FEATURE : AGRICULTURE
transformation to provide high accuracy and diagnosis of agronomic information .
These algorithms utilize neural networks and deep learning to predict and provide actionable insights that drive value to the farmer so they can make the most optimal decisions .
Applying farming tech elsewhere
While the application of cloud technologies on farms looks different than it would anywhere else , the technology itself is extremely applicable .
Connectivity , IoT devices and data management give farmers the ability to operate in harsh environments – which is something that can be impactful in many other industries .
Whether it ’ s manufacturing , supply chain or fleet management , all these industries rely on time , cost efficiency and resource optimization – things that are possible with the technologies being applied in farming and beyond .
In the same way farmers use precision technology to improve their operations , other industries have the opportunity to do the same .
Specific examples include :
• Similar to how farming uses precision farming to place an exact number of seeds on a sub-inch area of a farm , manufacturing uses precision welding , which involves placing the exact number of welds on the exact spot of the material .
• In the same way farmers use GPS connectivity and vehicle tracking technology to know where farm equipment is at any given moment , industries like car services ( Uber , Lyft ), trucking , warehouse management and construction use similar precision technology to track things like the location , condition , and the state of the goods that are being carried .
Embracing the challenges
Similar to the implementation of any new technology , there have been challenges and barriers along the way as the farming industry has adopted these practices .
The main challenges include a lack of standardization regarding cloud technology across the industry , as well as all the uncontrollable factors that come with farming . While these challenges remain , they have also shaped farmers into leaders in digital transformation .
By facing these obstacles , pivoting and adapting , the lessons learned in agriculture can be extremely beneficial as leaders in other industries look for guidance on implementing similar technologies .
• In healthcare – the same type of technology used in precision farming like sensors , IoT , communications , data aggregation and alerting platforms – are utilized to deliver real-time monitoring , assessment and visualizations of seniors who are aging in their homes without constant medical supervision .
There is tremendous potential to expand possibilities and the digital transformation in farming is just the start .
With more widespread adoption of cloud technology across industries , long-term sustainability and datadriven innovation will grow exponentially . p
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