Agricultural Intelligence Decision System Using Big Data Analysis

Authors

  • Patil HP Dept. of Computer Science, East West Institute of technology, Vishveswaraya Technological University, Bangalore, India
  • Gokul D Dept. of Computer Science, East West Institute of technology, Vishveswaraya Technological University, Bangalore, India
  • Dharmatej M Dept. of Computer Science, East West Institute of technology, Vishveswaraya Technological University, Bangalore, India
  • Reddy KV Dept. of Computer Science, East West Institute of technology, Vishveswaraya Technological University, Bangalore, India
  • Chandan Raj BR Dept. of Computer Science, East West Institute of technology, Vishveswaraya Technological University, Bangalore, India

Keywords:

big data technology, hadoop, environmental data, decision making

Abstract

Using hadoop in big data technologies into agriculture presents a significant challenge; at the same time, this technology contributes effectively in many countries’ economic and social development. In this work, we will study environmental data provided by precision agriculture information technologies, which represents a crucial source of data in need of being wisely managed and analyzed with appropriate methods and tools in order to extract the meaningful information by providing decision making support to the farmers.

References

[1] Ritaban Dutta; Ahsan Morshed; Jagannath Aryal; Claire D`Este...Development of an intelligent environmental knowledge system for sustainable agricultural [J]. Environmental Modelling and Software. 2014.

[2] Ştefan Conţiu; Adrian Groza. Improving remote sensing crop classification by argumentation-based conflict resolution in ensemble learning [J]. Expert Systems With Applications,2016.

[3] Safaa Abdelraouf Ahmed; Shadia Ragheb Tewfik; Hala Ahmed Tal. Development and verification of a decision support system for the selection of optimum water reuse schemes [J]. Desalination,2003.

[4] M. Pérez-Ruiz; P. Gonzalez-de-Santos; A. Ribeiro; C. Fernand. Highlights and preliminary results for autonomous crop protection [J]. Computers and Electronics in Agriculture, 2015.

[5] Ranya Elsheikh; Abdul Rashid B. Mohamed Shariff; Fazel Amiri. Agriculture Land Suitability Evaluator (ALSE): A decision and planning support tool for tropical and subtropical crops [J]. Computers and Electronics in Agriculture, 2013.

[6] Wu Wan-sheng; Su Zhong-bin; Li Xiao-ming. Research on Intelligent Decision Support System of Soybean [J]. Journal of Northeast Agricultural University(English Edition), 2013.

[7] Golait, Current Issues in Agriculture Credit in India: An Assessment, Reserve Bank of India Occasional Papers, Vol.28, Issue No.1, pp. 1-2, 2017.

[8] Manes, ICT applications in agriculture from Precision Agriculture to Aml, Presented in MIDRA Consortium, Ambient Intelligence Workshop, Florence 2017.

[9] Pulapre, Ramesh, Pankaj, Agriculture Growth in India Since 1991, Department of Economics Analysis and policy, Reserve Bank of India, Mumbai, Study No. 27, pp 18-19, 2015.

[10] Blackmore, S.(1994). Precision Farming: An Introduction. Outlook on Agriculture 23(4) 4, 275-280.

[11] R. D. Ludena, A. Ahrary et al., “Big data approach in an ict agriculture project,” in Awareness Science and Technology and Ubi-Media Computing (iCAST-UMEDIA), 2013 International Joint Conference on. IEEE, 2016, pp. 261–265.

[12] B. Venkatalakshmi and P. Devi, “Decision support system for precision agriculture,” International Journal of Research in Engineering and Technology, vol. 3, no. 7, pp. 849–852, 2014.

[13] H R Zhang, Z L Li, T F Qu, X Y Wei and G C Yang, “Overview of Agriculture Big Data Research”, Computer Science, vol.41, no.11A, pp.387-392, Nov 2014.

[14] J Q Ren, Z X Chen and Q P Zhou, “MODIS vegetation index data used for estimating corn yield in USA”, Journal of Remote Sensing, vol.19, no.4, pp.568-577, 2015.

[15] F Q Song, Z L Zheng and L C Wang, “Yield Estimation for Winter Wheat of Henan Province Based on CASA Model”, Henan Science vol.30, no.10, pp. 1466-1471, Oct.2014.

[16] W G Li and L H Zhao, “Wheat growth monitoring based on medium and high resolution images”,Jiangsu Journal of Agricultural Sciences, vol.27, no.4, pp.736-739, 2017.

[17] Y L Qian, Y Y Hou and H Yan, “Global crop growth condition monitoring and yield trend prediction with remote sensing”, Transactions of the Chinese Society of Agricultural Engineering, vol.28, no.13, pp.166-171, 2015.

[18] C Yang, J H EVERITT and D MURDEN, “Evaluating high resolution SPOT 5 satellite imagery for crop identification”, Computers & Electronics in Agriculture, vol.7q5, no.2, pp.347-354, 2015.

[19] Pierce, F.J.; Elliott, T.V. Regional and on-Farm Wireless Sensor Networks for Agricultural Systems in Eastern Washington. Comput. Electron. Agric. 61, pp 32-43, 2016.

[20] K Yu, Z M Wang and L Sun. “Crop growth condition monitoring and analyzing in county scale by time series MODIS medium resolution data”, proceedings of the International Conference on Agro-Geo informatics, F, 2017.

Downloads

Published

2025-11-26

How to Cite

[1]
H. P. Patil, G. D, D. M, K. V. R. Reddy, and C. R. BR, “Agricultural Intelligence Decision System Using Big Data Analysis”, Int. J. Comp. Sci. Eng., vol. 7, no. 15, pp. 27–31, Nov. 2025.