Volume 12, Number 15, September 2022

An Intelligent Community-Driven Mobile Application to Automate the Classification of plants
using Artificial Intelligence and Computer Vision

  Authors

Yifei Tong¹ and Yu Sun², ¹Trinity Grammar School, Australia, ²California State Polytechnic University, USA

  Abstract

How can the efficiency of volunteers be improved in performing bushcare in the limited amount of time able to be spent caring for each location every month [1]?

Bushcare is a volunteer activity with a high difficulty curve for volunteers just starting out as the crucial skill of distinguishing the native plants from the harmful invasive species only comes with experience and memorization [2]. The lack of ability to distinguish targeted plants will greatly reduce the efficiency of the volunteers as they work through the limited amount of time they have at each location each month while also discouraging newly joined volunteers from continuing this activity.

To assist newly joined volunteers, the majority of each would likely be from a younger demographic with a digital app that could help the user distinguish the species of plant, making it easier for them to start familiarizing themselves with both the native and invasive species in their area [3]. The user could simply have to take a picture of the plant they wish to identify and the software would use its image recognition algorithm trained with a database of different species of plants to identify the type of plant and whether it needs to be removed. At the same time, more experienced volunteers could continue to use this app, identifying errors in the app’s identification to make it more reliable.

  Keywords

Flutter, YOLOv5, Computer Vision, Inventory Management.