With ongoing growth for human population on Earth, food security became a real critical problem. Many spots on Earth land are suffering poverty food starvation and lack of essential food supplements. Using image processing, data manipulation and prediction, FoodEx, a map web based application, will provide dynamic data stream for all crops analyzing the patterns of Green, Yellow and Blue. In addition, FoodEx aims to reach a self sufficient world through using it's tool in worldwide contribution.

This project is solving the Food Directions challenge.


With continuous growth for human population on Earth, food security became a real critical problem. Many spots on Earth are suffering poverty food starvation and lack of essential food supplements. Although humans on Earth through last decade have made a huge progress in communication, electronics and technology, we are still suffering lack of essential needs to just survive. FAO is pushing data to achieve as much food security as possible but sometimes the problem is the info accessibility and usability. Here, we are putting all technological advances in action to achieve that goal.
Using data acquisition, image processing, predictions and NASA's imagery satellites, FoodEx will provide dynamic data streams (on a map) for all green spots on earth, showing the areas used for agriculture, the desert areas and the water areas. The dynamic day-by-day monitoring for lands will show the increase/decrease of green spots on earth, the utilization and usage of each spot. Using updates from FAO and NASA, solid and accurate live data about food security and dynamic changes happens to our Earth are being updated. FoodEx is designed with two main functionalities/modes in mind:

1- Horizon Mode

2- Greenify Mode

The Over the Horizon/Horizon Pro mode is where you are accessing all the data you need from a map interface. You choose your country of choice and you have endless statistics right in front of you. This data is categorized and shown either on infographics and graphs or by hovering your mouse over an area. The key here is data, you have lots and lots of data and you use them in the favor of the user. Some image processing is being used in order to identify the three color patterns Green (Crops and Plants), Yellow (Deserts), and Blue(Water).

The Greenify mode is where you take things to the next level and start editing the maps you already have. So the steps are as follows:

-You choose an area that is a desert (yellow) -You choose a polygon shape over this desert -According to arability of land you are to choose a crop and plant it over that area

Accordingly, you get updated maps statistics based on your own edits. You get details about, for example, the production rate, the harvesting season, the profit per year, and more and more statistics (that could be derived through long equations) that affect the economy and can show real predictions of how country food direction and self sufficiency percentage could be altered.

One section of our web application is what's so called a Green Explorer, a sub section of CitiAct. We have current world challenge going on that are listed on our website and rated according to severity and urgency, and the role of a Green Explorer (general audience) is to help find a solution. A Green Explorer is required to submit a contribution, where he/she does some edits on the map of the country facing the challenge and finds a pattern that would positively lower the risk of that challenge. The user's contribution is submitted online for everyone to review (likes, comments, economists reviews) and the contribution that receive the most interactions gets featured on our main page. This idea will drive the public to be part of the solution, just from the leisure of their homes and laptops. In addition, it will also offer investors with ready well prepared predictions driving them to take action.

Project Information

License: GNU General Public License version 2.0 (GPL-2.0)

Source Code/Project URL:



  • Waleed Abdou
  • M.Gehad Diab
  • Eslam Saad
  • Mohamed Ibrahim
  • Waleed Abdou
  • Mohamed El Sharif