Paper PublishingAI Based Prediction of Crop Harvesting by Using Essential Fertilizers
Project Code :TCMAPY438
Objective
The main objective of this project is to use machine learning techniques for predicting amounts of nutrients required for fertilizing a crop.
Abstract
India being an agriculture country, its economy predominantly depends on agriculture yield growth and agro-industry products. Maintaining high yield is a very important issue in agricultural. Any farmer is interested in knowing how much yield he is about to expect. Analyse the various related attributes like location, pH value from which alkalinity of the soil is determined. Along with it, percentage of nutrients like Nitrogen (N), Phosphorous (P), and Potassium (K) Location is used along with the use of third-party applications like APIs for weather and temperature, type of soil, nutrient value of the soil in that region, amount of rainfall in the region, soil composition can be determined. All these attributes of data will be analysed, train the data with various suitable machine learning algorithms for creating a model. The system comes with a model to be precise and accurate in predicting the end user with proper recommendations about required fertilizer ratio based on atmospheric and soil parameters of the land which enhance to increase the crop yield and increase farmer revenue. It also recommends a gel, oil or other chemical agent required for better crop growth.
Keywords: Supervised Learning, Crop Yield, Fertilizers, Gels, Oils etc.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
Block Diagram
Specifications
HARDWARE SPECIFICATIONS:
- Processor : I3/Intel Processor
- RAM : 4GB (min)
- Hard Disk : 128 GB
- Key Board : Standard Windows Keyboard
- Mouse :
Two or Three Button Mouse
- Monitor : Any
SOFTWARE SPECIFICATIONS:
- Operating System : Windows 7+
- Server-side Script : Python 3.6+
- IDE : PyCharm / Jupyter Notebook.
- Libraries Used : Pandas, Numpy, Scikit-learn.
Learning Outcomes
- Scope of Real Time Application Scenarios.
- How Internet Works.
- What is a search engine and how browser can work.
- What type of technology versions are used.
- Use of HTML and CSS on UI Designs.
- Data Parsing Front-End to Back-End.
- Working Procedure.
- Introduction to basic technologies used for.
- How project works.
- Input and Output modules.
- Frame work use.
- Data base connections.
- About python.
- Crud operations.
- Python built in function.
- How the voting system performs.
- Project Development Skills:
- Problem analyzing skills.
- Problem solving skills.
- Creativity and imaginary skills.
- Programming skills.
- Deployment.
- Testing skills.
- Debugging skills.
- Project presentation skills.
- Thesis writing skills.
Related Topics
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