I2WAC: A Proposal for Irrigation Management Exploring Situational Science at IoT
Abstract
According to the National Water Agency (ANA), approximately 46.2% of all clean water used in Brazil is destined for irrigation, which has been motivating the evaluation of alternatives for water supply agricultural crops. Considering this scenario, this article presents the I 2 WAC proposal, which aims to explore Situation Awareness in the decision making process, with the perspective of minimizing socioenvironmental impacts. For evaluation of I 2 WAC a prototype was developed that integrates open-source IoT technologies to the EXEHDA middleware and explores a weather prediction service. The results achieved were promising, reaching a success rate of approximately 94% regarding the irrigation decision.
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Erthal, E. S. and Berticilli, R. (2018). Sustentabilidade: Agricultura irrigada e seus im- pactos ambientais. CIÊNCIA & TECNOLOGIA, 2(1):64–74.
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Imteaj, A., Rahman, T., Hossain, M. K., and Zaman, S. (2016). Iot based autonomous percipient irrigation system using raspberry pi. In 2016 19th International Conference on Computer and Information Technology (ICCIT), pages 563–568. IEEE.
Joslyn, S., Nadav-Greenberg, L., and Nichols, R. M. (2009). Probability of precipitation: Assessment and enhancement of end-user understanding. Bulletin of the American Meteorological Society, 90(2):185–194.
Kamienski, C., Soininen, J.-P., Taumberger, M., Fernandes, S., Toscano, A., Cinotti, T. S., Maia, R. F., and Neto, A. T. (2018). Swamp: an iot-based smart water management platform for precision irrigation in agriculture. In 2018 Global Internet of Things Summit (GIoTS), pages 1–6. IEEE.
Koduru, S., Padala, V. G. D. P. R., and Padala, P. (2019). Proceedings of 2nd International Conference on Communication, Computing and Networking, volume 46.
Kumar, A., Surendra, A., Mohan, H., Valliappan, K. M., and Kirthika, N. Internet of things based smart irrigation using regression algorithm. In International Conference on Intelligent Computing, Instrumentation and Control Technologies.
Lopes, J. L., de Souza, R. S., Geyer, C., da Costa, C., Barbosa, J., Pernas, A. M., and Yamin, A. (2014). A middleware architecture for dynamic adaptation in ubiquitous computing. Journal of Universal Compuerter Science, 20(9):1327–1351.
MCU, N. (2018). Node mcu [online]. Último acesso 15 Dezembro 2018
Micropython (2018). Micropython [online]. Último acesso 2 Dezembro 2018.
PENTEADO, S. R. (2010). Manejo da Água e irrigação – em propriedades ecológicas. Via Orgânica.
Perera, C., Zaslavsky, A., Christen, P., and Georgakopoulos, D. (2014). Context aware computing for the internet of things: A survey. Communications Surveys Tutorials, IEEE, 16(1):414–454.
Picoweb (2018). Picoweb [online]. Último acesso 3 Dezembro 2018.
Raspberry (2018). Raspberry [online]. Último acesso 15 Dezembro 2018
Sezer, O. B., Dogdu, E., and Ozbayoglu, A. M. (2018). Context-aware computing, le- arning, and big data in internet of things: a survey. IEEE Internet of Things Journal, 5(1):1–27.
Souza, R., Lopes, J., Geyer, C., Cardozo, A., Yamin, A., and Barbosa, J. (2018). An archi- tecture for iot management targeted to context awareness of ubiquitous applications. Journal of Universal Computer Science, 24(10):1452–1471.
Published
2019-07-09
How to Cite
ALBANDES, Rogério; MACHADO, Roger; LOPES, João; PERNAS, Ana Marilza; YAMIN, Adenauer.
I2WAC: A Proposal for Irrigation Management Exploring Situational Science at IoT. In: INTEGRATED SOFTWARE AND HARDWARE SEMINAR (SEMISH), 46. , 2019, Belém.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2019
.
p. 101-112.
ISSN 2595-6205.
DOI: https://doi.org/10.5753/semish.2019.6571.
