SAgric-IoT: An IoT-Based Platform and Deep Learning for Greenhouse Monitoring

The Internet of Things (IoT) and convolutional neural networks (CNN) integration is a growing topic interest for researchers as technology that will contribute to transforming agriculture. IoT enable farmers decide act based on data collected from sensor nodes regarding field conditions not purely experience, thus minimizing the wastage supplies (seeds, water, pesticide, fumigants). On other hand, CNN complements monitoring systems with tasks such early detection crop diseases or predicting number consumable resources (water, fertilizers) needed increase productivity. This paper proposes SAgric-IoT, platform precision agriculture, monitor environmental physical variables provide disease while automatically controlling irrigation fertilization in greenhouses. results show SAgric-IoT reliable low packet loss level considerably reduces energy consumption has identification accuracy classification process over 90%.