By: Rishi Khanna
We are heading towards a major crisis. The crisis related to food shortage. Experts say that by 2050, Earth’s population is set to grow by 2 billion and the conventional ways of farming will not leave us with enough ways to feed the entire population. As per UN Food and Agricultural Organization (FAO), the global population will reach 9.2 billion (by the year 2050). In order to feed this crazy growth in people, there has to be a miracle. If we were to grow the agricultural produce in its current state, it will bring only more harm to the future generations and our planet than do any good.
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In order to increase produce, till now, humans have cut down forests and ploughed more farms and grasslands. Sizeable areas in South America and Africa have been cleared in order to raise livestock and to farm. To add to the challenge, there are challenges like global warming and urbanization that is making it more difficult to increase crop growth. World hunger and scarcity are all real horrors that we have to address soon. The sooner, the better.
Smart Farming with Artificial Intelligence
We have seen Artificial Intelligence help with Google search results and Facebook friend suggestions. In reality, AI has reached far and is impacting all industries. It is expected to help the Agricultural Industry with the current food crisis as well.
There is a need to go from small farming to smart farming. If Machine Learning, an algorithm that absorbs and analyzes a huge volume of data in order to ascertain common patterns and in turn transforms those patterns into predictions. In agriculture, it can prevent wastage and damage.
Precision Farming makes use of real-time historical data in combination with machine learning algorithms for specific actions. For example, it can help you decide how to save cost and reduce waste by applying pesticide to a specific area rather than a large area. You can avoid damage from chemical substance to trees, leaves and bushes with this information.
There can be real-time insights about crops produce with the help of sensors, in-field cameras, and micro weather data. Early signs of damage to the crop can be detected and addressed with the help of deep learning and computer vision algorithms. There might be a number of crop related issues that can skip the eyes of humans but can be detected with the help of proven and well-trained algorithms. There are smart sensors to detect the following:
- Crop water demand
- Water stress
- Microclimate data
- Canopy biomass
Decisions and predictions can be automated on the basis of real measurements rather than the gut feelings. Some companies are using NASA Satellite imagery and data related to weather for a prediction of water that is required for crops.
Everything is not as easy though. Poor connectivity at the farms will be a hurdle for AI technologies. Machine learning algorithms will also help to breed improved plant genes, and create an improved and safer crop protection products and fertilizers. AI disruption is critical to the agricultural industry to process abundant data and gain quicker results. AI-driven technologies can make the food produce process automated and data-driven but if it can address the world food crisis, only time will tell.
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