Smart Agriculture strengthening the future of AI in the farming industry, according to Zion market research. The world population is expected to grow by 9 billion by 2050 and there will be a shortage of food, as farmers count and farming land is decreasing at a higher rate. AI in farming can generate USD 2,072 by 2024. The availability of tech applications like agricultural drones, robots for farming, driverless tractors, facial recognition in crop health monitoring systems, and automated irrigation systems have made the agricultural sector the cusp of a technology revolution.
AI-powered technologies can help farmers in growing healthier crops, pest control, and determining soil conditions, and growing conditions. By advancing in technology, smart agriculture has the potential to change the chain of the entire food life cycle. Globally, AI applications in agriculture are segmented into technology applications, regions, and soil components. Before discussing the technologies that are changing the dynamics of farming, let’s have a short glimpse of AI technologies that are used in different regions of the globe.
Smart farming global outline:
North America is anticipated to hold the maximum percentage of shares globally by merging AI in the agriculture segment by 2024. The implementation of AI in farming in various zones is driving tremendous growth and attracting investors from various parts of the world. How did it start? North America has unsettled climatic conditions and its soil eruptions due to frequent natural disasters. In 2007, climate corp in partnership with D UAS corp implemented a climate monitoring system in western Canada. That provides advanced analytics for aerial imagery data, that helps farmers in climate field view.
In pacific Asia, countries such as China, India, South Korea, Australia, and Japan can have lucrative growth by adopting AI in the agricultural segment in the coming future. Alibaba’s global E-commerce giant has developed an AI-based model that assists farmers in, how to increase crop yield at a low cost in grape farming. And by using Alibaba’s mobile applications, the farmers can access the field demonstration through digitally monitored systems.
India has taken its first pace towards smart agriculture through the implementation of AI in the agriculture segment. NITI in collaboration with IBM unveiled an experiment in crop field prediction and monitoring model with the help of drones. Where, it provides insights to farmers in enhancing crop output, soil yield, and controlled agriculture input along with the reduced cost for crop yielding. Currently, this experiment is conducted in Maharashtra state on rabi crops.
Significance of AI in farming
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Data-driven farming:
Based on the historical data, the farmers can drive data insights regarding climatic conditions, soil quality, types of seeds, crop health conditions, and detection & prediction of diseases. Farmers can also analyze market trends, and costs for a particular variety of crops in different regions, which helps in taking quality decisions from informative insights.
Chatbots are mainly used in retail, banking, and other industries. Now agriculture and farming are leveraging its applications. For instance, Alexa for farmers. This chatbot uses voice assistants to answer all the queries of the farmers. And through IoT enabled system, it integrates with other tech applications in farming to communicate necessary information.
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Computer vision-enabled farming:
AI-powered drones, with computer vision cameras integrated with deep learning networks, can click and process images at high accuracy to monitor the farm fields. The drones can drive real-time insights to address the problem and provide better inputs for efficient farming.
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Indoor farming:
The ambitious techie farmers are implementing growing methods like hydroponics and artificial lights to grow large-scale crops, in a closed environment. Artificial lights provide different levels of light required for photosynthesis and plant growth. The world’s largest indoor farming is in Tokyo spread over 83 acres and it is fully automated with AI-driven technologies, which monitor crop growth from seed germination to harvesting.
Current AI prototypes driving Smart Agriculture:
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Blue river technology:
Blue river technology was founded in the year 2011, at the California base. This technology helps farmers in weed detection and control, and crop health monitoring, and aims at eradicating pesticides. It is computer vision-enabled and a machine learning robotic system that monitors every crop and depending upon a particular crop condition, it provides required supplements in the right quantity. The system also monitors larvae or insects that are affecting plant yield.
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Farm Bot
Farm bot was founded in the year 2014 by farmbot.it. It is a robot developed by Arison, a polytechnic student in California. The robot addresses the pain points of people who don’t know to farm and also helps farmers in reducing costs. The robot can perform end-to-end farming on its own, ranging from seed plantation to harvesting. This robot can farm 30 different varieties of crops, which can feed humans shortly. This robot can be used for indoor and outdoor farming and revolutionizing the smart agriculture industry.
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Plantix
Plantix is a plant diagnosis mobile app that uses AI and machine learning tools to guide farmers in detecting the disease of a plant and it helps in guiding the right diagnosis. It also suggests the soil conditions based on plant health.
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AG robot
The lack of laborers during harvesting has led to the loss of millions of dollars to farmers in certain areas of the world. This robot helps by reducing labor costs during the harvest season and time consumed in harvesting. AGrobot is a working prototype used for strawberry harvesting in the regions of Arizona and California as strawberry pickers need skills in harvesting the right fruit at the right time.
With AI-driven technologies farmers can harvest the right crop for the right season that yields best by monitoring soil, crop growth, climate, and water necessities. As agriculture advances in technology, farmers are gaining more revenue. AI in agriculture is at the core. Still, the vast areas of agricultural fields are unexplored. By leveraging the technologies and applications of AI in farming, the agriculture industry can drive more revenues, with less investment cost, in a short period of harvesting time.
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