Towards Sustainable Agriculture Management: IoT-Enabled Greenhouse Monitoring and Regulation System for Year-Round Crop Cultivation
Keywords:
Forensic Anthropology Cases. Forensic Anthropology Laboratory Identification. UruguayAbstract
The research focuses on the adaptation of greenhouses for farming, emphasising its positive feedback as a feasible and sustainable option for year-round crop cultivation. The research involves a system that utilises sensors connected to a microcontroller to monitor greenhouse conditions. The sensors measure temperature, humidity, soil moisture, light intensity, and water levels. The system is powered by AC to DC supply, with additional features like a fan to cool the environment and a bulb responding to natural light intensity. The collected data is sent to a webpage for remote monitoring through the Serial Peripheral Interface Flash File System (SPIFFS). The study encompasses two main aspects: sensing and regulation, and transmitting real-time data for remote monitoring.
References
Agilesh Saravanan, et al. (2023) IoT-Based Greenhouse Monitoring. 39-45.
Anon. (2020) ESP32 - DevKitC. www.components101.com/microcontrollers/esp32-devkitc
Anon. (2021) DHT11 Temperature and Humidity Sensor. www.components101.com/sensors/dht11-temperature-sensor
Xiaofeng Bo (2023) Design of remote intelligence monitoring system based on LabVIEW for the greenhouse. 385-392.
Yan Chen, et al. (2022) Design of remote monitoring system for greenhouse environment. 515-522.
Anita Chemura, Benedikt Schauberger, Christoph Gornott (2020) Impacts of climate change on agro-climatic suitability of major food crops in Ghana. 15(6), e0234789.
P.Q. Craufurd, T.R. Wheeler (2009) Climate change and the flowering time of annual crops. 60(9), 2529-2539.
J. Doshi, T. Patel, S. Kumar Bharti (2019) Smart Farming using IoT, a solution for optimally monitoring farming conditions. 160, 746-751.
Michal Babiuch, Petr Foltýnek, Pavel Smutný (2019) Using the ESP32 microcontroller for data processing. 1-6.
Ricardo K. Gallardo, Johanna Sauer (2018) Adoption of labor-saving technologies in agriculture. 10(1), 185-206.
D. Ibrahim (2006) Microcontroller based applied digital control. 314.
R.K. Kodali, V. Jain, S. Karagwal (2016) IoT based smart greenhouse. 1-6.
Christos Maraveas (2022) Incorporating artificial intelligence technology in smart greenhouses: Current state of the art. 13(1), 14. https://doi.org/10.3390/app13010014
Ahmed Mellit, et al. (2021) Design of a novel remote monitoring system for smart greenhouses using the Internet of things and deep convolutional neural networks. 14(16), 5045. https://doi.org/10.3390/en14165045
M. C. Moreno, L. D. Quintero, N. A. Torres (2023) Automated Monitoring and Control System for Greenhouses Using Modern Speech Processing Through Mathematical-Based Methods. 35-40.
G. Nicolosi, R. Volpe, A. Messineo (2017) An innovative adaptive control system to regulate microclimatic conditions in a greenhouse. 10(5), p.722.
S. Pallavi, J.D. Mallapur, K.Y. Bendigeri (2017) Remote sensing and controlling of greenhouse agriculture parameters based on IoT. 44-48.
A.C. Pusatkar, V.S. Gulhane (2016) Implementation of wireless sensor network for real time monitoring of agriculture. 3(5), p.5.
R. Rayhana, G. Xiao, Z. Liu (2020) Internet of things empowered smart greenhouse farming. 4(3), 195-211.
R. Shamshiri, F. Kalantari, K.C. Ting, K.R. Thorp, I.A. Hameed, C. Weltzien, D. Ahmad, Z.M. Shad (2018) Advances in greenhouse automation and controlled environment agriculture. A transition to plant factories and urban agriculture. 11(1), 1-22.
P. Singh, S. Saikia (2016) Arduino-based smart irrigation using water flow sensor, soil moisture sensor, temperature sensor and ESP8266 WiFi module. 1-4.
A. V. Starikov, A. A. Gribanov, A. A. Starikova (2022) Automation of combined irrigation system control in greenhouses with electrochemically activated water.
A.L. Virk, M.A. Noor, S. Fiaz, S. Hussain, H.A. Hussain, M. Rehman, M. Ahsan, W. Ma (2020) Smart farming: An overview. 191-201.
M. Zhu, J. Shang (2022) Remote Monitoring and Management System of Intelligent Agriculture under the Internet of Things and Deep Learning. p. 13.
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