artificial intelligence in agriculture indexing AXIA

Artificial Intelligence uses predictive analysis, image analysis, learning techniques and Pattern analysis to declare the best cost effective and maximum gain for the agriculturist. USDA found that 30-40% of the food supply in the United States becomes food waste. It is expected to grow at a 24.2% CAGR between 2023 and 2032. (2021) Total Docs. Harvesting - With the help of AI, it is also possible to automate harvesting and predict the best time for it. Artificial Intelligence in Agriculture 2589-7217 (Online) Website ISSN Portal About; Articles; About. 3.1 Greenhouse Control Technology. Accessibility of production capacity. Accessibility of natural compost. But with the help of artificial intelligence (AI), it can predict the right time for harvesting that can save the crops from over-harvesting. Furthermore, issues such as population growth, climate change . The Impact Factor of this journal is 14.050, ranking it 7 out of 144 in Computer Science, Artificial Intelligence With this journal indexed in 18 international databases, your published article can be read and cited by researchers worldwide CiteScore 8.7 Impact Factor 14.050 Top Readership CN US GB Publication Time 1 week Artificial intelligence in agriculture helps to control pests, organize farming data, produce healthier crops, reduce workload, and many more. It will become more automated. Scientists have used it to develop self-driving cars and chess-playing computers, but the technology has expanded into another domain: agriculture. According to our (LP Information) latest study, the global Artificial Intelligence (AI) in Agriculture market size is USD million in 2022 from USD 566.1 million in 2021, with a change of % between 2021 and 2022. Artificial Intelligence in Agriculture Agriculture plays a crucial role in the economic sector for each country. Its goal is to make farming simpler, more precise, lucrative, and fruitful for farmers. 3. In order to better grasp the development of agricultural modernization, the index data system of agricultural modernization based on network big data is used to predict the various element indexes of agricultural modernization in the next two years as shown in Figure 7. Artificial intelligence is based on the principle that human intelligence can be defined in a way that a machine can easily mimic it and execute tasks, from the simplest to those that are even more complex. The color scale in this figure depicts the daily average air temperature, and is therefore duplicative of the x-axis labels. This Journal is the 12 th out of 1,095 Agriculture journals. The global AI valuation in the agriculture market was at $671.6 million in 2019 and approximated to reach about $11,200.1 million in 2030, signifying a CAGR of 30.5% during the forecast period (2020-2030). The use of AI in sustainable agriculture has the potential to transform aspects of farming such as image sensing for yield mapping, yield prediction, skilled and unskilled workforce, increasing yield and decision-support for farmers and producers [ 25 ]. The goals of artificial intelligence include learning, reasoning, and perception. Ser. . It is estimated that AI and connected farm services can impact 70 million Indian farmers by 2020, thereby adding US$ 9 billion to farmer incomes. In 2017, the global AI in agriculture market size was US$ 240 million, and is expected to reach US$ 1.1 billion by 2025 (Maher, 2018). Figure 7. Figure 1. 5. Artificial intelligence (AI) has emerged as a promising technology in digital agriculture. Opportunity for High Growth: Globally, Artificial Intelligence applications in agriculture reached a valuation of nearly $1 billion in 2019, and this valuation is estimated to grow to almost $8 billion by 2030. The h-index is a way of measuring the productivity and citation impact of the publications. The study examines the growth environment that drives new use-cases and greater . According to the Food and Agriculture Organization of the United Nations, the world population will reach over 9 billion by 2050. Experiment 2. Agriculture Robotics How Influential is Artificial Intelligence in Agriculture? The investigations were then classified according to the Artificial Intelligence technique applied. H-index is a common scientometric index, which is equal to h if the journal has published at least h papers having at least h citations. Email: info@isindexing.com, submission@isindexing.com; Open. Building on a long history of artificial intelligence (AI) activities that span a realm of disciplines and program areas, NIFA seeks to catalyze efforts that harness the power of AI in applications throughout agriculture and the food supply chain. As per the report by BIS Research on the artificial intelligence (AI) in agriculture market was $1,091.9 million in 2018, but it is expected that by 2024, the market will reach $3,807.3 million. Rising population, technological breakthrough, and government participation are the key factors driving the growth of artificial intelligence in agriculture market. The Impact of the Top 3 Strategic Imperatives on the Artificial Intelligence in Agriculture Industry Growth Opportunities Fuel the Growth Pipeline Engine 1. Artificial Intelligence in Agriculture. Post conference, proceedings will be made available to the following indexing services for possible inclusion: Conference Tracks Artificial Intelligence & Applications Emotional Computing Artificial neural networks, Fuzzy Logic Support Vector Machine and kernel methods Genetic Algorithms and Evolutionary Computing Graphical models and applications The role of AI in the agriculture information management cycle Combining artificial intelligence and agriculture can be beneficial for the following processes: Analyzing market demand AI can simplify crop selection and help farmers identify what produce will be most profitable. The nature of most of these applications doesn't outright replace human labor . AI and Ag in action Those who know farming know the many variables in play at any given point of the season. It specifically helps those who work with precision farming. : Conf. The world population is expected to reach over 9 billion by 2050, which will require an increase in agricultural and food production by 70% to fit the need, a serious challenge for the agri-food industry. I. But even in that picture of the future, there will be a need for the computer to give you the best first guess it can. "Virtually every aspect of agriculture will be impacted by artificial intelligence over the next 10 years. For this, a search process was carried out in the main scientific repositories. Artificial Intelligence (AI) in Agriculture Abstract: The articles in this special section examine the use of artificial intelligence in the farming and agricultural industries. The y-axis depicts the range of corn growth rates associated with those daily average . Such requirement, in a context of resources scarcity, climate change, COVID-19 pandemic, and very harsh socioeconomic conjecture, is difficult to fulfill without the intervention of . However, the Indian agri-tech market, presently valued at $204 million, has reached just 1% of its estimated potential of $24 billion. We're just scratching the surface on what AI could achieve. Difficulties in farming are, 1. The . GENERAL INFORMATION The AI activities supported through a variety of NIFA programs advance the ability of computer systems to perform tasks that . This book offers a practical, hands-on exploration of Artificial Intelligence, machine learning, deep Learning, computer vision and Expert system with proper examples to understand. Agricultural robots are frequently used for tasks such as the harvesting of crops and weed control. In this research service, the analyst examines the core capabilities of AI technology in the agriculture industry. Market value variety and reduction popular of produce. Formal knowledge representations are used in content-based indexing and retrieval, scene interpretation, . Then, an agronomist or grower will still need to apply their own judgment to that guidance." Globally, the use of artificial intelligence in agriculture is expected to grow by more than 25 per cent a year through 2025. Artificial Intelligence uses predictive analysis, image analysis, learning techniques and Pattern analysis to declare the best cost effective and maximum gain for the agriculturist. The greenhouse control technology is a typical application of artificial intelligence technology and IoT technology in agriculture. Agricultural and Biological Sciences (miscellaneous) Agronomy and Crop Science; Algebra and Number Theory; . DOAJ is a unique and extensive index of diverse open access journals from around the world, driven by a growing community, committed to ensuring quality content is freely available online for everyone. Data-led Transformation The major AI applications in making agriculture a smart field fall in three categories, including: Agriculture Robots (Agbots) Drones, Satellites, and Planes Smartphone Apps 1. According to USDA's Economic Research Service estimates, 31% of food waste at the retail and consumer levels equated to 133 billion pounds of food in 2010. Artificial Intelligence in agriculture can increase yield and productivity. Solutions.AI Scalable artificial intelligence solutions that deliver game-changing results, fast. AI works by processing large quantities of data, interpreting patterns in that data, and then translating these interpretations into actions that resemble those of a human being. Artificial intelligence can also play a role in food waste and help alleviate world hunger. 2. Artificial Intelligence in Agriculture is the 8 th out of 273 Food Science and Technology journals. Consequently, there is growing pressure to find smarter and more efficient ways to grow food and regulate the use of finite resources such as land, water, and energy - or else we may be in the face of a global food crisis. Accessibility of water. a direct application of ai or machine intelligence across the farming sector could act to be an epitome of shift in how farming is practiced today .using artificial intelligence we can develop smart farming practices to minimize loss of farmers and proved them with high yield .farming solution which are ai powered enables a farmer to do more with Also, we identify that the Internet of Things (IoT) is an emergent topic and that decision support systems and machine learning are the transversal topics. Artificial Intelligence has an important role to play in transforming food systems and helping to address food and nutrition insecurity. Artificial Intelligence contributes to farming by providing us with decision support systems that help make better decisions related to disease detection, crop readiness identification, field. Sign up; Sign in Synthesis Lectures on Artificial Intelligence and Machine Learning: book series: 3.273 Q1: 26: 3: 10: 641: 135: 7: 14.43: 213.67: 13: Pattern . Making each item productive, attractive is a test. Popular AI applications in agriculture Artificial Intelligence in Agriculture has an h-index of 6. Accessibility of transport to ship the produce/reap. A major intersection of agriculture and technology today is in artificial intelligence and machine learning to process massive amounts of data from those quadcopters buzzing over crop fields. In 2022, the market is growing at a . Publishing with this journal. (3years) Total Refs. The data has become digital now and it is as huge as it needs large storage areas like big data. This is typically done by creating an index that can be used to look up data quickly. Artificial intelligence solutions can enable farmers not to only reduce wastage, but also improve quality and ensure faster market access for the produce. They introduced the technology in agriculture to define the accurate information about seed, soil, weather, disease and all factors which affecting the farming. Managing risk Details: The scope of AI in agriculture in India can be understood from the way the technology can provide an efficient platform for buyers and sellers of agricultural produce. The precision farming category generated the largest revenue in the AI in the agriculture market. Phys. 6. "We're at beginning of a golden age of AI. Therefore, artificial intelligence (AI), another promising tool of 5th industrial era, could be used to complement agricultural RS technology to improve data processing and generating visualizing . Artificial intelligence in agriculture is divided into three categories: robotics, soil and crop management, and livestock farming. Re-Draw The graph shows the changes in the h-index of Artificial Intelligence in Agriculture and its the corresponding percentile for the sake of comparison with the entire literature. According to the UN, global hunger will rise by 50% . You Save: $24.00 Add to Cart . The objective of this paper is to review how artificial intelligence (AI) tools have helped the agricultural sector. Among the most common applications of artificial intelligence in agriculture are agricultural robots. Artificial Intelligence and IoT-Based Technologies for Sustainable Farming and Smart Agriculture: 9781799817222: Environment & Agriculture Books . In artificial intelligence, indexing is the process of creating a data structure that allows for fast and efficient retrieval of data. The aim of this paper is to provide the crucial information with the help of technology which a farmers can use to harvest the variety of crops as per the demand in . Artificial intelligence will help improve the output, management, and sustainability of agriculture in the future. In this interview, Congcong Sun and Chiem van Straaten discuss the challenges of machine learning in agriculture and weather forecasting, and the similarities and differences between their respective fields. Artificial Intelligence in Agriculture is an Open Access journal, publishing original View full aims & scope Insights $400* The journal of Artificial Intelligence (AIJ) welcomes papers on broad aspects of AI that constitute advances in the overall field including, but not limited Population around the world is increasing day by day, and so is the demand for food. It means 6 articles of this journal have more than 6 number of citations. The human population globally has crossed 7.7 billion and has created an alarming state for various governments across the globe. Cloud service providers do provide such services which helps to store, scan, analyse, Published under licence by IOP Publishing Ltd Journal of Physics: Conference Series, Volume 1693, The 2020 3rd International Conference on Computer Information Science and Artificial Intelligence (CISAI) 2020 25-27 September 2020, Inner Mongolia, China Citation Jiali Zha 2020 J. Feeding crops - AI is useful for identifying the best patterns of irrigation and nutrient use times and predicting the best mix of agricultural products. Artificial intelligence (ai) in agriculture market research report 2018 - Artificial Intelligence (AI) in Agriculture Industry, 2013-2023 Market Research Report' is a professional and in-depth study on the current state of the global Artificial Intelligence (AI) in Agriculture industry with a focus on the Chinese market. The Global Artificial Intelligence (AI) in Agriculture market is anticipated to rise at a considerable rate during the forecast period, between 2022 and 2029. FREMONT, California, Dec. 5, 2019 /PRNewswire/ -- According to a new market intelligence report by BIS Research titled 'Global Artificial Intelligence (AI) in Agriculture . Relevant parameters in the greenhouse, such as air temperature and humidity, carbon dioxide concentration, light intensity, soil moisture and humidity, and soil temperature, which can be obtained through the remote monitoring . Agriculture industries need to grow as it is the necessity of the society; various IoT based platforms have already been implemented for the different sectors of the agriculture industry [].Artificial intelligence technologies can also play a crucial role in the further development of the industry helping farmers in yielding of healthier crops, pest controlling, soil parameters monitoring . Abu Dhabi Consortium Weighs Bid. Artificial Intelligence (AI) techniques are widely used to solve a variety of problems and to optimize the production and operation processes in the fields of agriculture, food and bio-system engineering. entertainment, security, industry and manufacturing, agriculture, and networks (including social networks, smart cities and the Internet of things). This book also covers the basics of python with . Our Artificial Intelligence (AI) capabilities We offer AI consulting services and solutions that will help you achieve your business objectives faster, while setting you up for sustainable growth. Index Terms - Artificial Intelligence, Agriculture, ML, Automation, Sensors. This means the journal is among the top 3% in the sub-discipline of Food Science and Technology. The Global Artificial Intelligence in Agriculture market is anticipated to rise at a considerable rate during the forecast period, between 2022 and 2029. 4. 24 September 2020, Rome - The Food and Agriculture Organization of the United Nations (FAO), IBM and Microsoft, at an event organized today with the Pontifical Academy for Life, relaunched a commitment towards developing forms of Artificial Intelligence (AI) that are inclusive and promote sustainable ways to achieve food and nutrition security.. Artificial Intelligence in agriculture has brought about change in agriculture. On November 16th, 2022, ICAI organizes the 'ICAI Day: Artificial Intelligence and Climate Change' where Congcong, Chiem, and many . IBM has the largest portfolio of . Cognitive computing has become the most disruptive technology in agricultural services as it can learn, understand, and interact with different environments to maximize productivity. In particular, weed control robots are growing in popularity as farmers look for more efficient alternatives to mass spraying of herbicide. This book is a platform for anyone who wishes to explore Artificial Intelligence in the field of agriculture from scratch or broaden their understanding and its uses. Dec. 5, 2019, 06:30 AM. Artificial intelligence was founded as an academic . Rainstorm turnaround time. Artificial intelligence (AI) applied in agriculture are all those capacities that a machine, sensor, monitor or computer is capable of performing with great precision, collecting a series of data that allow us to adjust and optimize any type of task and crop to the maximum. Indexing is a key component of many AI applications, as it allows for faster and more efficient access to data. H index Total Docs. At the end, it concludes, the great utility of AI . These new methods have met the needs of the diet and provided employment for billions of people. In the agricultural sectors, it can do so in several ways . 1693 012058 Overview of indexing and abstracting services for Journal Artificial Intelligence on Elsevier.com Abstracting Indexing - Artificial Intelligence - ISSN 0004-3702 Skip to content A set of technologies is applied to the field to collect the important information for decision-making that farmers must anticipate. Jiali Zha 1. These technologies have protected crop yields from a variety of factors such as climate change, population growth, employment issues and food security issues. Predictor data graph. (2021) Total Cites (3years) . AI in agriculture is a useful tool that is now being implemented worldwide for the benefit of producers. Digital agriculture relates to using digital technologies for collecting, storing, and further analyzing the electronic agricultural data for better reasoning and decision-making using AI techniques. INTRODUCTION Agriculture is the solid base to keep the economy alive and healthy [1]. Agriculture Artificial Intelligence : By 2050, the world population is expected to reach 9.7 billion, according to the United Nations. The global market for artificial Intelligence in agriculture was worth USD 1,260.8 million in 2021. Agribusiness companies adopt artificial intelligence technologies that are predictive analytics-based. Finally, we identified that precision agriculture, smart farming, and smart sustainable agriculture refers to apply artificial intelligence and information technologies in agriculture. As the global economy mends, the 2021 growth of Artificial Intelligence (AI) in Agriculture will have significant change from previous year. The global AI in the agriculture market was worth US$ 240 million in 2017 and is predicted to grow to US$ 1.1 billion by 2025. The aim of the online event: AI, Food for All. Figure 1: Corn growth rate as a function of daily average temperature, as calculated by a proprietary AI-based algorithm. The traditional methods that are used by the farmers are not sufficient to fulfil the need at the current stage. In agriculture, artificial intelligence becomes a key technique for solving different problems (Bannerjee et al., 2018); it is considered to be a feasible solution to increase food production. According to Jivabhumi, their tool will bridge the gap between farmers looking to find markets and consumers looking for affordable agricultural produce. Abstracting & Indexing Archiving Buy Hardcover Qty: $216.00 List Price: $240.00. 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