Plantonome: A Cross-Platform Application for Precision Agriculture

¹ Laboratory of Advanced Systems Engineering, National School of Applied Sciences, Ibn Tofail University, Kenitra 14000, Morocco
² Department of Electrical Engineering, Mohammadia School of Engineers, Mohamed V University, Rabat, Morocco

^* e-mail: anass.deroussi@uit.ac.ma
^** e-mail: abdessalam.aitmadi@uit.ac.ma
^*** e-mail: imam.alihamidi@uit.ac.ma
^**** e-mail: zakaria.chabou@uit.ac.ma
^† e-mail: adnane.addaim@uit.ac.ma

Abstract

In recent years, there has been growing interest in leveraging the Internet of Things (IoT) and Artificial Intelligence (AI) technologies for agriculture. A significant challenge for developers in this field is creating applications that provide precise data about plants, facilitating the smart automation of plant management.

This paper presents Plantonome, an open-source application developed using the Flutter software development kit (SDK) and the Dart programming language. Designed to integrate with IoT devices, Plantonome quickly and accurately identifies ornamental plant genera or species using the Plant.id API for plant image analysis. The application also utilizes a NoSQL database for storing user data and plant preferences, and it includes a dataset of ornamental plants with details such as name, brightness, temperature, and humidity requirements. The development approach outlined in this paper accelerates the creation process and results in a high-performing application with a flexible user interface and smooth user experience. The application, tested on Android 5.0 (API level 21) or higher, achieved an accuracy of 94.64% for plant identification and received highly positive feedback regarding its functionality, usability, and efficiency. This work offers significant benefits to researchers and startups aiming to develop cross-platform applications that can automate various agricultural tasks, contributing to advancements in smart agriculture.