SAVT (Smart Agro Visualization Tool)

GSOC 2017 Project proposal
Javier Calvo García, Liquid Galaxy LAB, Lleida, Spain


SAVT (Smart Agro Visualization Tool)


About me
My name is Javier Calvo García, i’m currently studying fourth grade of the Computer Science degree at
the University of Lleida in the information technologies’s speciality.
I have knowledge of several programming languages such as Python, Java, C, C++, Android, HTML 
or SQL, among others, and I’ve done internships in Liquid Galaxy Lab, collaborating since November 
9th of 2016.


Project description


SAVT will be a software engine to visualize data of crop fields to Liquid Galaxy, allowing you to track
his state.
This image data, collected by drones, planes or satellites, can be among others : vegetation map, 
vigor map, nitrogen map, irrigation sectors, dose of fertilizer and variability map.

We plan to have access also to data collected by drone, and by different IoT (Internet of Things) 
platforms, with sensor arrays on the crop field. We'll also use the platform to visualize this data overlaid
 on the maps and with explanations in almost real time, such as temperature, hygrometry, wind, and 
others upon availability.

The management interface will have the ability to show the analyzed data from a specific client, land or
area.Likewise, it will also be possible to collect data from various sources and import images with their 
coordinates to show them to Liquid Galaxy.

Each crop field will show a pop-up balloon with all the information about it.

The system will have an automatic orbit like 360 degree rotation mode, which will show the crop field 
from all angles by making circles.
The system will also have the ability to make an automatic route of all crop fields, stopping a 
configurable amount of seconds for each one.

Another functionality is the system integration with google assistant using actions SDK to make voice
 requests and having a conversational UI experience.






Linked technologies

In order to deploy the project will be need to use different kind of technologies and know how they work.
 We need the knowledge to communicate between the following platforms. A possible list of software
 needed it could be:

  • Google earth
  • Liquid Galaxy
  • Django
  • Assistant (Actions SDK, Api.AI)

Values for Liquid Galaxy community

  • Enrich the information represented on the Liquid Galaxy.
  • Graphic information of crop fields
  • Make interaction with the represented data.
  • Demonstration mode to show the capabilities of liquid galaxy


Timeline

Before May 4:

  • Learn about Django development, Liquid Galaxy functionalities, Google Earth, Google Assistant
     platform.
May 4- May 30 (Bonding period)
  • Discuss the project details with the assigned mentor.
  • Do a strict definition of how all project parts and features must be implemented.

May 30- June 26 (First working period - Mid term evaluation):
  • Receive and classify crop fields data from drones, planes and satellites
  • Implement conversion to kmz.
  • Develop management tool.

June 26 - July 24 (Second working period )

  • Implement rotation and screen blanker features.
  • Add the pop-up balloon functionality.

July 24 - August 21 (Third working period )

  • Provide Google Assistant functionality to the system.

August 21 - August 29 (Final)

  • Finish documentation