [6] Yitang Zeng, “Research on the Quality Supervision System of Agricultural Product Based
on Big Data,” Journal of Physics: Conference Series (ICCSCT 2020).
Publication
1. Paper Title: A Research to Construct the Interactive Platform for
Integrated Information of Agricultural Products.
2. Publication:
3. Paper Status:

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Agriculture ppt.pptx

  • 1. “A Research to Construct the Interactive Platform for Integrated Information of Agricultural Products”
  • 2. Contents  Introduction  Problem statement  Literature Survey  Existing System  Objectives  Proposed Model  Algorithm  Mathematical Model • UML Diagrams • Advantage • Limitation • Future Scope • Conclusion • Reference • Publication
  • 3. Introduction  The blockchain technology enables the traceability of information in the food supply chain and thus helps improve food safety.  It provides a secure way of storing and managing data, which facilitates the development and use of data-driven innovations for smart farming and smart index-based agriculture insurance.  The problem of yield prediction is a major problem that can be solved based on past data/dataset.  During the cultivation of crops, the amount of fertilizers, insecticides, fungicides and its related information are analyzed using E-Commerce platform and Informatics.  It will be beneficial if farmers could use the technique to predict the future crop productivity and consequently adopt alternative adaptive measures to maximize yield by using weather forecasting data.
  • 4. Problem Statement  Block chain as well as informatics is an emerging field of research in Information Technology as well as in agriculture. Agrarian sector in India is facing rigorous problem to maximize the crop productivity. The present study focuses on the applications of data mining techniques in yield prediction in the face of climatic change to help the farmer in taking decision for farming and achieving the expected economic return. The problem of yield prediction and as per productivity market is a major problem that can be solved based on available data.  Hence to address these problems we proposed a system “A Research to Construct the Interactive Platform for Integrated Information of Agricultural Products”, so in that we proposed both problems solution that is first E-Commerce of agriculture products and agriculture crop disease fertilizers & pesticides and second is Informatics about weather information, crop information, etc.
  • 5. Literature Review Sr. No. Paper name Author Publication Description 01 A Research to Construct the Interactive Platform for Integrated Information of Agricultural Products in China Xinjiang Yuan Li, and Zhigang Li IFIP International Federation for Information Processing 2011 Proposing an interactive platform for integrated information of agricultural products which combines farm production, supply and marketing of Xinjiang agricultural products. 02 Artificial Intelligence Based Recommendation System for Farmers G. Ramyalakshmi, A. Deeksha, M. Sumana International Journal of Computer Trends and Technology ( IJCTT ) 2019 In this paper, the farmer / beginner will predict the crop cultivation based on their weather, monsoon and soil type along with their pH level. 03 Affordable Smart Farming Using IoT and Machine Learning Reuben Varghese, Smarita Sharma Proceedings of the Second International Conference on Intelligent Computing and Control Systems (ICICCS 2018) In this paper, we develop an affordable system which when deployed will give an insight into the real time condition of the crop. The system leverages IoT and Machine learning to produce an affordable smart farming module.
  • 6. Literature Review (Cont…) Sr. No Paper name Author Publication Description 04 An Overview of Internet of Things (IoT) and Data Analytics in Agriculture: Benefits and Challenges Olakunle Elijah, Tharek Abdul Rahman, Igbafe Orikumhi, Chee Yen Leow, and MHD Nour Hindia IEEE Internet of Things Journal 2018 In this paper, several benefits and challenges of IoT have been identified. We present the IoT ecosystem and how the combination of IoT and DA is enabling smart agriculture. 05 Internet of Things Monitoring System of Modern Eco-agriculture Based on Cloud Computing. Shubo Liu, Liqing Guo, Heather Webb, Xiao Yao, Xiao Chang IEEE Access 2019 In this paper, Based on the new generation of information technology (IT), an integrated framework system platform incorporating Internet of Things (IoT), cloud computing, data mining and other technologies is investigated and a new proposal for its application in the field of modern agriculture is offered. 06 Research on the Quality Supervision System of Agricultural Product Based on Big Data. Yitang Zeng Journal of Physics: Conference Series (ICCSCT 2020) This paper systematically analyzes the role of big data in the quality supervision system of agricultural products and its innovative driving mechanism for operation mode
  • 7. Existing System  India is one among the oldest countries which is still practicing agriculture. But in recent times the trends in agriculture has drastically evolved due to globalization. Various factors have affected the health of agriculture in India. Many new technologies have been evolved to regain the health. One such technique is precision agriculture.  The problem of yield as well as disease prediction is a major problem that can be solved based on available data. Hence we proposed an system Prediction of “A Research to Construct the Interactive Platform for Integrated Information of Agricultural Products”.
  • 8. OBJECTIVES OF WORK In this proposed model we are going to implement following things:  To make better use of Information Technology in forecasting the crops.  To provide as well as predict the crop cultivation process based on their weather.  To present the agriculture ecosystem and how the combination of E-Commerce and Informatics is enabling smart agriculture.  To help farmers to improve decision making quality.  To suggest farmers to get high yield crops.  To extract the information from a dataset and transform it into understandable structure for further use.
  • 10. ALGORITHM  Algorithm 1: K-Nearest Neighbor.  Algorithm 2: K-Means Clustering.  Algorithm 3: Google API (Open Weather Map)  Algorithm 4: Classification Rule
  • 11. Advantages  Proposed System present the agriculture ecosystem and how the combination of E-Commerce and Informatics is enabling smart agriculture.  Suggest farmers to get high yield crops.  Required less time.  The experimental result shows that our application is as accurate as a reference device.  We perform a detailed security analysis and performance evaluation of the proposed data.  Increase Efficiency and accuracy.
  • 12. Limitation  Required proper project plan  System required i.e. PC, Laptop.  Internet Connection required  Database required.
  • 13. Future Scope  Future work includes extending the performance prediction to elective diseases and using the prediction results to recommend fertilizers and precautions to prevent disease.  This project can be used in any scientific organization, college as analysis purpose.
  • 14. Conclusion  This system first analyzes Agriculture E-Commerce data. Then, an agricultural Ecommerce platform based on data mining technology was established. Three modules were designed in the overall architecture: E-Commerce module, Informatics module, and data acquisition module by administration. Data such as soil moisture content, temperature and humidity, light intensity, crop growth status, and weather factors were obtained from the farmland. The data are then transmitted to the server through agriculture department and the 3G network, and the data are directly imported into the neural network model for processing the data through the Web Service.  Finally, by comparing the prediction results with the actual data, it is found that the prediction error of the model designed in this system is within 1% and the agricultural data are highly predictable, which helps efficiently in agricultural production and to help farmers for better productivity cost.
  • 15. References  [1] Yuan Li, and Zhigang Li, “A Research to Construct the Interactive Platform for Integrated Information of Agricultural Products in China Xinjiang.” IFIP International Federation for Information Processing 2011.  [2] G. Ramyalakshmi, A. Deeksha, M. Sumana, “Artificial Intelligence Based Recommendation System for Farmers ,” International Journal of Computer Trends and Technology ( IJCTT ) .  [3] Reuben Varghese, Smarita Sharma, “Affordable Smart Farming Using IoT and Machine Learning” Proceedings of the Second International Conference on Intelligent Computing and Control Systems (ICICCS 2018).
  • 16. References (Cont..)  [4] Olakunle Elijah, Tharek Abdul Rahman, Igbafe Orikumhi, Chee Yen Leow, and MHD Nour Hindia, “An Overview of Internet of Things (IoT) and Data Analytics in Agriculture: Benefits and Challenges,” IEEE Internet of Things Journal 2018.  [5] YShubo Liu, Liqing Guo, Heather Webb, Xiao Yao, Xiao Chang, “Internet of Things Monitoring System of Modern Eco-agriculture Based on Cloud Computing,” IEEE Access 2019.  [6] Yitang Zeng, “Research on the Quality Supervision System of Agricultural Product Based on Big Data,” Journal of Physics: Conference Series (ICCSCT 2020).
  • 17. Publication 1. Paper Title: A Research to Construct the Interactive Platform for Integrated Information of Agricultural Products. 2. Publication: 3. Paper Status: