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SMART: Sustainable Management of Agriculture with the Intelligent Computing Continuum

Grant number:24/15527-9
Support Opportunities:Research Program on Global Climate Change - Thematic Grants
Start date: January 01, 2025
End date: December 31, 2027
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computer Systems
Agreement: National Natural Science Foundation of China (NSFC)
Principal Investigator:Carlos Alberto Kamienski
Grantee:Carlos Alberto Kamienski
Principal researcher abroad:Lei Xue
Institution abroad: Sun Yat-Sen University , China
Host Institution: Centro de Matemática, Computação e Cognição (CMCC). Universidade Federal do ABC (UFABC). Santo André , SP, Brazil
City of the host institution:Santo André
Principal investigatorsLuís Henrique Bassoi ; Reinaldo Augusto da Costa Bianchi ; Ronaldo Cristiano Prati
Associated researchers:André Torre Neto ; Carlos Manoel Pedro Vaz ; Dener Edson Ottolini Guedes da Silva ; Ednaldo José Ferreira ; Eduardo Antonio Speranza ; Fabíola Martins Campos de Oliveira Genari ; Gabriela Oliveira Biondi ; João Henrique Kleinschmidt ; Juliana Polizel ; Ladislau Marcelino Rabello ; Luiz Fernando Bittencourt ; Paulo Sergio de Paula Herrmann Junior ; Ronaldo Cristiano Prati
Associated scholarship(s):25/25634-0 - Integrating Deep Learning into Smart Farming, BP.TT
25/11944-7 - Desenvolvendo o Continuum Inteligente de IoT para Agricultura de Precisão: Alocação de Tarefas, Previsão, Gestão de Recursos e Análise de Dados, BP.PD
25/11943-0 - Smart Application Deployment for the IoT Computing Continuum, BP.PD

Abstract

Food security remains a significant global concern, particularly in large countries like Brazil and China. Modern agriculture faces the dual challenge of increasing crop productivity while ensuring environmental sustainability amid climate change. Precise and smart agriculture management is crucial, leveraging technologies like IoT, 5G/6G, and AI to enhance decision-making, reduce resource usage, and minimize environmental impact. Innovative agriculture applications generate vast amounts of data from IoT sensors and remote sensing. However, the distributed nature of real-world infrastructures complicates data management. This is where the IoT Computing Continuum, which includes sensors, edge computing nodes, and cloud datacenters, comes into play. It handles the end-to-end data flow, a complex task that requires innovative solutions. Yet, ensuring a reliable dataflow for sophisticated models that enhance precision, food security, and environmental protection remains challenging. The SMART project aims to develop and deploy trustworthy platforms across the IoT computing continuum, from field sensors to the cloud. It will utilize various sensors, data sources, networking technologies, data management, and machine learning to ensure reliable dataflow and trustworthiness. The project will be piloted in Brazil and China, focusing on coffee and wheat crops. It will emphasize smart irrigation and fertilization to reduce water and fertilizer usage. This approach aims to contribute to sustainability goals and address the challenges of climate change. (AU)

Articles published in Agência FAPESP Newsletter about the research grant:
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Articles published in other media outlets ( ):
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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
RIBEIRO JUNIOR, FRANKLIN MAGALHAES; BIANCHI, REINALDO A. C.; KAMIENSKI, CARLOS A.. IoT-Beeps: IoT Behavior Perception System. ANNALS OF TELECOMMUNICATIONS, v. N/A, p. 20-pg., . (24/15527-9)