scholarly journals Farm-n-Pedia: Expert mobile agricultural knowledge-based system for Indian Farmers

2021 ◽  
Vol 10 (7) ◽  
pp. 27-39
Author(s):  
Ashmean Kaur Sran ◽  
Sherrie Yi Komiak ◽  
Sabir Manzoor
Keyword(s):  
Interface Design ◽  
Mobile Application ◽  
Expert Knowledge ◽  
Agricultural Practices ◽  
Crop Productivity ◽  
Technological Advancement ◽  
Knowledge Based System ◽  
Agriculture Sector ◽  
Knowledge Based ◽  
Agriculture Management

Efficiency in farming productivity and optimum utilization of resources in the agriculture sector in developing countries is a challenge that can be addressed with technological advancement. There is also a strong need to work on the farming community’s engagement to make better farming decisions. This study aims to create an expert knowledge-based system (KBS) in a mobile application to help Indian farmers improve their agricultural practices and increase crop productivity. A prototype mobile application, ‘Farm-n-Pedia,’ is designed and used to fulfill the farmers’ informational and engagement needs. It provides a tool for agriculture management using a single platform. The expert KBS incorporates a crowdsourcing system as part of the knowledge base and interface design. The mobile application enables the users to access the worldwide information they want, get personalized expert guidance, interact with the local agrarian community, know about the latest farming techniques and technology, crowdsource data collection and increase agricultural productivity.

scholarly journals Social Innovation through Precision Farming: An IoT Based Precision Farming System for Examining and Improving Soil Fertility and Soil Health

2019 ◽  
Vol 8 (11) ◽  
pp. 2877-2881
Keyword(s):  
Soil Fertility ◽  
Crop Production ◽  
Production Efficiency ◽  
Social Innovation ◽  
Soil Health ◽  
Farming System ◽  
Crop Productivity ◽  
Precision Farming ◽  
Technological Advancement ◽  
Agriculture Sector

Agriculture is the most important sector of Indian Economy. Indian agriculture sector provides employment to 50% of the countries workforce. India is the world's largest producer of pulses, rice, wheat, sugarcane, pomegranates etc. The current scenario of agriculture business in India is not up to the mark as expected. There are number of reasons which causes less yield in the agriculture such as unpredictable environmental conditions, excess use of fertilizers (cost is increasing day by day), increased draught frequency and its severity, increasing labor rate, less difference between the income and expenditure, ripeness of soil, influenced suspensions, non-appropriate water management, diseases on crops, invasion of animals and so on. There is need to find the ways which makes the use of Information Technology (IT) concepts and tools wherever possible for increasing automation in the agriculture business, which results in the efficient and effective outcome of agriculture i.e. higher yields. The production efficiency can be increased significantly with technological advancement in agriculture. Internet of Things (IoT) is a novel design approach for precision farming. Farming has seen number of technological transformations in the last decade. By using various smart agriculture gadgets, farmers have gained better control over the process of raising the growing crops and livestocks. One of the major issues which cause fewer yields is the soil health. This paper mainly analyses/reviews the problems related to the soil health (soil fertility), which is a main obstacle in the crop production. Also this study focuses on the use of IoT applications in precision farming. It gives an overview of the relation between crop productivity and soil health

scholarly journals Sistem Diagnosa Penyakit THT Pada Balita Menggunakan Dempster Shafer

2018 ◽  
Vol 3 (1) ◽  
pp. 27
Author(s):  
Maura Widyaningsih
Keyword(s):  
Decision Making ◽  
Problem Solving ◽  
Expert Systems ◽  
Expert Knowledge ◽  
Computing Systems ◽  
Knowledge Based System ◽  
Forward Chaining ◽  
Knowledge Based ◽  
Rule Changes ◽  
Auxiliary Program

Computer field supports the existence of auxiliary program in medical development that is expert knowledge-based system, this system is one branch of Artifical Intellegence (AI). Expert systems are knowledge in learning about estimation or decision-making ability of an expert. Problem solving in the identification of a disease by using auxiliary program is needed a method and concept. Calculation techniques in computing systems are so important, given the level of need for information and the settlement of cases quickly.The results of the study are expert applications that assist in providing results of diagnosis of symptoms managed  the system, with inference using forward chaining, and reasioning with Dempster Shafer. Dempster Shafer's method is not monotonous in solving uncertainty problems, due to the addition or subtraction of new facts. Rule changes will occur, allowing the system to do the work of an expert.Data changes will occur both to diseases, symptoms, solutions and rules, allowing the system to do the work of an expert. The results of manual calculations with the system gives results in accordance with the application of Dempster Shafer method. Management of rules in the database facilitates the search for symptoms within the system.

scholarly journals Developing a Prototype Knowledge-Based System for Diagnosis and Treatment of Diabetes Using Data Mining Techniques

2020 ◽  
Vol 30 (1) ◽  
Author(s):  
Kedir Eyasu ◽  
Worku Jimma ◽  
Takele Tadesse
Keyword(s):  
Data Mining ◽  
Expert Knowledge ◽  
Diagnosis And Treatment ◽  
Data Mining Techniques ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
The Status ◽  
Treatment Of Diabetes ◽  
Using Data ◽  
Accuracy Of Results

BACKGROUND: Diabetes is a disease that affects the body’s ability to produce or use insulin. A total of 425 million people are suffering from diabetes in the world. Of this, more than 16 million people live in the Africa Region, which is estimated to be around 41 million by 2045. The main objective of this study was to design and develop a prototype knowledge-based system using data mining techniques for diagnosis and treatment of diabetes.METHODS: For this study, experimental research design was employed, and the researchers used domain expert knowledge as a supplement of data mining techniques whereby three classification algorithms in WEKA; namely J48, PART and JRip were used, and finally the researchers decided to use the results of J48 classification algorithm. Ultimate Visual basic studio 2013 (Vb.net) was used to store knowledge and as front side of prototype. Common lisp prolog (Clisp) was used for obtained knowledge back end coding.RESULTS: Using a decision tree algorithm; namely J48, 2512 (95.1515%) of the instances were classified correctly, and 128 (4.8485 %) were classified incorrectly. The second most performing model was generated by JRip Classier. This model scored the 94.7348% accuracy on the general data to classify the status of diabetic patient datasets. It classified the 2501 instances of the records correctly.CONCLUSION: The J48 model was the best performing model with the best accuracy of results. 

A Knowledge-Based System for Disaster Emergency Relief

2020 ◽  
Vol 34 (11) ◽  
pp. 2059038 ◽  
Author(s):  
Bo Li ◽  
Tingting Li ◽  
Qing Jiang ◽  
He Huang ◽  
Rujing Wang ◽  
...  
Keyword(s):  
Natural Disasters ◽  
Expert Knowledge ◽  
System Development ◽  
Human Beings ◽  
Plan Evaluation ◽  
Emergency Relief ◽  
Evaluation Plan ◽  
Knowledge Based System ◽  
Knowledge Based ◽  
Hybrid Knowledge

Natural disasters have had great impact on human beings. Emergency relief is becoming more important with the increase of the frequency and scale of humanitarian emergencies resulting from more natural disasters because of climate change. In this paper, an interesting hybrid knowledge representation method during the development of a KBS for design of emergency relief structures is presented. It encapsulates ill-structured, semi-structured and structured knowledge that is gathered from literature, human expert and even knowledge gleaned during the system development. All routine as well as cumbrous activities in the emergency relief cycle are covered. The system can provide the user with advice on preliminary plan evaluation, plan optimization, plan evaluation, plan summary and miscellaneous. It would be beneficial to the field of disaster emergency relief decision by focusing on the acquisition and organization of expert knowledge through the development of knowledge-based system.

Analysis of Crop Yield Prediction of Kharif & Rabi Jowar Crops Using Data Mining Techniques

2017 ◽  
Vol 7 (11) ◽  
pp. 79
Author(s):  
Sujata Mulik
Keyword(s):  
Data Mining ◽  
Crop Yield ◽  
Crop Production ◽  
Climatic Factors ◽  
Crop Productivity ◽  
Yield Prediction ◽  
Data Mining Techniques ◽  
Agriculture Sector ◽  
Using Data ◽  
Rabi Crops

Agriculture sector in India is facing rigorous problem to maximize crop productivity. More than 60 percent of the crop still depends on climatic factors like rainfall, temperature, humidity. This paper discusses the use of various Data Mining applications in agriculture sector. Data Mining is used to solve various problems in agriculture sector. It can be used it to solve yield prediction.  The problem of yield prediction is a major problem that remains to be solved based on available data. Data mining techniques are the better choices for this purpose. Different Data Mining techniques are used and evaluated in agriculture for estimating the future year's crop production. In this paper we have focused on predicting crop yield productivity of kharif & Rabi Crops. 

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