Esp8266 module use in animal production: a review
DOI:
https://doi.org/10.13083/reveng.v30i1.15461Keywords:
Digital agriculture, Internet of things, Animal production, Decision makingAbstract
The thermal environment in livestock buildings affects the productive and reproductive performance of animals. Therefore, monitoring thermal environment variables is necessary. This study reviewed the applicability of the electronic device ESP8266 module to monitoring animal production. The ESP8266 module is a microcontroller that enables the collection, storage and transmission of data that influence livestock production. The data collected are transferred to cloud computing systems allowing the development of supervisory systems that can be accessed by smartphones, tablets or computers. With this type of microprocessor, it is possible to develop autonomous management systems for animal production. Connected devices using the internet of things, artificial intelligence, machine learning and blockchain will facilitate the analysis of data from the production chain and the appropriate decision-making. Managers of livestock production systems will be in charge of following up and monitoring the processes.
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Baêta, F., & Souza, C. (2010). Ambiência em Edificações Rurais (2o ed, Vol. 1). Editora UFV.
Becker, C. A., Collier, R. J., & Stone, A. E. (2020). Invited review: Physiological and behavioral effects of heat stress in dairy cows. Journal of Dairy Science, 103(8), 6751-6770.
Burhans, W. S., Rossiter Burhans, C. A., & Baumgard, L. H. (2022). Invited review: Lethal heat stress: The putative pathophysiology of a deadly disorder in dairy cattle. Journal of Dairy Science, 105(5), 3716-3735.
Ceja, J., Renteria, R., Ruelas, R., & Ochoa, G. (2017). Módulo ESP8266 y sus aplicaciones en el internet de las cosas. Revista de Ingeniería Eléctrica, 1(2), 24-36.
Chen, S., Yong, Y., & Ju, X. (2021). Effect of heat stress on growth and production performance of livestock and poultry: Mechanism to prevention. Journal of Thermal Biology, 99, 103019.
Chigwada, J., Mazunga, F., Nyamhere, C., Mazheke, V., & Taruvinga, N. (2022). Remote poultry management system for small to medium scale producers using IoT. Scientific African, 18, e01398.
Espressif Systems. (2022). ESP8266EX Datasheet. https://www.espressif.com/en/subscribe.
Furtado, W. V. dos S., Vaz Júnior, O. A., Veras, A. A. de O., de Sá, P. H. C. G., & Antunes, A. M. (2022). Low-cost automation for artificial drying of cocoa beans: A case study in the Amazon. Drying Technology, 40(1), 42-49.
Garg, L., & Kumar, K. (2021). Application of distributed ledger technology Blockchain in agriculture and allied sector: A review. ~ 215 ~ The Pharma Innovation Journal, 2, 215-221.
Gonzalez-Rivas, P. A., Chauhan, S. S., Ha, M., Fegan, N., Dunshea, F. R., & Warner, R. D. (2020). Effects of heat stress on animal physiology, metabolism, and meat quality: A review. Meat Science, 162, 108025.
Hlaing, W., Thepphaeng, S., Nontaboot, V., Tangsunantham, N., Sangsuwan, T., & Pira, C. (2017). Implementation of WiFi-Based single phase smart meter for internet of things (IoT). 2017 International Electrical Engineering Congress, iEECON 2017.
Hoffmann, G., Herbut, P., Pinto, S., Heinicke, J., Kuhla, B., & Amon, T. (2020). Animal-related, non-invasive indicators for determining heat stress in dairy cows. Biosystems Engineering, 199, 83-96.
Kumar Sai, K. B., Mukherjee, S., & Parveen Sultana, H. (2019). Low Cost IoT Based Air Quality Monitoring Setup Using Arduino and MQ Series Sensors With Dataset Analysis. Procedia Computer Science, 165, 322-327.
Michie, C., Andonovic, I., Davison, C., Hamilton, A., Tachtatzis, C., Jonsson, N., Duthie, C.-A., Bowen, J., & Gilroy, M. (2020). The Internet of Things enhancing animal welfare and farm operational efficiency. Journal of Dairy Research, 87(S1), 20-27.
Nugroho, A. P., Okayasu, T., Hoshi, T., Inoue, E., Hirai, Y., Mitsuoka, M., & Sutiarso, L. (2016). Development of a remote environmental monitoring and control framework for tropical horticulture and verification of its validity under unstable network connection in rural area. Computers and Electronics in Agriculture, 124, 325-339.
Pereira, W. F., Fonseca, L. da S., Putti, F. F., Góes, B. C., & Naves, L. de P. (2020). Environmental monitoring in a poultry farm using an instrument developed with the internet of things concept. Computers and Electronics in Agriculture, 170, 105257.
Polsky, L., & von Keyserlingk, M. A. G. (2017). Invited review: Effects of heat stress on dairy cattle welfare. Journal of Dairy Science, 100(11), 8645-8657.
Rawlins, B., Trevathan, J., & Sattar, A. (2022). Embedded fog models for remote aquatic environmental monitoring. Internet of Things, 20, 100621.
Roth, Z. (2020). Reproductive physiology and endocrinology responses of cows exposed to environmental heat stress - Experiences from the past and lessons for the present. Theriogenology, 155, 150-156.
Ruiz-Ortega, J., Martínez-Rebollar, A., Flores-Prieto, J., & Estrada-Esquivel, H. (2022). Design on a Low Cost IoT Architecture for Greenhouses Monitoring. Computación y Sistemas, 26(1), 221-232.
Shuba, A., Le, A., Alimpertis, E., Gjoka, M., & Markopoulou, A. (2016). AntMonitor: A System for On-Device Mobile Network Monitoring and its Applications.
Sindwani, A., Kumar, A., Gautam, C., Purohit, G., & Tanwar, P. (2020). Prediction and Monitoring of stored food grains health using IoT Enable Nodes. 2020 IEEE International Conference on Computing, Power and Communication Technologies (GUCON), 516-522.
St-Pierre, N. R., Cobanov, B., & Schnitkey, G. (2003). Economic Losses from Heat Stress by US Livestock Industries. Journal of Dairy Science, 86(SUPPL. 1), E52-E77.
Thomazini, D., & Albuquerque, P. U. B. de. (2020). Sensores industriais: fundamentos e aplicações. (Saraiva Educação SA).
Tong, X., Hong, S.-W., & Zhao, L. (2019). CFD modelling of airflow pattern and thermal environment in a commercial manure-belt layer house with tunnel ventilation. Biosystems Engineering, 178, 275-293.
Zhou, L., Qiu, Z., & He, Y. (2020). Application of WeChat Mini-Program and Wi-Fi SoC in Agricultural IoT: A Low-Cost Greenhouse Monitoring System. Transactions of the ASABE, 63(2), 325-337.
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