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Integrating Big Data Practices in Agriculture

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IoT and Analytics for Agriculture

Part of the book series: Studies in Big Data ((SBD,volume 63))

Abstract

The world is facing shortage of food supply due to lack of integration and utilization of technology in agriculture. Huge information available online about cultivation using drones, details about production and consumption of fertilizer, crop productivity and production data could be used efficiently to make farming practices better and more efficient. Big Data provides a high volume, speed and assortment required for particular innovation and explanatory strategies for efficient agriculture operation right from farm cultivation to marketing. In this chapter, we have laid focus on integration of Big Data practices in agronomical practices, supply chain operation and consumers’ feedback, by using different Big Data approaches. This chapter would help in understanding the multifaceted concept of Big Data in various agricultural practices.

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Author information

Authors and Affiliations

  1. Erasmus School of Economics, Erasmus University, Rotterdam, The Netherlands

    Jolly Masih

  2. School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India

    Rajkumar Rajasekaran

Authors
  1. Jolly Masih
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  2. Rajkumar Rajasekaran
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Corresponding author

Correspondence to Jolly Masih .

Editor information

Editors and Affiliations

  1. School of Computer Engineering, Kalinga Institute of Industrial Technology, Bhubaneswar, Odisha, India

    Prasant Kumar Pattnaik

  2. Department of Computer Science and Engineering, Laxmi Narayan College of Technology, Jabalpur, Madhya Pradesh, India

    Raghvendra Kumar

  3. Department of Computer Science and Engineering, JIS College of Engineering, Nadia, West Bengal, India

    Souvik Pal

  4. Chitkara University, Chandigarh, Punjab, India

    S. N. Panda

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Masih, J., Rajasekaran, R. (2020). Integrating Big Data Practices in Agriculture. In: Pattnaik, P., Kumar, R., Pal, S., Panda, S. (eds) IoT and Analytics for Agriculture. Studies in Big Data, vol 63. Springer, Singapore. https://doi.org/10.1007/978-981-13-9177-4_1

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