A Flower Status Tracker and Self Irrigation System (FloTIS)

Rumeysa KESKİN | Furkan GÜNEY | M. Erdal ÖZBEK

The Internet of Things (IoT) provides solutions to many daily life problems. Smartphones with user-friendly applications make use of artificial intelligence solutions offered by deep learning techniques. In this work, we provide a sustainable solution to automatically monitor and control the irrigation process for detected flowers by combining deep learning and IoT techniques. The proposed flower status tracker and self-irrigation system (FloTIS) is implemented using a cloud-based server and an Android-based application to control the status of the flower which is being monitored by the local ...Daha fazlası