… use of deep learning techniques, … deep learning techniques, to detect diseases in grapevine
plants and achieved over 80% accuracy in this mixed scenario. In summary, a deep learning …

… system of temperature, humidity and water supply, and also early disease monitoring and …
, the tomato greenhouse in Fukushima, Japan. We trained and tested the deep learning model …

… under the eye of monitoring and can destroy the … monitoring process is needed to monitor
the health and type of plants. This chapter proposes an architecture which will help to monitor …

… Using these controllers, we can monitor the crop, and we can control the motor and automatic
drip irrigation. In this research, deep learning algorithms are used to diagnosis the plant …

… approach for implementing a Smart Greenhouse with aspects of monitoring, alerting, efficient
… from camera placed in the greenhouse to evaluate three different deep learning models. …

… , monitoring and predicting a greenhouse is important to allow optimal growth condition for
crops. However, testing the greenhouse … thereby improve the greenhouse environment. This …

… to characterize the growth of greenhouse lettuce. Currently, … method for monitoring the
growth of greenhouse lettuce was … -of-the-art deep learning approach, can directly take images …

… greenhouse monitoring system systematically, serve the data transmission and server processing
subsystems by identifying, listing and further explaining the greenhouse … deep learning…

… In this paper, a novel prototype for remote monitoring of a greenhouse is designed. The … the
Internet of Things and deep learning have showed their capability to monitor the health of the …

… Thereby, the greenhouse is a continuously operating … monitoring the greenhouse
environment. This poses a major challenge in making accurate predictions about the greenhouse …