Temperature fluctuations and, in general, climatic conditions can significantly affect the chemical composition of grapes and, in turn, the taste and aromas of wine. At the same time, having a complete climatic mapping of the vineyard is a challenging topic. Traditional solutions are based on using sensors displaced in strategic points of interest. However, in many cases, disseminating a large number of fixed sensors capable of monitoring environmental parameters in a capillary manner is impractical in terms of costs and space constraints. For this reason, some alternative solutions have been envisioned by combining a limited number of sensors and artificial intelligence solutions for building precise predictive models

The collection of micro-climatic information through a mobile robot

Sara Migliorini;Davide Quaglia
2025-01-01

Abstract

Temperature fluctuations and, in general, climatic conditions can significantly affect the chemical composition of grapes and, in turn, the taste and aromas of wine. At the same time, having a complete climatic mapping of the vineyard is a challenging topic. Traditional solutions are based on using sensors displaced in strategic points of interest. However, in many cases, disseminating a large number of fixed sensors capable of monitoring environmental parameters in a capillary manner is impractical in terms of costs and space constraints. For this reason, some alternative solutions have been envisioned by combining a limited number of sensors and artificial intelligence solutions for building precise predictive models
2025
micro-climate mapping, mobile sensors, agricultural robots, recurrent neural network, reinforcement learning, trajectory planning
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1170070
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