Abstract
This study proposes an agricultural management system designed to enhance productivity by leveraging artificial intelligence and Internet of Things (IoT) technologies. It addresses the complex microclimate conditions within greenhouses by integrating microcontrollers and sensors to monitor parameters such as temperature, humidity, and soil moisture, enabling precise environmental management. Web and mobile applications provide interactive interfaces, allowing users to monitor real-time factors influencing the greenhouse environment. The system can execute actions like activating fans or irrigation pumps based on user inputs or predefined settings. In addition to improving yields, the system aims to create a dataset that can be used for assessing the effectiveness of future machine learning models. Important considerations include data privacy, training farmers to effectively use the technology, and integrating the system with traditional farming practices, thereby enhancing sustainability. Overall, this study aspires to continuously improve agricultural practices by combining modern technology with traditional knowledge, ultimately aiming for a more efficient and sustainable agricultural landscape.
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