As India is agricultural based country. In a field of agriculture, sustained harvesting must be followed with fixed check of fertility rate of soil because soil nutrient measurement is very essential and plays an important role in proper plant growth and effective fertilization. The more accurate method leads to better future of farmers. In this paper we have reviewed many methods for measuring the soil nutrients. The traditional approach is to perform test in soil testing laboratories where chemical process is performed after drying the soil and other preprocessing but it leads to more efforts and tedious process. As a solution a smarter way in which the level is observed and measured using Photodiodes, Light Emitting Diodes, analog-to-digital converter (ADC), FPGA and NIR Laser. AS a result it will leads to more time saving and detailed measure of nutrients. According to NPK values of soil that are acquired and whether attributes, prediction of future crop is possible. Using various techniques for measuring soil nutrients and according to that nutrients using various classification and machine learning algorithms we can make the prediction of which crop to cultivate. Those Methods are studied analyzed according to various requirements.

Data mining, NPK detection, Optical transducer, Soil fertility, Classification, Crop prediction

[1] S. S. Gadgil and R. R. Lobo, "Arduino Applications for Smart Cities," IJCSE, vol. 04, no. 04, pp. 4-20, 2016.
[2] K. b. M. Yusof, Suhaila binti Isaak and N. H. b. Ngajikin, "LED based soil spectroscopy," Buletin Optik, 2016.
[3] M. Marianah and S. A. R. Mohamad, "Detection of Nitrogen, Phosphorus, and Potassium," IEEE, 2017.
[4] A. Rawankar, M. Nanda, H. Jadhav and P. Lotekar, "Detection of N,P,K Fertilizers in Agricultural Soil with NIR Laser Absorption Technique," in International Conference on Microwave and Photonics (ICMAP 2018), 2018.
[5] J. C. PUNO, E. S. E. DADIOS, I. VALENZUELA and J. CUELLO, "Determination of Soil Nutrients and pH level using Image Processing and Artificial Neural Network," IEEE, 2017.
[6] M. W. JIanhan Lin and M. Zhang, "Electrochemical sensors for soil nutrient detection: Oppertunity and challange," KLMPASI, Ministory of Education, China, Baijing.
[7] D. Vadalia, M. Vaity, K. Tawate and D. Kapse, "Real Time soil fertility analyzer and crop prediction," International Research Journal of Engineering and Technology (IRJET), vol. 04, no. 03, 2017.
[8] S. S.N. and D. M.B., "Real-Time Monitoring of Soil Nutrient Analysis using WSN," in International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS), 2017.
[9] M. K. R. S. Preetha, S. Nishanthini and D. Santhiya, "Crop Yield Prediction," IJETS, vol. III, 2016.
[10] C. P. Devi and T Vigneswari, "A Survey on Machine Learning and Stastical Meyhods for Bankruptcy Prediction," IJCSE, vol. 7, no. 3, 2019.
[11] Y. He, Y. Zhang, S. Zhang and H. Fang, "Application of Artificial Neural Network on Relationship Analysis between Wheat Yield and Soil Nutrients," in IEEE Engineering in Medicine and Biology 27th Annual Conference, Shanghai, China, 2005.
[12] P. D. Zingade, O. Buchade, N. Mehta, S. Ghodekar and C. Mehta, "Machine Learning based Crop Prediction System Using Multi-Linear Regression," IJETCS, vol. 3, no. 2018, 2018.
[13] T. Sujjaviriyasup and K. Pitiruek, "Agricultural Product Fore- casting Using Machine," Int. Journal of Math. Analysis, vol. 7, 2013.
[14] R. Kumar, M. Singh, P. Kumar and J. Singh, "Crop Selection Method to Maximize Crop Yield Rate using Machine Learning Technique," in International Conference on Smart Technologies and Management,Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, 2015.