title_smart-farming

Smart Farming through Intelligent Mobile Machines

Smart farming helps to lead agriculture into a new age through modern information and communication technologies (ICT). The goal is to make food production more efficient and at the same time more sustainable. Intelligent mobile machines and agricultural robots are an important component that can make a major contribution in achieving this goal.

What is Smart Farming?

Data, Data and Data

Smart Farming relies on modern methods of digital data processing. To this end, as much data as possible is recorded, e.g. by intelligent sensor systems, and used for the optimized planning, execution and documentation of operations. The aim is to increase yields while reducing the use of resources. These added values result from coordinated support in decision-making and optimized process execution.

Decision support through smart data linking

For example, the operations carried out are correlated with the agents applied, the prevailing weather and soil conditions, and the resulting yields or growth phases of the fruit. Artificial intelligence is then used to identify correlations and patterns within these data sets and use them as recommendations for action in decision-making.

Support through intelligent assistance functions

Intelligent mobile machines and agricultural robots will also play a very important role in smart farming. This is because the automation of entire operations in agriculture can greatly optimize the efficiency of processes. A first step towards achieving efficiency increases through Smart Farming is already in full swing: Intelligent assistance systems support the execution of work processes with the help of powerful sensors, which can appropriately control the actuators with unprecedented precision and speed. In this way, a higher area output is achieved with optimized quality at the same time. In addition, the driver is much more relaxed when he gets off his mobile machine after work.

Implement automation Vineyard Pilot Assistant

A suitable example here is the Vineyard Pilot Assistant from Braun Maschinenbau. It uses an environment sensor to detect the individual plants and controls the implements for mechanical soil cultivation in viticulture so nimbly and precisely that a doubling of the working speed can be achieved with certain implement combinations. Together with the RowCropPilot assist lane guidance system, the operator is also relieved of steering within the crop rows.

Efficiency increases can already be achieved through smart farming by means of intelligent assistance functions.
The Vineyard Pilot Assistant from Braun Maschinenbau in Landau, Germany, is a good example for the possibilities that Smart Farming offers through assistance functions also in special crops such as viticulture.

Agricultural Robots and Intelligent Mobile Machines in Smart Farming

One step further are (partially) autonomous smart farming systems, which are already technically capable of performing entire operations without user intervention. In addition to sensor data from the vehicle for local navigation (odometry, inertial sensor technology and environmental detection), absolute positioning is also used in many cases with the aid of global navigation satellite systems such as GPS, Galileo, Glonass or Beidou. These can determine the position of the vehicle to within a few centimeters via near-earth satellites.

(Partially) autonomous systems like the sprayer seen here are another step in smart farming.
A NIKO HY-40 (semi-)autonomous tracked vehicle is used to apply crop protection products in the very narrow rows of Burgundy. The operator can monitor the vehicle remotely through the intelligent control system and is thus safe from the chemical pesticides.

Intelligent environment acquisition for automated and continuous data collection

Increasingly, such autonomous work machines or agricultural robots are also equipped with additional sensor technology. As a result, the intelligent system continuously collects further information about the condition of the plantations as it passes through. Classic camera systems with intelligent evaluation based on artificial intelligence are used for this purpose. For example, the system detects and classifies weeds and counts fruits. This is followed by automatic documentation with the degree of ripeness of the individual fruits. In this way, growth monitoring can be realized over time, which, in conjunction with other data, e.g. on fertilization processes or the prevailing weather, allows in-depth statements to be made about the cause and effect of operations.

More and more data obtained with artificial intelligence from environmental sensors, among other things, can be profitably used in smart farming.
Based on data from the environment survey, trees can be counted and mapped, for example, or the area of the foliage wall can be used to implement smart farming crop protection sprayers.

Preventive disease detection through multi- and hyperspectral cameras

Likewise, multi- or hyperspectral cameras allow an insight into the health of the plants. In further operations, for example, proactive treatment with crop protection agents can then take place precisely at the points where a pest infestation has already been detected. This ensures healthier plants that produce a higher yield, while at the same time saving resources. Such methods are currently being investigated in the EU Horizon 2020 research project ATLAS, among others.

The digital driver as the starting point of smart farming

The RowCropPilot from Robot Makers GmbH provides the perfect basis for implementing such smart farming solutions. The application kit, which can be retrofitted by manufacturers on their own production vehicles, brings with it all the technology for autonomous driving in row planted specialty crops. The appropriate intelligent implement automation or sensor detection can be seamlessly integrated on a customer-specific basis.

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