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Smart Farming System Based on IoT for Precision Controlled Greenhouse Management

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Computational Intelligence

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 968))

Abstract

Smart farming with accurate greenhouses needs to be implemented for better farming growth management, and therefore, precision agriculture monitoring in diverse conditions is required. The Internet of Things (IoT) is a new era in computer communication that is gaining traction due to its vast range of applications in project development. The IoT provides individuals with smart and remote approaches, such as smart agriculture, smart environment, smart security, and smart cities. This is the most recent technology that is making things easier these days. The Internet of Things (IoT) has fundamentally expanded remote distance control and the diversity of networked things or devices, which is an intriguing element. The IoT comprises the hardware as well as the Internet connectivity to the real-time application. Sensors, actuators, embedded systems, and an Internet connection are the key components of the Internet of Things. As a result, we are interested in creating a smart farm IoT application. In greenhouse agriculture, this study presented a remote sensing of parameters and control system. The objective is to manage CO2, temperature, soil moisture, humidity, and light, with regulating actions for greenhouse windows/doors dependent on crops being carried out once a quarter throughout the year. The major goal is to properly regulate greenhouse conditions in accordance with plant requirements, in order to enhance output and provide organic farming. The results show that the greenhouse may be controlled remotely for CO2, temperature, soil moisture, humidity, and light, resulting in improved management.

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Correspondence to Manwinder Singh .

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Rokade, A., Singh, M. (2023). Smart Farming System Based on IoT for Precision Controlled Greenhouse Management. In: Shukla, A., Murthy, B.K., Hasteer, N., Van Belle, JP. (eds) Computational Intelligence. Lecture Notes in Electrical Engineering, vol 968. Springer, Singapore. https://doi.org/10.1007/978-981-19-7346-8_37

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