Impactul tehnologiilor “smart agriculture” asupra eficienței economice
The impact of “smart agriculture” technologies on economic efficiency

Summary/Abstract: The paper examines the impact of integrating smart technologies on the economic efficiency and sustainability of modern agriculture. It aims to evaluate the performance of IoT systems and machine learning algorithms in optimizing resource use. The study relies on a thorough review of the scientific literature and a comparison of recent experimental research in precision agriculture. The data come from experiments carried out in greenhouses and real agricultural farms, where parameters such as soil moisture, temperature, air humidity, and light intensity were collected using digital sensors connected through LoRa and WiFi networks. Data processing was performed using XGBoost and Model Predictive Control models, and performance was assessed through statistical indicators such as the coefficient of determination R² and the root mean square error RMSE. The results show water consumption reductions of up to 20 to 30 percent compared to traditional irrigation methods, lower energy costs in greenhouses through consumption oriented automation, and a transmission reliability rate of 99.98 percent in a case study conducted on a 1.3 hectare vineyard in Spain. The comparative analysis indicates that implementing a monitoring node based on ESP32 costs around 300 EUR, significantly less than commercial solutions priced between 1500 and 2500 EUR, which allows the investment to be recovered in less than two agricultural seasons. The study shows that integrating sensors, wireless communications, and artificial intelligence turns farm management into a data driven process, with a direct impact on reducing waste, stabilizing production, and increasing farm profitability.

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