AgrobotiX - Agricultural Sustainability

About Solution

The question is “are today’s agricultural and food systems able to fulfill the need of a population that’s projected to reach 9 billion by mid-century?”. The most optimistic view that it may be able to produce enough food but to do so in an inclusive and sustainable manner requires major transformations.

As we are all creature of habit this may be difficult.

So, we created an AI-based System that uses autonomous drones to collect footage data from the farm, alongside ground sensors for temperature, humidity and NO2 emissions.

Our system -using data from drones and ground sensors of humidity, temperature and Nitrogen emissions alongside machine learning and AI algorithms
enables farmers monitor their crops to identify progress and detect pests and deceases early on. By creating a 3D model of each tree individually we are able to track progress because of the videos from the autonomous drones.

What is breaking through about the project that it can monitor crop progress, weed detection, pests and diseases identification, provides weather prediction and analysis and create an action plan in an optimal way so as not to waste resources or contribute to land degradation. An extra feature is cattle tagging and monitoring to avoid overgrazing.

The system has 3 operation modes:

  • No intervention in decision making where it only provides information.
  • Basic intervention by suggesting action plan.
  • Full autonomy where it takes action controlling irrigation, fertilizing, pesticizing and cultivating.

The system improves its accuracy as it works because of new acquired data and reinforcement learning model.

When we implemented the system in a farm in Algadaref, we yielded a 35% increase in size and oil content of sesame seeds and a 40% increase of gross production of peanuts per acre.

The true cost of the system was 3 dollars per acre. A price worth paying for both quality and quantity.

Despite that the project may deprive workers from their jobs, it creates twice the number of jobs for them directly by training them on operation and maintenance of the system and indirectly by developing rural areas and creating jobs for the community according to the increase of productivity.



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