Sistema centralizado para la gestión, automatización y almacenamiento de datos ambientales para el cultivo de orellana rosada

Abstract

The project addresses the problem of unintegrated management and ineffective control of environmental conditions in Pink Oyster mushroom (Pleurotus djamor) cultivation, particularly in distributed production scenarios. Cultivating this mushroom across multiple distributed units presents significant challenges for accurately monitoring and controlling the environment, which is critical for optimal growth, requiring specific ranges of temperature and relative humidity. Currently, producers typically rely on manual methods or separate tools, which compromises the consistency of key environmental variables. This lack of uniformity can reduce production yields, affect product quality, and limit the ability to scale in a competitive and sustainable manner. There is a clear need for an integrated, user-friendly solution that enables the collection, processing, and visualization of data from multiple cultivation points, facilitating data-driven decision-making and centralized control while respecting the individual needs of each growing unit. To address this need, a distributed client-server architecture is proposed. Each cultivation unit will be equipped with an SBC-based node featuring sensors (for temperature and humidity) and actuators (fans, humidifiers, heaters), communicating via MQTT to a central server. This server, also SBC-based, will function as the MQTT broker, run a web server with a user interface for visualization and control, and manage a database for historical data storage. Furthermore, a Data Storage and Management Module (MSAD) will be integrated to provide backup and reporting functionalities. This functional system is expected to enable real-time monitoring and remote, individualized, and centralized control over environmental conditions across multiple cultivations. This will result in production optimization, improved product quality, and facilitated decision-making based on historical data, thanks to the MSAD capabilities. The system will contribute to reducing human error, ensuring consistency, and freeing the producer from constant manual supervision. In conclusion, the implementation of this system demonstrates the potential of IoT technologies to enhance efficiency and sustainability in small-to-medium scale controlled agriculture. The goal is to offer a practical and well-documented solution that facilitates technological adoption in this specific sector, laying the groundwork for future adaptations in other cultivations with similar environmental requirements and distributed production models.