AI-Driven Farmers are Changing the Conventions of Agriculture

By CIOReview | Friday, June 21, 2019

Virtual AI-based farmers are making food production faster and easier. Extensive testing and validation of AI applications are continuing in the agricultural sector, with the changing environmental conditions.

FREMONT, CA: Artificial Intelligence holds the promise of driving a revolution in the sector, at a time when the world must produce more food using fewer resources. Natural factors including climate change, population growth and food security concerns are propelling the industry into seeking more advanced approaches to protect and improve crop yield. To this end, AI is slowly emerging as a part of the industry's technological evolution. Some most popular applications of AI in agriculture are discussed below.

• Agricultural Robots

Manufacturers are developing and programming autonomous robots to handle essential agricultural activities, including harvesting crops at a faster pace and higher volume than the human labors. The developed robots can leverage computer vision monitor and precisely prevent weeds on plants, and this can help prevent herbicide resistance. Reports estimate that precision technology eliminates 80% of the volume of chemicals commonly sprayed on crops can reduce herbicide expenditure by 90%. Robotic automation is also emerging to help address the challenges in the labor force. Robots will help farmers to help pick and pack their crops.

Check this out: Top Agricultural Startups

• Monitoring Abilities

Degradation of soil quality and deforestation is posing significant threats to food security and hurt the agricultural economy. Agricultural technology providers are developing deep learning applications that can identify potential defects and nutrient deficiencies in crops and soil. To find this analysis is conducted by software algorithms which integrates foliage patterns with soil defects, plant pests, and various diseases.AI driven image recognition applications are used to identify possible defects through images captured by user's smartphone.

• Predictive Analysis

Companies are using machine learning algorithms in connection with satellites to predict the weather, analyze crop sustainability and evaluate farms for the presence of pests and diseases. High-quality data is updated at a rapid rate continuously, which is accessible for users daily. The amount of data captured by technologies like drones and satellites will give the agricultural industry the ability to predict changes and identify opportunities. 

AI-powered technologies are emerging to help improve efficiency and to address challenges faced by the agricultural sector. The above solutions are going to become highly valued applications of AI in the domain. In such a point, it will be necessary for the farmers to be up to date to ensure technologies are rightly used and helping in improvement.

Few Agricultural Startups: Indigo , AEssenseGrows , AgShift , Grower's Secret