Agriculture and AI

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Today let's go for a long drive with car of words to the field where AI is helping in Agriculture

Photo by Isak Engström on Unsplash


Some 30 years ago world population was around 5.5 billion .Today it's over 7.9 billion , and as per UN it will touch 9.3 billion  and to feed these humongous population  we will need to produce 60% more food .

But current techniques of farming won't be able to cater the desired need ,not even close to suggested numbers. Thus we have no choice but to rely on Artificial Intelligence for scalability as well as efficiency.

                                        




1. Tackling labor challenge:
    It is evident that today less people are entering farming profession so there is shortage of workforce        in this area. This labor shortage can be curbed by AI based agribots,small tractors ,which can                augment the labor workforce and other activities.This bots can harvest the crops at higher volume         than labors ,eliminate weeds ,accurately identify and discard weeds and can work round the clock.

2. Crop yield prediction:
    Farms produce a huge amount of real time data on daily basis such as weather conditions,temperature     ,soil moisture content ,water usage etc.  Using  Machine learning ,branch of AI one can analyze this        data properly and can determine patterns, correlation  and   come up with insights which can help             farmers optimize planning their  crop choice for more yields  and utilize resources in proper way. 

3. Disease Diagnosis:
    Different AI techniques like Convolution Neural Networks,Artificial Neural Network and Deep            Learning have been successfully used to detect diseases in various crops such as rice,wheat ,maize        etc simply on basis of the images. Early detection of disease can help preventing spreading of disease     to larger portion of crops and save the yield.

4. Intelligent spraying and pest management:
    Using sensors ,AI can detect various weeds affected , disease infected areas and then accurately spray      herbicides/pesticides in that particular region so that overuse of chemicals can be avoided and                 improve yield.

5. Monitoring Livestock's health:
    Monitoring vital signs,food intake and daily activities can help to ensure and have a check on                livestock's health . In many farms who rely on  livestocks , using AI  can help to  keep an eye on             milk yield ,disease ,temperature ,body movements(resting,lying and sleeping) and food intake                composition of each livestock.

6. Crop and Soil monitoring:
    Different sensors recording moisture content of soil,humidity in air ,temperature and climate                condition can be feed to ML based model to automate amount of water needed to the soil without            intervention of human labor. This can help reduce overuse of water and maintain crop as well as soil       health

References:
  • https://www.forbes.com/sites/louiscolumbus/2021/02/17/10-ways-ai-has-the-potential-to-improve-agriculture-in-2021/?sh=57b63d627f3b
  • https://www.wipro.com/holmes/towards-future-farming-how-artificial-intelligence-is-transforming-the-agriculture-industry/#:~:text=AI%20systems%20are%20helping%20to,to%20apply%20within%20the%20region.
  • https://www.forbes.com/sites/cognitiveworld/2019/07/05/how-ai-is-transforming-agriculture/?sh=771367094ad1

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