Artificial Intelligence & Machine Learning

Know more about the technology transforming agriculture

KhetiBuddy’s AI and ML applications enables the agribusinesses’ with a key tech component for adoption of better and efficient farming practices. AI and ML can help crops yield and quality more efficiently than ever before, owing to its ability to optimize resources, predict weather patterns, and identify pests or diseases early on.

Resolving production bottlenecks with DeepTech

Agriculture is a critical part of the global economy, but it's also one of the most challenging sectors to operate in. Agriculture is challenged by the growth of the global population at an alarming rate, and with it the demand for food.

It's estimated that we'll need to produce 70% more food by 2050 to meet the needs of the world's population. Farmers are under constant pressure to produce more food with fewer resources, and they often don't have access to the latest technology or information while they face increasing competition from abroad and rising production costs.

Artificial Intelligence (AI) and Machine Learning (ML) can help farmers overcome these challenges. It can help increase crop yields while reducing production costs at farm level. Our algorithms use real-time data and visualize analytics to improve predictions about which crops will thrive and where pests are likely to appear. We also develop optimized pesticide mixes to be applied only where needed, reducing waste and environmental impact. With our algorithms' ability to identify pests and disease using image processing and recognition framework, farmers/growers can get immediate actionable advice for limiting crop losses. It also connects them with advisors for further assistance.

Applications of AI and ML for Agriculture

Traditional methods are no longer enough to handle huge food demand, which is driving farmers and agri-based companies to find newer ways to increase production and reduce input and output waste. As a result, Artificial Intelligence (AI) and Machine Learning (ML) is steadily emerging as part of the agri industry’s tech evolution. There’s no doubt that crop yields and quality are more efficient now than they were centuries, or even decades ago with the help of AI. We’ll take a look at some of the most promising AI/ML use-cases for agriculture:
Looking for optimizing farm resource management and increasing farm profitability?
Artificial intelligence
Artificial Intelligence

Proprietary AI algorithm for agribusiness

High data granularity
Reduce crop losses
Combat climate change
Machine Learning
Machine Learning

High performance computing for agriculture

Optimizing farming practices
Data-driven decision making
Yield forecast and estimation
Mitigate crop deficiencies

FAQs on AI/ML for Agriculture

Our AI/ML modules are trained with a credible secondary and primary database upon which we run the algorithm to create actionable insights and inputs for improving farming practices. This model can be trained for any crops provided that sufficient database (includes images) is available with you to provide high accuracy. KhetiBuddy does not take any responsibility or liability for variances in output in such cases, however we will provide support and guidance in order to help you train the model with right inputs.
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