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Artificial Intelligence in Agriculture- Benefits and Future:
Artificial Intelligence in Agriculture- Benefits and Future:

July 1, 2021

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Artificial Intelligence in Agriculture- Benefits and Future:

"I imagine a world in which AI is going to make us work more productively, live longer, and have cleaner energy." -Fei-Fei Li, Professor of Computer Science at Stanford University

Agriculture has constantly improved with the introduction of various technologies from motorized equipment to biotechnology.Factors such as climate change,food security concerns have propelled the industry into seeking more innovative approaches to protecting and improving crop yield. As a result, AI is steadily emerging as part of the industry’s technological evolution.

AI solved agricultural problems:

AI gathers market demand, forecasting prices, soil health insights, provide fertilizer recommendations, monitor the weather and track the readiness of produce. All of that enables farmers to make better decisions at every stage of the crop cultivation process.

Scope of AI in Agriculture:

Agriculture is seeing rapid adoption of Artificial Intelligence and Machine Learning both in terms of agricultural products and in-field farming techniques. Providing solutions like chatbot to all the farmers will help them keep pace with technological advancements as well as apply the same in their daily farming to reap the benefits of this service.Here are some areas:

Monitoring of crops:

Remote sensing techniques along with hyper spectral imaging and 3d laser scanning are essential to build crop metrics across thousands of acres. It has the potential to bring in a revolutionary change in terms of how farmlands are monitored by farmers both from time and effort perspective. This technology will also be used to monitor crops along their entire lifecycle.

Agricultural Robotics:

Companies are using automation and robotics to help farmers find more efficient ways to protect their crops from weeds. “Blue River Technology” has developed a robot called “See & Spray” which reportedly leverages computer vision to monitor and precisely spray weeds on cotton plants.

Using Drone Technology:

Before the crop cycle, drone can be used to produce a 3-D field map of detailed terrain, drainage, soil viability and irrigation. Nitrogen-level management can also be done by drone solutions. Aerial spraying of pods with seeds and plant nutrients into the soil provides necessary supplements for plants.

Pest Control:

Pest control companies are using AI to automate and improve everything from pesticide route planning, to spray times and pest prediction. By using AI technology, agricultural farmers and pest control companies can virtually walk every crop and provide nearly full-time monitoring to look for irregular crop degradation, pests, disease spots or dead soil.

IoT powered data analytics:

With the implementation of agricultural AI, farmers can analyze weather conditions, temperature, water usage and soil conditions collected from their farm to make informed decisions on business choices. Big data analysis helps reduce greenhouse gas emissions and pinpoints the exact soil, light, food and water requirements necessary for propagation.

Conclusion: Future of AI in Agriculture:

Many companies are using drone technology,remote sensors now a days. Farmers seek recommendations on specific problems using chatbots. AI also brings cost savings. So, in future Agriculture will be widely devloped using AI.

 

 

 

 

 

 


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