Soil testing Agriculture for long term optimization of yield Management Systems by using Machine Learning Algorithm

Project Title

Soil testing Agriculture for long term optimization of yield Management Systems by using Machine Learning Algorithm

Project Area of Specialization Internet of ThingsProject Summary

The current work illustrated the importance of smart agriculture on improving and increasing agricultural production in order to contribute to reducing the food demand gap. A soil-based crop selection and management system, as well as a standardized approach to define the composition of bare soil, metalloids, and ecological parameters, have been established in this study. We collect data for various soils and which crop is ideal for cultivation to produce maximum yield for a particular field based on statistical analysis. The farm field is controlled and monitored using a variety of sensors, including humidity sensors, temperature sensors, and cameras are used to control the agriculture field. Water level sensors, GSM, and a controller are used to control irrigation. Sensors are in charge of measuring and monitoring all aspects of the smart system; for example, soil health monitoring includes sensors for nutrients, phosphates, soil moisture, compaction, and other parameters. Many sensors for monitoring water levels, irrigation efficiency, climate sensors, and other features were added in the smart irrigation system. On-farm sensors may measure and monitor changes in soil and yield qualities, as well as local weather. As a result, the sensors can collect various data that can be utilized to analyze agricultural statutes and make appropriate decisions. These smart sensors track changes in soil, crop, and livestock health, as well as helping to improve the amount and quality of agricultural products. Sensors that are commonly utilized in smart agricultural networks are soil moisture sensors that use to measure the change in soil moisture, soil temperature used to measure the monitor the temperature in soil, air temperature, soil pH value, humidity, N, P, K sensors.

Project Objectives

Accurate evaluation of soil and crops and improving agricultural production. Demand for food supply increased day by day as population increased. Smart agriculture is critical for enhancing agricultural production in order to overcome the food demand gap.

Our aim is to design such tools that will increased crop production for continues food supply.

Objective of this project is to implementation such tools to soil for optimization of yield to fulfill the requirement of food.

Project Implementation Method

In our project, we are going to predict yield and Soil testing for long-term optimization to increase the production and also find out the diseases with the help of 
machine learning algorithms CNN and LSTM. Yield prediction is important for the government as a well individual farmer. 
Currently, there is no effective automated system is available in Pakistan. Cheap yield prediction is 
important for timely decisions. Diseases have greater impact on yield

Benefits of the Project

 Predict crop yield at an early stage.
2. Predict the soil.
3. Detect the weather.
4. Provide better information for making a management decision.
5. Provide more details and useful farm records.
6. Reduces fertilizer costs.
7. Detection of diseases.
8. Rectify the disease.
9. Reduce time while detecting diseases.
10. Reduces pesticides costs.
11. The crop is ripe with the time frame.

Technical Details of Final Deliverable

? Data processing
? Machine learning
? Training model
? Yield prediction
? Disease detection
? User interface (input-output)

Final Deliverable of the Project Hardware SystemCore Industry AgricultureOther Industries Others Core Technology Internet of Things (IoT)Other Technologies Artificial Intelligence(AI)Sustainable Development Goals No Poverty, Good Health and Well-Being for People, Affordable and Clean Energy, Reduced Inequality, Responsible Consumption and ProductionRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	73440
Arduino Wifi	Equipment	2	2000	4000
Node Mcu	Equipment	2	1500	3000
Moisturization Sensor	Equipment	2	500	1000
Ph sensor	Equipment	2	15000	30000
temperature sensor	Equipment	2	1500	3000
soil tester	Equipment	2	2000	4000
GPS Tracker	Miscellaneous	2	2000	4000
GSM sensor	Equipment	2	1000	2000
LCD	Equipment	500	2	1000
jumper wire	Equipment	20	72	1440
Respri pi	Equipment	1	20000	20000