Denis Kardakov
An overview of technologies in the AgriTech field: opportunities for insurance companies.
Rel. Lia Morra, Fabrizio Lamberti. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management), 2022
Abstract: |
Agriculture is one of the first spheres of the human economy. Over the years it has undergone radical changes, moving from bare-hand crop harvesting to using drones, robots, and other modern technologies that increase the farm’s efficiency and effectiveness. Today’s agriculture sector is responsible for feeding the whole Earth’s population and contributes to the GDP growth of many developing countries. All of these achievements would not be possible without the emergence and implementation of modern technologies, which are generally referred to as Smart farming or Agriculture 4.0. IoT sensors, machine learning and Big Data algorithms, AI, satellite imaging, robots, drones, and many more, today are helping farmers to increase their farms’ output. In order to help the farmers’ community fully benefit from using the technologies of smart farming, we need to understand the problems, challenges, and opportunities associated with the emergence of this framework. For this purpose, the present thesis introduces a systematic literature review of scientific papers and so-called “grey” literature (white papers, technical reports, corporate case studies, etc.) in order to build a comprehensive Smart farming technology categorization. Insights from the analysis of more than 100 use cases are illustrated to identify possible pitfalls and growth opportunities. Based on that analysis, possible avenues for new or improved insurance services, leveraging the use of modern technologies, are suggested.This overview provides an accurate snapshot of the technological landscape in the field of Agritech in 2022, alongside possible future opportunities for all players in the sector. |
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Relators: | Lia Morra, Fabrizio Lamberti |
Academic year: | 2022/23 |
Publication type: | Electronic |
Number of Pages: | 81 |
Additional Information: | Tesi secretata. Fulltext non presente |
Subjects: | |
Corso di laurea: | Corso di laurea magistrale in Ingegneria Gestionale (Engineering And Management) |
Classe di laurea: | New organization > Master science > LM-31 - MANAGEMENT ENGINEERING |
Aziende collaboratrici: | UNSPECIFIED |
URI: | http://webthesis.biblio.polito.it/id/eprint/25080 |
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