This project is solving the Leaf Me Alone challenge. Description
The Mobile App allows you to take a leaf's photo. Then the app gives an ID and requires a user to fill a form which includes:
- Crop name
- Dropped Leaf?
- Zone: Urban or Rural?
Moreover the app automatically adds the date, time and GPS location. Finally it sends the data to the Web Server which analyses and responds with:
- % Ozone injury
- % Holes in the leaf ( only if the user want to know)
- % Total Injury
- Classification (based on ozone-induced foliar injury field guide).
Notes: Android compatible app
The Web displays the data of all users using pins on a simple map. You can click a specific pin and gets access to discoverer the photo and the data of every survey. Also it shows a historic survey's data and let you filter by: date, zone, crop name, etc.
In addition, a server was employed to support the mobile and web app.. The server interacts with an image processing algorithm that was written in Octave software. The algorithm separates the channels and operates them based on the difference of light reflectance on the leaf. First, it identifies the leaf, calculates the area and computes the percent of ozone injury. Also, it determinates: the presence of black dots, brown dots and holes on the leaf.
The server needs: - Octave 3.8 and libraries (general-1.3.4.tar.gz / control-2.8.0.tar.gz / signal-1.3.1.tar.gz / image-2.2.2.tar.gz)
Web & App Download:
License: Apache License 2.0 (Apache-2.0)
Source Code/Project URL: https://github.com/jmorocho/DropiAlone
Web & App Download - http://dropialone.epn.edu.ec/
Presentation - https://prezi.com/wclwe9kxibvu/space-apps-dropialone/
Octave - https://www.gnu.org/software/octave/
Video Link 1 - https://youtu.be/BMd8HqZpFjc
Video Link 2 - https://vimeo.com/125416591