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Precision Agriculture

Código 16125
Ano 1
Semestre S1
Créditos ECTS 6
Carga Horária PL(15H)/T(30H)/TP(15H)
Área Científica Engenharia e Gestão Industrial
Learning outcomes Upon completion of the course, students will be able to:
1. describe management decisions through the use of precision agriculture techniques.
2. demonstrate the use of artificial intelligence in management decisions.
3. interpret, explain, and apply basic theories and concepts of precision agriculture.
4. demonstrate knowledge of Internet of Things (IoT) tools and devices used.
Syllabus 1. define precision farming
2. introduction to smart farming and its relation with precision agriculture
3. Introduction to IoT tools used to collect data in smart farming
4. Application of drones in the smart agriculture for the precision farming and data collection.
5. Definition of Decision making process
6. Definition of artificial intelligent (AI), Machin learning (ML), and deep learning (DL) and
7. Application of AI, ML, DL in smart farming.
8. Introduction to Tensorflow and Keras
9. Programing of AI algorithms in Python
Main Bibliography 1) Smart Agriculture: An Approach towards Better Agriculture Management : Editor: Prof. Dr. Aqeel-ur-Rehman, OMICS Group,
2) J. Patterson and A. Gibson, Deep Learning: A Practitioner’s Approach. O’Reilly, Beijing, 2017. 12, 16, 51, 52, 53, 58, 73, 82, 83, 86, 98, 124
3) J. Doshi, T. Patel, and S. kumar Bharti, “Smart farming using iot, a solution for optimally monitoring farming conditions,” Procedia Computer Science, vol. 160, pp. 746–751, 2019, the 10th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN-2019) / The 9th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH-2019) / Affiliated Workshops. [Online]. Available: https:
//www.sciencedirect.com/science/article/pii/S1877050919317168 1, 6, 92, 111
4) J. Doshi, T. Patel, and S. kumar Bharti, “Smart farming using iot, a solution for optimally monitoring farming conditions,” Procedia Computer Science, vol. 160, pp. 746–751, 20
Language Portuguese. Tutorial support is available in English.

Regente

Imagem d@ Pedro Miguel de Figueiredo Dinis Oliveira Gaspar [Ficheiro Local]
 Pedro Miguel de Figueiredo Dinis Oliveira Gaspar

Curso

Departamento de Engenharia Electromecânica
Data da última atualização: 2023-01-25
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