AI Smart Farm

Smart Agriculture strengthening the future of AI in the farming industry, according to Zion market research. The world population is expected to grow 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. With 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, 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.

Significance of AI in farming

Evolving tech applications have changed the outlook of farming. Below mentioned are prominent tech areas that are leveraged by today’s farming industry.

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, cost for a particular variety of crops in different regions, which helps in taking quality decisions from informative insights.

The chatbots are mainly used in retail, banking and other industries. Now agricultural and farming is 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.

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.

Indoor farming:

The ambitious techie farmers are implementing growing methods like hydroponics and artificial lights to grow large scale crop, 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:

Blue river technology:

Blue river technology was founded in the year 2011, at California base. This technology helps farmers in weed detection and control, 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 larva or insects that are affecting plant yield.

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 doesn’t know farming and also helps farmers in reducing cost. 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 smart agriculture industry.

Plantix

Plantix is a plant diagnosis mobile app that uses AI and machine learning tools to guide farmers in detecting disease of a plant and it helps in guiding the right diagnosis. It also suggests the soil conditions based on plant health.

AG robot

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 cost 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, the farmers are gaining more revenues. 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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