**4. Experimentation and results**

The proposed organic farming model can be implemented in two phases, the first phase is building hardware kit using IoT enabled sensor technology to measure the soil macro nutrients [NPK] and pH of irrigation water. The second phase is developing advisory mobile application using Android studio to predict and suggest the suitable crop and appropriate fertilizer for organic farming to achieve sustainable agriculture. The experiment for measuring the soil parameter and pH of irrigation water has been conducted in fields for different soil samples. The results obtained from the sensor forms repository for further processing to predict crop and fertilizer using machine learning algorithm viz. SVM technique.

The **Figure 14** shows the experimental setup of hardware kit which consists of Arduino UNO microcontroller to control all the operation. The IoT enabled sensors namely soil moisture sensor to measure the moisture content of the soil, temperature and humidity sensor (DHT11) to measure the temperature and humidity of soil respectively, pH sensor for water pH value and color sensor is used to determine the soil NPK value.

Experimentation is carried out for six different parts of the Bagalkot district namely Hunugund, Kaladagi, Kerur, Bilagi, Kudalsangam and Mudhol of Karnataka State, India. The different lands of soil samples to measure the soil parameter such as moisture, temperature, humidity and NPK nutrient value of soil. The pH value of the

**Figure 14.** *Experimental setup of IoT enabled kit.*

irrigation water is also determined at different locations of land including borewell water, rain water, river water etc. available in the reservoirs. The suitable pH value for the irrigation water for sustainable agriculture should lie between the value 5 to 7.

Experimentation is conducted as shown in **Figure 15** to measures the moisture, temperature and humidity content of soil in agriculture field which has grown green grams. The results are uploaded onto the thingsspeak software. This software helps to visualize and analyze live data by plotting graphs, the graph for moisture is shown in **Figure 16** and graph for temperature and humidity are as shown in **Figure 17**.

#### **Figure 15.**

*Experimental setup of hardware kit to collect NPK values.*

#### **Figure 16.**

*Graph showing soil moisture.*

**Figure 17.** *Graph of humidity and temperature of soil.*

#### *Organic Farming for Sustainable Agriculture Using Water and Soil Nutrients DOI: http://dx.doi.org/10.5772/intechopen.100319*

Experimentation is additionally done to quantify these essential supplements and results are appeared in **Figures 18** and **19**.

The values which are retrieved from the sensor are transferred to Arduino from there to thingsspeak software and eventually on to the app. The result for different soil sample have been listed in the **Table 4**. With these measurements the sustainability is maintained and increased organic yield is obtained as depicted in the above **Table 1**.

Experimentation is also conducted to determine pH of irrigation water the LCD display value as shown in **Figure 20** shows the result of pH of water.

The Second step of implementation in the proposed methodology is developing the mobile application to assist the farmer in selecting location specific crop for cultivation and also provide appropriate fertilizer recommendation to the farmer. The developed mobile app can be used by both APMC admin and farmer as shown in **Figure 21** through which it establishes a communication link between them.

**Figure 18.** *LCD display output for soil sample 1.*



#### **Table 4.**

*Results of sensor readings for different soil sample.*

**Figure 20.** *LCD display value of pH of irrigation water.*


**Figure 21.** *Mobile application - direct marketing.*
