- Development of machine learning data pipeline and applications to agricultural and livestock structures
- Ceccarelli, Mattia <1996>
Subject
- AGR/10 Costruzioni rurali e territorio agroforestale
Description
- Big data analysis has made its way up to being one of the most requested skill in today’s world. Industries and research endeavours increasingly rely on advanced analytics techniques to navigate the vast volume of data originating from monitoring systems, wearables, cameras, and similar sources. The sheer amount of data collected has surpassed the feasibility of manual analysis or traditional statistical methods. Moreover, recent years have witnessed a significant reduction in the cost of powerful computing machines, enabling widespread access to advanced models for processing extensive datasets. The confluence of this accessible computational power and the inherent flexibility of machine learning has resulted in a thriving landscape for data analysis. Nowadays, machine learning technique are being applied in every sector, from physics to finance, from agriculture to medicine. In general, data science entails the ability to extract information, and eventually even knowledge, from large amount of data, often without the constraints of a meticulously designed experimental setup. This work delves into the applications of data science, specifically focusing on precision livestock farming, monitoring systems, and enhancing energy efficiency in agro-industrial buildings.
Date
- 2024-06-17
- info:eu-repo/date/embargoEnd/2025-05-06
Type
- Doctoral Thesis
- PeerReviewed
Format
- application/pdf
Identifier
urn:nbn:it:unibo-30344
Ceccarelli, Mattia (2024) Development of machine learning data pipeline and applications to agricultural and livestock structures, [Dissertation thesis], Alma Mater Studiorum Università di Bologna. Dottorato di ricerca in Scienze e tecnologie agrarie, ambientali e alimentari