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Agrilogistics - A Genetic Programming Based Approach

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Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST,volume 318)

Abstract

The advent of technology in the agriculture sector, such as precision agriculture, the Internet of Things (IoT) and machine learning has dramatically improved the experience of farming scenario. Apart from improving the farming conditions, there is a need for focused effort to achieve a balanced ecosystem in the supply chain of agrilogistics. Inefficient price signals conveyed to the farmer, erratic price fluctuations and inflation of the agri-produce coupled with the presence of several intermediaries, tend to imbalance the system. In this work, we propose an IoT based agrilogistic system coupled with a genetic programming algorithm to ensure fair prices across all the participants within. The system evolves and generates a set of programs that, in turn, generates the selling rate for every participant in the supply chain in a manner that confers fairness.

Keywords

  • Internet of Things (IoT)
  • Genetic Programming
  • Agrilogistics
  • Supply chain

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Correspondence to Divya D. Kulkarni .

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Kulkarni, D.D., Nair, S.B. (2020). Agrilogistics - A Genetic Programming Based Approach. In: Pereira, P., Ribeiro, R., Oliveira, I., Novais, P. (eds) Society with Future: Smart and Liveable Cities. SC4Life 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 318. Springer, Cham. https://doi.org/10.1007/978-3-030-45293-3_7

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  • DOI: https://doi.org/10.1007/978-3-030-45293-3_7

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