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Due to the increasing complexity and increasing data challenges, it is getting impossible to harness agricultural data manually in the traditional way.

From climate change to global warming, there are increasingly new threats to the agricultural industry together with the ever-increasing demand for food by the exponentially increasing population.

Farmers more than ever are being forced to look for new ways to produce more food with scarce resources.

To overcome these challenges the agriculture industry must evolve.

Artificial intelligence gives great new insights into doing so.

How Artificial intelligence in agriculture can change farming for the better

It can give the best technological predictions about the best crops to grow using both the new and pre-existing data from your farm and other external factors like the weather reports.

Not only this but artificial intelligence can recognize pest diseases and help in fighting them faster.

Using artificial intelligence in agriculture farmers, even the ones who own a small business will be able to connect with vendors across the globe easily.

Data will be collected from each field in the most time-efficient manner to provide the farmers with a detailed in-depth analysis that can help them have an unprecedented view of their crops.

Using the latest technology like edge computing, they will be able to lower the cost of field oversight and accelerate the response to potential threats like pests, heavy rainfall, or dust storms.

Not only will artificial intelligence highlight in-efficiencies in the pre-existing system (which in some countries is failing to meet the demands of the growing population) but will also give great new insights about how these challenges can be overcome.

Virtual and mixed reality will be great new tools to generate a complete view of the farm hence offering great insights regarding planting zones and soil quality.

Robotics will ease the jobs of manual labor and will open new opportunities of how and where crops can be produced especially in the areas that were hard for humans to cultivate.

This will allow growers to do more with far lesser resources but will also guarantee quality. 

The scope of artificial intelligence includes growth-driven crops by cognitive IoT which includes imaging, proximity sensing, remote sensing, and soil testing.

Artificial intelligence will be able to understand, store and learn a huge amount of data, thereby responding to it to improve efficiency.

Using cognitive IoT, AI can analyze the data to give great insights to improve the yield of the crops.

Proximity sensing and remote sensing can play a vital role in collecting intelligent high-resolution data.

For example, this data can be used for soil testing.

This can help in soil characterization of soil below the surface of a particular place.

Hardware solutions available in the market are being paired with data collecting software with robotics to prepare the best fertilizer for the particular fields to maximize the output.

In precision farming, images taken by drones can help the farmers to get in-depth crop monitoring, scanning of the field, and so on.

Computer vision technology, data from drones, and IoT alerts are combined and analyzed to give accelerated alerts concurrently to improve precision farming.

The images collected by these drones for example of leaves are divided into zones like background, non-diseases part, and diseased part to detect crop disease more efficiently.

The diseased part can then be cropped and sent for laboratory investigations.

This technology can also help identify pests, nutrients diseases, and more.

Crop readiness identification is another great tool that uses artificial intelligence.

By taking multiple images of different crops in white UVA light, farmers can predict how ripe the fruits are.

This can help the farmers sort the fruit out in stacks of different levels of readiness before sending them to the market.

Field management using high-quality images from systems like drones and copters enables real-time predictions.

These predictions are made during the time of cultivation by creating feed maps, field maps and identifying areas where crops require more or less water, fertilizers, or pesticides.

This is a great way to optimize resources on a large scale.

Cognitive solutions give farmers great insights into the condition of the soil, weather predictions, kinds of seeds, and infestation in a particular area.

These recommendations can also be tailor-made to the farm’s requirements and the other feature such as the local weather.

An external crisis like marketplace trends and consumer needs are also provided by the solution to optimize the crops as much as possible.

This technology is a great way to monitor crops across their life cycle.

It can easily generate reports in case of MLM anomalies.

Labor-intensive processes such as irrigation can be done more efficiently, automatedly.

Machines can learn historical weather patterns and soil quality to give great insights to increase the overall yield.

Precision farming provides more accurate and in-control techniques that can replace the repetitive and human-intensive part of farming such as high precision positioning systems, automated steering systems, geo-mapping, sensor, and remote sensing, and integrated electronic communication.

It also guides the farmers about crop rotation, profitability, efficiency, and sustainability.

 

Top Artificial Intelligence in Agriculture applications being used

Some of the top AI applications in agriculture include:

  • Fasal
  • Intelair
  • FarmWise
  • rootAI
  • OneSoil
  • AGEYE technologies
  • Blue River technology
  • Earth Sense agricultural intelligence.

Agriculture ERP system

Many agriculture industries also use ERP systems for their business.

ERP system can provide you with a unique holistic solution for all your agricultural needs.

There are several solutions available in the market however the Folio3 provides you with the best solution.

Agriculture ERP software by Folio3 uses the best business practices and is supported by the key method of contemporary ERP systems, Microsoft Dynamics allows you to enhance the potency and accuracy on an operational level whereas still managing the efficient allocation of resources in core business activities

Conclusion

Keeping in mind all the challenges the agriculture industry is facing today and will face in the future it’s safe to say it’s never too late to innovate your business and watch it grow to full fruition.

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