Uso da internet das coisas no monitoramento da alface hidropônica em ambiente controlado

Abstract

Urban agriculture, through hydroponic cultivation, is an increasingly relevant alternative for dealing with the challenges of producing and feeding the population. In this context, hydroponic cultivation in a controlled environment with the help of technological tools in vertical urban farms is a promising option for guaranteeing a sustainable and efficient food supply. The main objective of this study was to evaluate the use of artificial intelligence (AI) in monitoring hydroponic lettuce in an indoor environment. To do this, sensors were used to collect data on the plants and the environment; this data was interpreted by machine learning algorithms to support decisions in real time. The automation consists of a set of devices integrated with the Arduino [trade mark] platform and monitoring software. A prototype was built in a greenhouse to simulate a real production environment. The results showed that, working with an average nutrient solution temperature of 28.6ºC, lettuce plants with up to 13 leaves and a weight of 200g were obtained, demonstrating the viability of hydroponic automation and the potential of artificial intelligence for monitoring and efficient food production in controlled environments.