How Artificial Intelligence and Machine Learning Can Help In Agriculture

Artificial Intelligence is growing at a rapid pace. With advances in computational capabilities and increased cloud penetration, wider parts of the world economies have started to reap the benefits of Artificial Intelligence. (Machine Learning)

Agriculture is a field that has started to leverage AI for its benefits. Be it containing weeds, calculating the best time to harvest crops, Monitoring the health of soil and crops, or predicting the yield in advance.

Be it small farmers or Large corporations having a vast amount of land AI has something to offer to everyone.

Pests have always plagued farmers. Some ten thousand years after the invention of agriculture, locusts, grasshoppers, and other crop devouring insects still eat profits and gobble grains that would otherwise feed human beings. But AI gives growers a weapon against cereal-hungry bugs.

Not long ago, a farmer in Texas checked the direction of the wind and reckoned a swarm of grasshoppers was likely to descend on the southwest corner of his farm. But before he could check his crops, the farmer got an alert on his smartphone from the AI and data company he hires to help monitor his farm.

Checking new satellite images against pictures of the same parcel over a five-year period, an AI algorithm detected that the insects had landed in another corner of the farmer’s field. The farmer inspected the section, confirmed the warning was accurate, and removed the costly pests from his field of nearly ripened corn.

Artificial intelligence holds the promise of driving an agricultural revolution at a time when the world must produce more food using fewer resources. The future of agriculture and humanity is in safe hands with Artificial Intelligence.

TagX helps companies developing Artificial Intelligence solutions for Agriculture in Labeling their data collected from sensors, drones, and vehicles. TagX can segment machinery, crops, and humans in drone imagery, Tag sensor data or create synthetic datasets for testing sensors and also create solutions to monitor prices of different crops in real-time.

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