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Enhancing agricultural audit systems with IoT and predictive analytics: deployment and performance
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Orientador(es)
Resumo(s)
This article proposes an extension of a geospatial-based agricultural audit platform by integrating Internet of Things technologies and predictive analytics. It builds on previous work to address field connectivity, scalability, and risk anticipation. The proposal outlines a modular architecture, identifies technical challenges and mitigation strategies, and presents use cases for different user profiles. Ethical, legal, and environmental implications of digitalisation are also discussed. This conceptual work supports future experimental validation and highlights the potential of digital transformation to enhance compliance with the Common Agricultural Policy and align with the European Green Deal priorities.
Descrição
Palavras-chave
Agricultural audit management Geospatial data integration Internet of things Predictive analytics
Contexto Educativo
Citação
Correia, Maria Patrocínia; Alves, Joaquim; Sequeira, Romeu; Exposto, José (2025) Enhancing agricultural audit systems with IoT and predictive analytics: deployment and performance. International Conference on Application of Information and Communication Technologies. p. 1-6. ISBN 979-833159342-1. DOI: 10.1109/67988.2025.11268564
Editora
IEEE