IoT Based Farming Recommendation System Using Soil Nutrient and Environmental Condition Detection
Arun Kumar1, Abhishek Kumar2, Akash De3, Shashank Shekhar4, Rohan Kumar Singh5
1Arun Kumar, Apex Institute of Technology, Chandigarh University, Mohali, India.
2Abhishek Kumar, Apex Institute of Technology, Chandigarh University, Mohali, India.
3Akash De, Apex Institute of Technology, Chandigarh University, Mohali, India.
4Shashank Shekhar, Apex Institute of Technology, Chandigarh University, Mohali, India.
5Rohan Kumar Singh, Apex Institute of Technology, Chandigarh University, Mohali, India.
Manuscript received on 23 August 2019. | Revised Manuscript received on 03 September 2019. | Manuscript published on 30 September 2019. | PP: 3055-3060 | Volume-8 Issue-11, September 2019. | Retrieval Number: K23350981119/2019©BEIESP | DOI: 10.35940/ijitee.K2335.0981119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Over one third of world workforce are employed in agriculture and the amount is steadily falling because of the financial losses of the farmers. One of the key reason behind this financial loss is the lack of technology in agriculture. Continuous cropping and overuse of fertilizers cause the decline in soil productivity and effect the environment as well. This paper demonstrates how the soil productivity can be optimized by implementing an IoT (Internet of Things) based model. Specifically, the paper describes the way to identify the amount of soil nutrients and environmental conditions, followed by the recommendations for cropping and site specific fertilization. Nitrogen, phosphorous and potassium are the key nutrients that are responsible for the plant growth. Soil moisture, pH level of soil and environmental conditions also effects the productivity of crops. In this present work, the system incorporated with various chemicals and sensors to report NPK level, pH level, soil moisture level, temperature and weather forecast. The proposed system takes the soil sample as the input and performs the chemical reactions, corresponding changes in the color of sample is sensed by color sensors and decoded by colorimetry technique. An android application has been built to show the test report and recommendations based on sensed data. The paper has proposed a scientific way to develop a robust, fully automated and low-cost smart farming solution to suit the socioeconomic conditions of small scale farmers in developing countries.
Keywords: Soil Nutrients, Precision Agriculture, Arduino.
Scope of the Article: Soil-Structure Interaction