Investigation of Common Big Data Analytics and Decision-Making Requirements Across Diverse Precision Agriculture and Livestock Farming Use Cases

Spiros Mouzakitis,Ioannis N Athanasiadis,Simos Ntanopoulos,Sjoukje Osinga,Dimitris Askounis,Giannis Tsapelas,Sotiris Pelekis

doi:10.1007/978-3-030-39815-6_14

Spiros Mouzakitis, Ioannis N Athanasiadis + Show 5 more

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https://doi.org/10.1007/978-3-030-39815-6_14

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Abstract

The purpose of this paper is to present the investigation of common requirements and needs of users across a diverse set of precision agriculture and livestock farming use cases that was based on a series of interviews with experts and farmers. The requirements were based on nine interviews that were conducted in order to identify common requirements and challenges in terms of data collection and management, Big Data technologies, High Performance Computing infrastructure and decision making. The common requirements that derived from the interviews and user requirement analysis per use case can serve as basis for identifying functional and non-functional requirements of a technological solution of high re-usability, interoperability, adaptability and overall efficiency in terms of addressing common needs for precision agriculture and livestock farming.

Highlights

The recent technological advancements in Big Data, Artificial Intelligence (AI), High Performance Computing (HPC), Cloud Services and Internet of Things (IoT) have the potential to enable farmers to overcome long-standing challenges in exploiting the vast amount of data that can be collected, in order to increase efficiency and productivity while reducing the initial farm input costs [1–3]
Big data and AI enable novel precision agriculture opportunities that allow the performing of queries and analytics on a distributed and diverse set of collected data that may lead to better and faster predictions and vital insights for farming decisions
The purpose of this paper is to present the investigation of common requirements and needs of users across a diverse set of precision agriculture and livestock farming use cases that was based on a series of interviews with experts and farmers

Summary

Introduction

The recent technological advancements in Big Data, Artificial Intelligence (AI), High Performance Computing (HPC), Cloud Services and Internet of Things (IoT) have the potential to enable farmers to overcome long-standing challenges in exploiting the vast amount of data that can be collected, in order to increase efficiency and productivity while reducing the initial farm input costs [1–3]. Big data and AI enable novel precision agriculture opportunities that allow the performing of queries and analytics on a distributed and diverse set of collected data (from IoT devices, images, video, satellite data, etc.) that may lead to better and faster predictions and vital insights for farming decisions. Livestock production management exploits technology to quantitatively measure the behaviour, health and performance of animals, including real-time monitoring of reproduction, health and welfare of livestock and the corresponding environmental impact [11, 12]. There is an increasing literature of individual use-cases on precision agriculture and livestock farming applications, the identification of common requirements and challenges across different use cases is currently missing

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