One of the key challenges of precision agriculture is the development of automated systems that would enable reliable production in natural conditions, where plant growth is affected by a wide range of difficult to control factors such as climate, soil quality and precipitation. As part of the master's thesis, a smart IoT system for automated irrigation of lettuce in soil was developed. The system combines a mathematical evapotranspiration model with soil moisture sensor measurements and precipitation data. An important contribution of the thesis is also the development of a standardized model for evaluating the effectiveness of the system. Existing methods in research papers are often poorly evaluated, which makes it difficult to compare results and transfer findings into practice. An experimental comparison with a commercial solution and a control group showed comparable growth of lettuce with significantly lower water consumption. The research thus demonstrates the practical applicability of the developed system and at the same time offers a methodological framework for future evaluation of similar IoT solutions in precision agriculture.
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