A Review on Developing Tech-Agriculture using Deep Learning Methods by Applying UAVs

Authors

  • J V N Lakshmi  MCA Department, AIMS Institute of Higher Education, Bangalore, Karnataka, India
  • G V N Naresh  Chief Manager, Kotak Mahindra Bank, Bangalore, Karnataka, India

Keywords:

Deep Learning, Drones, UAVs, Agriculture, Artificial Intelligence, Neural Networks

Abstract

UAVs are replacing the manmade aircrafts or the satellites because of their peculiar feature of capturing high-resolution imagery below the cloud level. These drones are capable of collecting, mapping, processing and automation for computation using inexpensive open source tools. Now, invent of Deep Learning techniques took a great insights in handling the image datasets gathered by drones. Deep learning methods employed to experiment in finding the differences in the images and as well to improve the societal needs. Drones are boons for farmers in agriculture sector. Applying the Drone technology answers many issues in the field of agriculture. As agriculture is the major occupation of developing countries like India. Scarcity of food resources, reduction in land dimensions, high-end labour costs, uncertain weather and price of the crop yield are some of the factors prove to be peril profession. Technology supported agriculture is at present required to meet the needs. This can be achieved with invent of UAVs in agriculture for smart farming. This article briefs the application of drones in various aspects of agriculture. The methods applied assist in improving the farming practices. The main aim of this paper is to implement the drone technology for advancing the Indian agriculture.

References

  1. Allen,R. G. (1998). "Crop evapo-transpiration: Guidelines for computing crop water requirements",(FAO irrigation and drainage paper. Rome: FAO.Google Scholar
  2. Andriyas,S.,& McKee,M. (2013). "Recursive partitioning techniques for modeling irrigation behavior",Journal of Environmental Modelling & Software,47,207–217.
  3. Adrian C.,Carlos S.,et.al,(2017) ,"A Review of Deep Learning methods and Applications for Unmanned Aerial Vehicle",at CAR Hindawi,Journal of Sensors Article id: 3296874.
  4. Aditya S. N. and Kulkarni S.C. (2016),"Adoption and utilization of Drones for advanced Precision Farming: A Review",in IJRITCC Vol 4,Issue 5,pp:563-565.
  5. Anuj T. and Abhilasha D. (2015),"Unmanned Aerial Vehicle and Geo Spatial technology pushing the limits of development",AJER Vol 4 (1),pp: 16-21.
  6. Faine Greenwood,(2016),"ICT Update-a current awareness bulletin for ACP Agriculture – ESRI Agriculture CTA",Issue 82 from Signal Programme at Harvard Humanitarian Initiative.
  7. Yao C. and Zhang Y.,(2017),"Application of Convolutional Neural Network in Classification of High Resolution Agricultural Remote Sensing images",Spatial Information Science,Vol XLII 2/WT.
  8. Karandeep K.,(2016),"Machine Learning: Applications in Indian Agriculture",IJARCCE Vol 5,Issue 4 pp: 342-344.
  9. Konstantinos M. and Konstantinos K. (2015),"Deep Supervised learning for hyper Spectral Data Classification through Convolutional Neural Network",in IGARSS IEEE conf,pp: 4959-4962.
  10. Salman Siddique,(2015),"Sri Lanka’s drone pioneers"at Geographic Information System in Srilanka.
  11. Quan Le (2015),"A bird’s eye view on Africa’s rice irrigation Systems",as Developer at GrowmoreX in Africa.
  12. Keith Cressman,(2016),"Preventing the spread of desert Locust Swarms",as forecast officer at DLIS FAO in Rome.
  13. William Allen,(2015),"Drones protect crop stresses more effectively"as officer at Missourie.
  14. Ruchit G.,(2016),"Insuring Indian Farmers more effectively",at Silicon Valley for Data Driven insights to farmers.
  15. Robert A.Q.,(2015),"UAV based remote sensing will be like using a cell phone today"a scientist at International Potato Center CIP Lima,Peru.
  16. Ola Hall,(2015),"Challenge of Comparing Crop imagery over space and time",GIS Spatial analysis and remote sensing at Sweden.
  17. Raul Z.M.,(2015),"Transforming small holders farming through remote sensing",by Information Processing Faculty at STARS PROJECT.
  18. Eph raim Reynold,(2015),"Counting Coconuts with drones",GIS technician at Skyeye.
  19. Cedric J.,(2016),"Making Sense of drone regulations",by freelance Geographer and social ecologist.
  20. Walter Volkmann ,(2015),"Five steps of making map with small drones",Geo Spatial Solutions Specialist.
  21. De Etta Mills,(2016),"Drones and dogs work together to save Avocado crops",Florida International University and research.
  22. Steven W.C.,Shreyas S.,et al.,(2017),"Counting Apples and Oranges with Deep Learning: A Data Driven Approach",IEEE Robotics and Automation Letters Vol 2,Issue 2,pp: 781-788
  23. Hao J. and Shuisen C. et al.,(2017),"Papaya Tree Detection with UAV Images using a GPU- Accelerated Scale- Space Filtering Method",Journal of Remote Sensing,Vol 9,Issue 2.
  24. Weijia L.,Haohuan F.,et al,(2017),"Deep Learning Based oil palm Tree Detection and counting for High Resolution remote sensing Images",in Remote Sensing,Vol 9,Issue 2. 

IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2018-02-28

Issue

Volume 3, Issue 1, January-February-2018

Section

Research Articles

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
J V N Lakshmi, G V N Naresh, " A Review on Developing Tech-Agriculture using Deep Learning Methods by Applying UAVs , IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 1, pp.1858-1863, January-February-2018.