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Precision Agriculture

Using Big Data and Drones to feed the next generations: Aileronex AUA-Agro model to monitor agro fields

AUA-Agro

AUA-Agro model can be built based on our basic proprietary air-frame designs as star-mutirotor and glider-catamaran. The basic drone is then modified and equipped with a GPS, a camera and flight wind-stabilizers.

GPS

GPS technology sends a drone to the pre-programmed points and maintains a constant altitude of 25 meters.

Camera

A drone pilot can takes a series of photographs of the agro field below. The aerial images are then downloaded and analyzed to spot where the field needs fertilizers and repair and for other practical applications as a low-cost crop monitoring.

Parameters

It’s powered by a lithium ion polymer battery, can stay aloft from up to 24 hours and can carry five pounds of camera gear. A basic unit costs from $7,000 to $10,000 . Additional equipment, ranging from simple digital cameras to infrared sensors that can detect nutrient deficiencies, can add  to the cost.

Agriculture Use Cases

The drone technology can be used as wide as to detect and combat diseases as “citrus greening” that kills orange trees in Florida, to spot a forest repair needs in Brazil or to control algae pollution  in Taiwan.

Precision Agriculture

To keep up with rising populations, global food production must increase by 70 percent in the next 20 years order to be able to feed the world. The answer to this challenge lies in real time data gathering and analysis for “precision agriculture”.

What is precision agriculture? By collecting and analyzing real-time data on soil, air, crop maturity and weather conditions, the farmers are able to make better decisions. This is known as precision agriculture.

With precision agriculture, data is collected by using robotic drones,  processed in real time and coupled with weather data to help farmers make the best decisions to optimize planting and harvesting. In order to grow crops optimally farmers need to understand how to cultivate the crops in a particular area, taking into account a seed’s resistance to local diseases, and considering the environmental impact of planting a seed. Once the seeds have been planted, the decisions made around fertilizing and maintaining the crops are time-sensitive and heavily influenced by the weather.

Currently, precision agriculture technologies are used by large companies as it requires an IT infrastructure and resources to do the monitoring. However, with drone technology even smaller farms could optimize their own agriculture. A farmer could take a picture of a crop, reading the temperature and humidity from the sensor data and upload it all to a database where an expert could assess the maturity of the crop based on its coloring and other properties with high performance computing, analytic and optimization.