Artificial Intelligence For Biology And Agriculture


Artificial Intelligence For Biology And Agriculture
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Artificial Intelligence For Biology And Agriculture


Artificial Intelligence For Biology And Agriculture
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Author : S. Panigrahi
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Artificial Intelligence For Biology And Agriculture written by S. Panigrahi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.


This volume contains a total of thirteen papers covering a variety of AI topics ranging from computer vision and robotics to intelligent modeling, neural networks and fuzzy logic. There are two general articles on robotics and fuzzy logic. The article on robotics focuses on the application of robotics technology in plant production. The second article on fuzzy logic provides a general overview of the basics of fuzzy logic and a typical agricultural application of fuzzy logic. The article `End effectors for tomato harvesting' enhances further the robotic research as applied to tomato harvesting. The application of computer vision techniques for different biological/agricultural applications, for example, length determination of cheese threads, recognition of plankton images and morphological identification of cotton fibers, depicts the complexity and heterogeneities of the problems and their solutions. The development of a real-time orange grading system in the article `Video grading of oranges in real-time' further reports the capability of computer vision technology to meet the demand of high quality food products. The integration of neural network technology with computer vision and fuzzy logic for defect detection in eggs and identification of lettuce growth shows the power of hybridization of AI technologies to solve agricultural problems. Additional papers also focus on automated modeling of physiological processes during postharvest distribution of agricultural products, the applications of neural networks, fusion of AI technologies and three dimensional computer vision technologies for different problems ranging from botanical identification and cell migration analysis to food microstructure evaluation.



Machine Learning In Biological Sciences


Machine Learning In Biological Sciences
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Author : Shyamasree Ghosh
language : en
Publisher: Springer Nature
Release Date : 2022-05-04

Machine Learning In Biological Sciences written by Shyamasree Ghosh and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-04 with Medical categories.


This book gives an overview of applications of Machine Learning (ML) in diverse fields of biological sciences, including healthcare, animal sciences, agriculture, and plant sciences. Machine learning has major applications in process modelling, computer vision, signal processing, speech recognition, and language understanding and processing and life, and health sciences. It is increasingly used in understanding DNA patterns and in precision medicine. This book is divided into eight major sections, each containing chapters that describe the application of ML in a certain field. The book begins by giving an introduction to ML and the various ML methods. It then covers interesting and timely aspects such as applications in genetics, cell biology, the study of plant-pathogen interactions, and animal behavior. The book discusses computational methods for toxicity prediction of environmental chemicals and drugs, which forms a major domain of research in the field of biology. It is of relevance to post-graduate students and researchers interested in exploring the interdisciplinary areas of use of machine learning and deep learning in life sciences.



Agricultural Biotechnology


Agricultural Biotechnology
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Author : Charles Oluwaseun Adetunji
language : en
Publisher: CRC Press
Release Date : 2022-12-21

Agricultural Biotechnology written by Charles Oluwaseun Adetunji and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-21 with Medical categories.


This book presents strategies and techniques highlighting the sustainability and application of microbial and agricultural biotechnologies to ensure food production and security. This book includes different aspects of applications of Artificial Intelligence in agricultural systems, genetic engineering, human health and climate change, recombinant DNA technology, metabolic engineering and so forth. Post-harvest extension of food commodities, environmental detoxification, proteomics, metabolomics, genomics, bioinformatics and metagenomic analysis are discussed as well. Features: Reviews technological advances in microbial biotechnology for sustainable agriculture using Artificial Intelligence and molecular biology approach. Provides information on the fusion between microbial biotechnology and agriculture. Specifies the influence of climate changes on livestock, agriculture and environment. Discusses sustainable agriculture for food security and poverty alleviation. Explores current biotechnology advances in food and agriculture sectors for sustainable crop production. This book is aimed at researchers and graduate students in agriculture, food engineering, metabolic engineering and bioengineering.



A Biologist S Guide To Artificial Intelligence


A Biologist S Guide To Artificial Intelligence
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Author : Ambreen Hamadani
language : en
Publisher: Elsevier
Release Date : 2024-03-15

A Biologist S Guide To Artificial Intelligence written by Ambreen Hamadani and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-15 with Computers categories.


A Biologist’s Guide to Artificial Intelligence: Building the Foundations of Artificial Intelligence and Machine Learning for Achieving Advancements in Life Sciences provides an overview of the basics of Artificial Intelligence for life science biologists. In 14 chapters/sections, readers will find an introduction to Artificial Intelligence from a biologist’s perspective, including coverage of AI in precision medicine, disease detection, and drug development. The book also gives insights into the AI techniques used in biology and the applications of AI in food, and in environmental, evolutionary, agricultural, and bioinformatic sciences. Final chapters cover ethical issues surrounding AI and the impact of AI on the future. This book covers an interdisciplinary area and is therefore is an important subject matter resource and reference for researchers in biology and students pursuing their degrees in all areas of Life Sciences. It is also a useful title for the industry sector and computer scientists who would gain a better understanding of the needs and requirements of biological sciences and thus better tune the algorithms. Helps biologists succeed in understanding the concepts of Artificial Intelligence and machine learning Equips with new data mining strategies an easy interface into the world of Artificial Intelligence Enables researchers to enhance their own sphere of researching Artificial Intelligence



A Biologist S Guide To Artificial Intelligence


A Biologist S Guide To Artificial Intelligence
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Author : Ambreen Hamadani
language : en
Publisher: Elsevier
Release Date : 2024-03

A Biologist S Guide To Artificial Intelligence written by Ambreen Hamadani and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03 with Computers categories.


A Biologist's Guide to Artificial Intelligence: Building the Foundations of Artificial Intelligence and Machine Learning for Achieving Advancements in Life Sciences provides an overview of the basics of Artificial Intelligence for life science biologists. In 14 chapters/sections, readers will find an introduction to Artificial Intelligence from a biologist's perspective, including coverage of AI in precision medicine, disease detection, and drug development. The book also gives insights into the AI techniques used in biology and the applications of AI in food, and in environmental, evolutionary, agricultural, and bioinformatic sciences. Final chapters cover ethical issues surrounding AI and the impact of AI on the future. This book covers an interdisciplinary area and is therefore is an important subject matter resource and reference for researchers in biology and students pursuing their degrees in all areas of Life Sciences. It is also a useful title for the industry sector and computer scientists who would gain a better understanding of the needs and requirements of biological sciences and thus better tune the algorithms.



Artificial Intelligence And Internet Of Things In Smart Farming


Artificial Intelligence And Internet Of Things In Smart Farming
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Author : Mohamed Abdel-Basset
language : en
Publisher: CRC Press
Release Date : 2024-04-01

Artificial Intelligence And Internet Of Things In Smart Farming written by Mohamed Abdel-Basset and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-01 with Computers categories.


This book provides a broad overview of the areas of artificial intelligence (AI) that can be used for smart farming applications, through either successful engineering or ground-breaking research. Among them, the highlighted tactics are soil management, water management, crop management, livestock management, harvesting, and the integration of Internet of Things (IoT) in smart farming. Artificial Intelligence and Internet of Things in Smart Farming explores different types of smart framing systems for achieving sustainability goals in the real environment. The authors discuss the benefits of smart harvesting systems over traditional harvesting methods, including decreased labor requirements, increased crop yields, increased probabilities of successful harvests, enhanced visibility into crop health, and lower overall harvest and production costs. It explains and describes big data in terms of its potential five dimensions—volume, velocity, variety, veracity, and valuation—within the framework of smart farming. The authors also discuss the recent IoT technologies, such as fifth-generation networks, blockchain, and digital twining, to improve the sustainability and productivity of smart farming systems. The book identifies numerous issues that call for conceptual innovation and has the potential to progress machine learning (ML), resulting in significant impacts. As an illustration, the authors point out how smart farming offers an intriguing field for interpretable ML. The book then delves into the function of AI techniques, such as AI in accelerating the development of nano-enabled agriculture, thereby facilitating safe-by-design nanomaterials for various consumer products and medical applications. This book is for undergraduate students, graduate students, researchers, and AI engineers who pursue a strong understanding of the practical methods of machine learning in the agriculture domain. Practitioners and stakeholders would be able to follow this book to understand the potential of ML in their farming projects and agricultural solutions. Features: • Explores different types of smart framing systems for achieving sustainability goals in the real environment • Explores ML-based analytics such as generative adversarial networks (GAN), autoencoders, computational imaging, and quantum computing • Examines the development of intelligent machines to provide solutions to real-world problems, emphasizing smart farming applications, which are not modeled or are extremely difficult to model mathematically • Emphasizes methods for better managing crops, soils, water, and livestock, urging investors and businesspeople to occupy the existing vacant market area • Discusses AI-empowered Nanotechnology for smart farming



Bioinformatics For Agriculture High Throughput Approaches


Bioinformatics For Agriculture High Throughput Approaches
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Author : Atul Kumar Upadhyay
language : en
Publisher: Springer Nature
Release Date : 2021-03-19

Bioinformatics For Agriculture High Throughput Approaches written by Atul Kumar Upadhyay and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-19 with Science categories.


This book illustrates the importance and significance of bioinformatics in the field of agriculture. It first introduces the basic concepts of bioinformatics, such as homologous sequence and gene function analyses, determination of protein structures, and discusses machine learning applications for an in-depth understanding of the desired genes and proteins based on commonly used bioinformatics software and tools, e.g. BLAST, molecular modelling, molecular-docking and simulations, protein-protein and domain-domain interactions. The book also describes recent advances in the high-throughput analysis of whole genome and transcriptome using next-generation sequencing platforms, and functional proteome studies. It also examines the role of computational biology in understanding and improving the nutrient quality and yield of crops. Lastly, the book explores a comprehensive list of applications of bioinformatics to improve plant yield, biomass, and health, and the challenges involved.



Artificial Intelligence Of Things Aiot In Precision Agriculture


Artificial Intelligence Of Things Aiot In Precision Agriculture
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Author : Yaqoob Majeed
language : en
Publisher: Frontiers Media SA
Release Date : 2024-02-12

Artificial Intelligence Of Things Aiot In Precision Agriculture written by Yaqoob Majeed and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-12 with Science categories.


The merging of Artificial Intelligence (AI) and Internet-of-Things is known as Artificial Intelligence-of-Things (AIoT). IoT consists of interlinked computing devices and machines which can acquire, transfer, and execute field/industrial operations without human involvement, while AI processes the acquired data and helps extract the required information. The technologies work in synergy: AI enriches IoT through machine learning and deep learning-based data analysis and learning capabilities, whereas IoT enriches AI through data acquisition, connectivity, and data exchange. Precision agriculture is becoming critically important for sustainable food production to meet the growing food demand. In recent decades, AI and IoT techniques have played an increasing role within industrial operations (e.g. autonomous manufacturing, automated supply chain management, predictive maintenance, smart energy grids, smart home appliances, and wearables), however, agricultural field operations are still heavily dependent on human labor. This is because these operations are ill-defined, unstructured, and susceptible to variation in natural conditions (e.g. illumination, landscape, atmosphere) plus the biological nature of crops (fruits, stems, leaves, and/or shoots continuously change their shape and/or color as they grow).



Iot And Ai In Agriculture


Iot And Ai In Agriculture
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Author : Tofael Ahamed
language : en
Publisher: Springer Nature
Release Date : 2023-04-10

Iot And Ai In Agriculture written by Tofael Ahamed and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-04-10 with Technology & Engineering categories.


This book reviews recent innovations in the smart agriculture space that use the Internet of Things (IoT) and sensing to deliver Artificial Intelligence (AI) solutionsto agricultural productivity in the agricultural production hubs. In this regard, South and Southeast Asia are one of the major agricultural hubs of the world, facing challenges of climate change and feeding the fast-growing population. To address such challenges, a transboundary approach along with AI and BIG data for bioinformatics are required to increase yield and minimize pre- and post-harvest losses in intangible climates to drive the sustainable development goal (SDG) for feeding a major part of the 9 billion population by 2050 (Society 5.0 SDG 1 & 2). Therefore, this book focuses on the solution through smart IoT and AI-based agriculture including pest infestation and minimizing agricultural inputs for in-house and fields production such as light, water, fertilizer and pesticides to ensure food security aligns with environmental sustainability. It provides a sound understanding for creating new knowledge in line with comprehensive research and education orientation on how the deployment of tiny sensors, AI/Machine Learning (ML), controlled UAVs, and IoT setups for sensing, tracking, collection, processing, and storing information over cloud platforms for nurturing and driving the pace of smart agriculture in this current time. The book will appeal to several audiences and the contents are designed for researchers, graduates, and undergraduate students working in any area of machine learning, deep learning in agricultural engineering, smart agriculture, and environmental science disciplines. Utmost care has been taken to present a varied range of resource areas along with immense insights into the impact and scope of IoT, AI and ML in the growth of intelligent digital farming and smart agriculture which will give comprehensive information to the targeted readers.



Artificial Intelligence Theory Models And Applications


Artificial Intelligence Theory Models And Applications
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Author : P Kaliraj
language : en
Publisher: CRC Press
Release Date : 2021-10-21

Artificial Intelligence Theory Models And Applications written by P Kaliraj and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-21 with Computers categories.


This book examines the fundamentals and technologies of Artificial Intelligence (AI) and describes their tools, challenges, and issues. It also explains relevant theory as well as industrial applications in various domains, such as healthcare, economics, education, product development, agriculture, human resource management, environmental management, and marketing. The book is a boon to students, software developers, teachers, members of boards of studies, and researchers who need a reference resource on artificial intelligence and its applications and is primarily intended for use in courses offered by higher education institutions that strive to equip their graduates with Industry 4.0 skills. FEATURES: Gender disparity in the enterprises involved in the development of AI-based software development as well as solutions to eradicate such gender bias in the AI world A general framework for AI in environmental management, smart farming, e-waste management, and smart energy optimization The potential and application of AI in medical imaging as well as the challenges of AI in precision medicine AI’s role in the diagnosis of various diseases, such as cancer and diabetes The role of machine learning models in product development and statistically monitoring product quality Machine learning to make robust and effective economic policy decisions Machine learning and data mining approaches to provide better video indexing mechanisms resulting in better searchable results ABOUT THE EDITORS: Prof. Dr. P. Kaliraj is Vice Chancellor at Bharathiar University, Coimbatore, India. Prof. Dr. T. Devi is Professor and Head of the Department of Computer Applications, Bharathiar University, Coimbatore, India.