Application of ai in agriculture

Artificial Intelligence is an approach to make a computer, a robot, or a product to think about how smart humans think. AI is a study of how the human brain thinks, learns, decides and work when it tries to solve problems. And finally, this study outputs intelligent software systems. The aim of AI is to improve computer functions that are related to human knowledge, for example, reasoning, learning, and problem-solving.

1. SAM HIGGINBOTTOM UNIVERSITYOFAGRICULTURE, TECHNOLOGY AND SCIENCES PROJECT ON “ARTIFICIAL INTELLIGENCE IN AGRICULTURE” COURSE NAME: COMPUTER ORIENTATION COURSE CODE: CSIT-701 PROGRAMME: MSC. FORESTRY (FOREST BIOLOGY AND TREE IMPROVEMENT)

2. INTRODUCTION TO ARTIFICIAL INTELLIGENCE Artificial Intelligence is an approach to make a computer, a robot, or a product to think how smart human think. AI is a study of how human brain think, learn, decide and work, when it tries to solve problems. And finally this study outputs intelligent software systems. The aim of AI is to improve computer functions which are related to human knowledge, for example, reasoning, learning, and problem-solving. John McCarthy said, “The science and engineering of making intelligent machines, especially intelligent computer programs”. The intelligence is intangible and it is composed of: Reasoning Learning Problem Solving Perception Linguistic Intelligence

3. SCOPE OF ARTIFICIAL INTELLIGENCE IN AGRICULTURE In a country like India, where over 58% of the rural population is dependent on agriculture in direct or indirect manner, bringing AI tools and technologies can be game-changing. Satellite data is also being used for assessing the farm imageries and offering predictions regarding future yields. It cannot just help the farmers get assured returns from their agricultural investment but also help in avoiding any unknown damage from pest attack or sudden climate change. Various startups like PEAT, SatSure, Earth Food, and V Drone Agro are empowering the farmers with varied solutions that are based on Artificial Intelligence, Machine Learning, data science, analytics, and cloud. Several AI-powered technologies like robotics, agrictech, drones, predictive analysis, soil monitoring devices, satellite imagery, automated irrigation system, etc., are here to change the face of Indian agriculture.

4. ARTIFICIAL INTELLIGENCE POWERED PROJECTS IN INDIAN AGRICULTURE SECTOR e- National agriculture market ( eNAM ) eNAM is an online trading platform for agricultural commodities in India. The market facilitates farmers, traders and buyers with online trading in commodities. AI for precision farming Pradhan Mantri Fasal Bima Yojana (PMFBY) PMFBY will be providing support to farmers who are suffering from crop loss or damage arising out of unforeseen events, along with stabilizing the income of farmers to ensure their continuance in farming. PM- KISAN Pradhan Mantri Kisan Samman Nidhi is an initiative by the government of India in which all small and marginal farmers will get up to Rs 6,000 (US$84) per year as minimum income support.

5. AGRI-UDAAN The program focuses on catalyzing scale-up stage food and agribusiness startups through rigorous mentoring, industry networking and investor pitching. This initiative is a 6- month program launched in Hyderabad. 6. Government of karnataka inks MoU with microsoft The collaboration intends to empower smallholder farmers with AI- based solutions that will help them increase income using ground- breaking, cloud-based technologies, machine learning and advanced analytics. Maha agri tech project The first phase of the project uses satellite images and data analysis done by Maharashtra Remote Sensing Application Centre (MRSAC) and the National Remote Sensing Centre (NRSC) to assess the area of land, and the conditions of select crops in select talukas . However, the second phase includes an analysis of the data collected to build a seamless framework for agriculture modeling and a geospatial database of soil nutrients, rainfall and moisture stress to facilitate location- specific advisories to farmers.

6. Application of Artificial Intelligence in Agriculture Weather forecasting Soil health monitoring system Analyzing crop health Precision Farming Identifying Plant Diseases Detecting pest infestations Agricultural Product Grading Alerts on Crop Infestation Detecting weeds Irrigation Warehousing

7. CHALLENGES IN AI ADOPTION IN AGRICULTURE “The major challenge in the broad adoption of AI in agriculture is the lack of simple solutions that seamlessly incorporate and embed AI in agriculture. The majority of farmers don’t have the time or digital skills experience to explore the AI solutions space by them. AI faces the same challenge as the war between AC and DC current did at the turn of the 19th century; it became more about the solutions that the technology-powered, rather than the technology itself. AI solutions in agriculture will require new ontology's and common terminologies to be agreed upon globally. These new AI solutions will then have to be incorporated into existing and legacy infrastructure and systems that farmers already use (e.g. tractors, spreaders or Farm Management software), through improved APIs, in order to seamlessly incorporate and embed AI within agriculture.” (Gary Morgan).

8. Difference between traditional methods of farming and modern methods of farming TRADITIONAL METHODS OF FARMING MODERN METHODS OF FARMING 1. The outdated and old methods of farming used from earlier times are known as traditional methods of farming. 1. New and scientific methods of farming which are used nowadays are known as modern methods of farming. 2. These methods are time consuming and production is also low. 2. These methods are quick, efficient and easy to used and lead to higher production in less time. 3. Old methods like irrigating lands with the help of Persian wheels are used. 3. Machinery like tractors and threshers are used. 4. Traditional seeds are used. 4. HYV seeds, irrigation, chemical fertilizers, pesticides etc. are used. 5. Farmers are dependent on monsoon rain. 5. Farmers are not dependent on monsoon rain as they have provision of tube wells for irrigation. 6. Cow-dung and other natural manure are used as fertilizers. 6. Chemical fertilizers are pesticides are used. 7. Traditional farming methods do not require more inputs which are manufactured in industry. 7. Modern farming methods required more inputs which are manufactured in industry.

9. Pros and Cons of Artificial Intelligence Pros AI would have a low error rate compared to humans, if coded properly. They would have incredible precision, accuracy, and speed. They won't be affected by hostile environments, thus able to complete dangerous tasks, explore in space, and endure problems that would injure or kill us. Predict what a user will type, ask, search, and do. They can easily act as assistants and can recommend or direct various actions. D etect fraud in card-based systems, and possibly other systems in the future. Interact with humans for entertainment or a task as avatars or robots. AI can be for medical purposes, such as health risks and emotional state. Cons Can cost a lot of money and time to build, rebuild, and repair. Robotic repair can occur to reduce time and humans needing to fix it, but that'll cost more money and resources. It's questionable: is it ethically and morally correct to have androids, human-like robots, or recreate intelligence, a gift of nature that shouldn't be recreated? This is a discussion about AI that's popular in the days. Robots, with them replacing jobs, can lead to severe unemployment, unless if humans can fix the unemployment with jobs AI can't do or severely change the government to communism.

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