Page 27 - Banking Finance May 2023

ARTICLE

and start-ups". In fact, the overall allocation for the sector industry. Robotic systems can be used to perform various
saw an increase of 4.7 per cent - from Rs 11,02,54.53 crore tasks, such as planting, harvesting, weeding, and crop
in the Revised Estimates (RE) of financial year (FY) 2022-23 monitoring. Some of the way's robots are being used in
to Rs 11,55,31.79 crore in 2023-24. farming are:
1. Planting and Harvesting: Robots can be used for
Advances in computer vision, mechatronics, artificial precision planting and harvesting, which allows farmers
intelligence, and machine learning are enabling the to optimize their crop yields and reduce labour costs.
development and deployment of remote sensing For example, robots can be programmed to plant seeds
technologies to identify and manage plants, weeds, pests at a specific depth and spacing, which can help ensure
and diseases. This also provides a unique opportunity to optimal growth and reduce waste.
develop intelligent seeding methods for precise fertilization.
2. Automatic Weeding: Robots can be used for
Artificial intelligence solutions can enable farmers not only
automated weeding, which can help reduce the use of
to reduce wastage, but also improve quality and ensure herbicides and improve crop yields. Automated weeding
faster market access for the produce. robots can use computer vision and machine learning
algorithms to identify and target weeds, while avoiding
Cognitive computing has become the most disruptive crops.
technology in agricultural services as it can learn,
3. Crop and Soil Monitoring: Robots can be used for crop
understand, and interact with different environments to
monitoring, which can help farmers identify potential
maximize productivity. Microsoft is currently working with
problems early and take corrective action. For example,
175 farmers in Andhra Pradesh to provide agricultural, land
robots can be equipped with sensors to monitor soil
and fertilizer advisory services. This initiative has already
moisture levels, temperature, and nutrient levels.
resulted in 30% higher average yield per hectare last year.
4. Dairy Farming: Robots can also be used in dairy farming
to automate tasks such as milking cows and feeding
AI in agriculture involves the use of machine learning,
them. Automated milking robots can use sensors to
computer vision, and robotics to optimize various aspects
detect when a cow needs to be milked, and then
of farming. The technology helps farmers to analyse data,
automatically attach and detach milking machines.
make informed decisions, and automate tasks that would
be time-consuming and expensive when done manually. 5. Insect and Plant disease monitoring: Using image
recognition technology based on deep learning, we can
Here we will be discussing some of the use cases of AI, now automate detection of plant diseases and pests.
Robotics and other technologies in Agriculture and allied This works using image classification, detection, and
activities. image segmentation methods to build models that can
"keep an eye" on plant health.
Robots in farming have been gaining traction in recent years,
6. Ariel survey and imaging: AI can analyse imagery from
as they offer the potential to revolutionize the agricultural drones and satellites to help farmers monitor crops and
herds. That way they can be notified immediately if
something looks amiss without having to constantly
observe the fields themselves. Aerial imaging is also
useful for boosting the precision and efficiency of
pesticide spraying. As mentioned previously, ensuring
that pesticides only go where they're intended saves
money as well as the surrounding environment.
7. Management of livestock: Farmers can use sensors to
track the health and behaviour of their animals, and
machine learning algorithms can analyse the data to
detect patterns and identify potential health problems.
This helps farmers to prevent the spread of disease,
reduce the use of antibiotics, and improve the overall
health of their animals.

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