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In the current scenario, there are no such recommendations in the available system online and also farmer has to physically go and ge thet recommendations based on their soil report provided by quality executives. Each and every sector in the digital world is going through a dramatic change due to the influence of IT field. But, till date not a whole lot work has been done in the agricultural sector. The use of various data mining techniques in agricultural section will be a continuing area of research. It will offer an internet base answer for the soil testing laboratories yet as free messages for the farmer that contains information on soil testing code, chemical that is important for the crop and additionally the knowledgeable recommendation. Additionally the farmers specify their next crop whereas they furnish their sample to scantiest therefore in keeping with next crop the chemical can recommend. The result’s which were obtained supported the classification of contains that should be gif tin soil and in keeping with result report are generated. The ultimate goal is to increase the growth of the agricultural sector.

1.3 Problem Definition
The basic aim of this project is to characterize and classify the soil to provide more details about the subsurface morphological information. An additional objective of this project is to seek out an approximate value of soil moisture and predict the fertility of soil and further predict which crops should be grown based on the soil moisture. The basic idea of this project is to get the values of Ph level ,temperature, moisture and humidity by using Ph meter, moisture sensor and temperature sensor. Then by using wifi module these values will be uploaded to the server and we will predict the fertility of the soil which will in turn help the farmers.

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1.4 Objectives of Project
The objectives of this study were to characterize and classify the soil to provide more details about the quality information of soil.
An additional objective of this study was to seek out approximate crops can be growing on that field..This study is to characterize and classify the soil to provide more details about the subsurface morphological information. An additional objective of this study was to seek out an approximate value of soil loss from the Lower Moshi Irrigation Scheme using the Universal Soil Loss Equation

1.5 Scope of the project
For future developments, it can be enhanced by developing this system for large acres of land. Also, the system can be integrated to check the quality of the soil and the growth of crop in each soil. The sensors and microcontroller are successfully interfaced and wireless communication is achieved between various nodes. Also, the system can be further improved by adding machine learning algorithms, which are able to learn and understand the requirements of the crop. This would help the field be an automatic system. The observations and results tell us that this solution can be implemented for reduction of water loss and reduce the man power required for a field. Agriculture is a field that still lacks the mass innovation and applications based on modern techniques. Our proposal of smart irrigation will make optimized use of sources and solve the problem of water shortage. The data is stored in the server. Based on the conditions, data would be retrieved.

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