Created by four University of Chicago students, Amo is an innovative solution designed to help plant owners monitor and maintain the health of their houseplants. The system uses a Raspberry Pi package equipped with a camera and sensors to collect data on plant leaves, soil temperature, and moisture levels. By leveraging a ResNet-9 model, Amo identifies the plant species and detects diseases based on leaf images. This information is combined with real-time temperature and moisture data to dynamically adjust care recommendations for each plant. The system offers a user-friendly interface with color-coded alerts, providing actionable insights to ensure plants receive proper care. Amo is a mobile and self-contained system that can be used without an internet connection, making it a practical and accessible tool for improving plant care.