| computer science in agriculture: Computer Applications in Agricultural Environments J.A. Clark, K. Gregson, R.A. Saffell, 2016-01-22 Computer Applications in Agricultural Environments talks about the influence of computers on the industry of agriculture. The text explains how computers help to simplify calculations and other duties related to the field. The book's 21 chapters revolve around the relationship of computers, agriculture, and the environment. The majority of the chapters talks about the different simulation controls that the computer can do. Controls include climate control, greenhouse control, greenhouse climate feedback/feed-forward control (GCFFC) control, glasshouse control, crop drying control, sulfur dioxide control, retort control, animal control, broiler-house ventilation control, and poultry-house control. Other topics related to computers and agriculture are also discussed, such as monitoring rainfall interception, grain drying, monitoring techniques for ammonia, and various techniques for remote monitoring. The text covers a wide range of topics in the mentioned fields, and can therefore serve as an excellent reference for students or professors in the field of agriculture. |
| computer science in agriculture: Computer Vision and Machine Learning in Agriculture Mohammad Shorif Uddin, Jagdish Chand Bansal, 2021-03-23 This book discusses computer vision, a noncontact as well as a nondestructive technique involving the development of theoretical and algorithmic tools for automatic visual understanding and recognition which finds huge applications in agricultural productions. It also entails how rendering of machine learning techniques to computer vision algorithms is boosting this sector with better productivity by developing more precise systems. Computer vision and machine learning (CV-ML) helps in plant disease assessment along with crop condition monitoring to control the degradation of yield, quality, and severe financial loss for farmers. Significant scientific and technological advances have been made in defect assessment, quality grading, disease recognition, pests, insects, fruits, and vegetable types recognition and evaluation of a wide range of agricultural plants, crops, leaves, and fruits. The book discusses intelligent robots developed with the touch of CV-ML which can help farmers to perform various tasks like planting, weeding, harvesting, plant health monitoring, and so on. The topics covered in the book include plant, leaf, and fruit disease detection, crop health monitoring, applications of robots in agriculture, precision farming, assessment of product quality and defects, pest, insect, fruits, and vegetable types recognition. |
| computer science in agriculture: Deep Learning for Sustainable Agriculture Ramesh Chandra Poonia, Vijander Singh, Soumya Ranjan Nayak, 2022-01-09 The evolution of deep learning models, combined with with advances in the Internet of Things and sensor technology, has gained more importance for weather forecasting, plant disease detection, underground water detection, soil quality, crop condition monitoring, and many other issues in the field of agriculture. agriculture. Deep Learning for Sustainable Agriculture discusses topics such as the impactful role of deep learning during the analysis of sustainable agriculture data and how deep learning can help farmers make better decisions. It also considers the latest deep learning techniques for effective agriculture data management, as well as the standards established by international organizations in related fields. The book provides advanced students and professionals in agricultural science and engineering, geography, and geospatial technology science with an in-depth explanation of the relationship between agricultural inference and the decision-support amenities offered by an advanced mathematical evolutionary algorithm. - Introduces new deep learning models developed to address sustainable solutions for issues related to agriculture - Provides reviews on the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and mitigation of sustainable agriculture - Illustrates through case studies how deep learning has been used to address a variety of agricultural diseases that are currently on the cutting edge - Delivers an accessible explanation of artificial intelligence algorithms, making it easier for the reader to implement or use them in their own agricultural domain |
| computer science in agriculture: Computer Vision-Based Agriculture Engineering Han Zhongzhi, 2019-09-16 In recent years, computer vision is a fast-growing technique of agricultural engineering, especially in quality detection of agricultural products and food safety testing. It can provide objective, rapid, non-contact and non-destructive methods by extracting quantitative information from digital images. Significant scientific and technological advances have been made in quality inspection, classification and evaluation of a wide range of food and agricultural products. Computer Vision-Based Agriculture Engineering focuses on these advances. The book contains 25 chapters covering computer vision, image processing, hyperspectral imaging and other related technologies in peanut aflatoxin, peanut and corn quality varieties, and carrot and potato quality, as well as pest and disease detection. Features: Discusses various detection methods in a variety of agricultural crops Each chapter includes materials and methods used, results and analysis, and discussion with conclusions Covers basic theory, technical methods and engineering cases Provides comprehensive coverage on methods of variety identification, quality detection and detection of key indicators of agricultural products safety Presents information on technology of artificial intelligence including deep learning and transfer learning Computer Vision-Based Agriculture Engineering is a summary of the author's work over the past 10 years. Professor Han has presented his most recent research results in all 25 chapters of this book. This unique work provides students, engineers and technologists working in research, development, and operations in agricultural engineering with critical, comprehensive and readily accessible information. It applies development of artificial intelligence theory and methods including depth learning and transfer learning to the field of agricultural engineering testing. |
| computer science in agriculture: Internet of Things and Machine Learning in Agriculture Jyotir Moy Chatterjee, Abhishek Kumar, Pramod Singh Rathore, Vishal Jain, 2021-02-08 Agriculture is one of the most fundamental human activities. As the farming capacity has expanded, the usage of resources such as land, fertilizer, and water has grown exponentially, and environmental pressures from modern farming techniques have stressed natural landscapes. Still, by some estimates, worldwide food production needs to increase to keep up with global food demand. Machine Learning and the Internet of Things can play a promising role in the Agricultural industry, and help to increase food production while respecting the environment. This book explains how these technologies can be applied, offering many case studies developed in the research world. |
| computer science in agriculture: AI, Edge and IoT-based Smart Agriculture Ajith Abraham, Sujata Dash, Joel J.P.C. Rodrigues, Biswaranjan Acharya, Subhendu Kumar Pani, 2021-11-10 AI, Edge, and IoT Smart Agriculture integrates applications of IoT, edge computing, and data analytics for sustainable agricultural development and introduces Edge of Thing-based data analytics and IoT for predictability of crop, soil, and plant disease occurrence for improved sustainability and increased profitability. The book also addresses precision irrigation, precision horticulture, greenhouse IoT, livestock monitoring, IoT ecosystem for agriculture, mobile robot for precision agriculture, energy monitoring, storage management, and smart farming. The book provides an overarching focus on sustainable environment and sustainable economic development through smart and e-agriculture. Providing a medium for the exchange of expertise and inspiration, contributions from both smart agriculture and data mining researchers around the world provide foundational insights. The book provides practical application opportunities for the resolution of real-world problems, including contributions from the data mining, data analytics, Edge of Things, and cloud research communities working in the farming production sector. The book offers broad coverage of the concepts, themes, and instruments of this important and evolving area of IOT-based agriculture, Edge of Things and cloud-based farming, Greenhouse IOT, mobile agriculture, sustainable agriculture, and big data analytics in agriculture toward smart farming. - Integrates sustainable agriculture, Greenhouse IOT, precision agriculture, crops monitoring, crops controlling to prediction, livestock monitoring, and farm management - Presents data mining techniques for precision agriculture, including weather prediction, plant disease prediction, and decision support for crop and soil selection - Promotes the importance and uses in managing the agro ecosystem for food security - Emphasizes low energy usage options for low cost and environmental sustainability |
| computer science in agriculture: Applications of Image Processing and Soft Computing Systems in Agriculture Razmjooy, Navid, Estrela, Vania Vieira, 2019-02-22 The variety and abundance of qualitative characteristics of agricultural products have been the main reasons for the development of different types of non-destructive methods (NDTs). Quality control of these products is one of the most important tasks in manufacturing processes. The use of control and automation has become more widespread, and new approaches provide opportunities for production competition through new technologies. Applications of Image Processing and Soft Computing Systems in Agriculture examines applications of artificial intelligence in agriculture and the main uses of shape analysis on agricultural products such as relationships between form and genetics, adaptation, product characteristics, and product sorting. Additionally, it provides insights developed through computer vision techniques. Highlighting such topics as deep learning, agribusiness, and augmented reality, it is designed for academicians, researchers, agricultural practitioners, and industry professionals. |
| computer science in agriculture: Computer and Computing Technologies in Agriculture II, Volume 3 Daoliang Li, Chunjiang Zhao, 2010-02-03 The papers in this volume comprise the refereed proceedings of the Second IFIP International Conference on Computer and Computing Technologies in Agriculture (CCTA2008), in Beijing, China, 2008. The conference on the Second IFIP International Conference on Computer and Computing Technologies in Agriculture (CCTA 2008) is cooperatively sponsored and organized by the China Agricultural University (CAU), the National Engineering Research Center for Information Technology in Agriculture (NERCITA), the Chinese Society of Agricultural Engineering (CSAE) , International Federation for Information Processing (IFIP), Beijing Society for Information Technology in Agriculture, China and Beijing Research Center for Agro-products Test and Farmland Inspection, China. The related departments of China’s central government bodies like: Ministry of Science and Technology, Ministry of Industry and Information Technology, Ministry of Education and the Beijing Municipal Natural Science Foundation, Beijing Academy of Agricultural and Forestry Sciences, etc. have greatly contributed and supported to this event. The conference is as good platform to bring together scientists and researchers, agronomists and information engineers, extension servers and entrepreneurs from a range of disciplines concerned with impact of Information technology for sustainable agriculture and rural development. The representatives of all the supporting organizations, a group of invited speakers, experts and researchers from more than 15 countries, such as: the Netherlands, Spain, Portugal, Mexico, Germany, Greece, Australia, Estonia, Japan, Korea, India, Iran, Nigeria, Brazil, China, etc. |
| computer science in agriculture: Deep Learning Applications and Intelligent Decision Making in Engineering Senthilnathan, Karthikrajan, Shanmugam, Balamurugan, Goyal, Dinesh, Annapoorani, Iyswarya, Samikannu, Ravi, 2020-10-23 Deep learning includes a subset of machine learning for processing the unsupervised data with artificial neural network functions. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. When applied to engineering, deep learning can have a great impact on the decision-making process. Deep Learning Applications and Intelligent Decision Making in Engineering is a pivotal reference source that provides practical applications of deep learning to improve decision-making methods and construct smart environments. Highlighting topics such as smart transportation, e-commerce, and cyber physical systems, this book is ideally designed for engineers, computer scientists, programmers, software engineers, research scholars, IT professionals, academicians, and postgraduate students seeking current research on the implementation of automation and deep learning in various engineering disciplines. |
| computer science in agriculture: Cloud Computing Technologies for Smart Agriculture and Healthcare Urmila Shrawankar, Latesh Malik, Sandhya Arora, 2021-12-28 The Cloud is an advanced and fast-growing technology in the current era. The computing paradigm has changed drastically. It provided a new insight into the computing world with new characteristics including on-demand, virtualization, scalability and many more. Utility computing, virtualization and service-oriented architecture (SoA) are the key characteristics of Cloud computing. The Cloud provides distinct IT services over the web on a pay-as-you-go and on-demand basis. Cloud Computing Technologies for Smart Agriculture and Healthcare covers Cloud management and its framework. It also focuses how the Cloud computing framework can be integrated with applications based on agriculture and healthcare. Features: Contains a systematic overview of the state-of-the-art, basic theories, challenges, implementation, and case studies on Cloud technology Discusses of recent research results and future advancement in virtualization technology Focuses on core theories, architectures, and technologies necessary to develop and understand the computing models and its applications Includes a wide range of examples that uses Cloud technology for increasing farm profitability and sustainable production Presents the farming industry with Cloud technology that allows it toaggregate, analyze, and share data across farms and the world Includes Cloud-based electronic health records with privacy and security features Offers suitable IT solutions to the global issues in the domain of agriculture and health care for society This reference book is aimed at undergraduate and post-graduate programs. It will also help research scholars in their research work. This book also benefits like scientists, business innovators, entrepreneurs, professionals, and practitioners. |
| computer science in agriculture: Intelligent Data Mining and Fusion Systems in Agriculture Xanthoula-Eirini Pantazi, Dimitrios Moshou, Dionysis Bochtis, 2019-10-08 Intelligent Data Mining and Fusion Systems in Agriculture presents methods of computational intelligence and data fusion that have applications in agriculture for the non-destructive testing of agricultural products and crop condition monitoring. Sections cover the combination of sensors with artificial intelligence architectures in precision agriculture, including algorithms, bio-inspired hierarchical neural maps, and novelty detection algorithms capable of detecting sudden changes in different conditions. This book offers advanced students and entry-level professionals in agricultural science and engineering, geography and geoinformation science an in-depth overview of the connection between decision-making in agricultural operations and the decision support features offered by advanced computational intelligence algorithms. - Covers crop protection, automation in agriculture, artificial intelligence in agriculture, sensing and Internet of Things (IoTs) in agriculture - Addresses AI use in weed management, disease detection, yield prediction and crop production - Utilizes case studies to provide real-world insights and direction |
| computer science in agriculture: Artificial Intelligence and IoT-Based Technologies for Sustainable Farming and Smart Agriculture Tomar, Pradeep, Kaur, Gurjit, 2021-01-08 As technology continues to saturate modern society, agriculture has started to adopt digital computing and data-driven innovations. This emergence of “smart” farming has led to various advancements in the field, including autonomous equipment and the collection of climate, livestock, and plant data. As connectivity and data management continue to revolutionize the farming industry, empirical research is a necessity for understanding these technological developments. Artificial Intelligence and IoT-Based Technologies for Sustainable Farming and Smart Agriculture provides emerging research exploring the theoretical and practical aspects of critical technological solutions within the farming industry. Featuring coverage on a broad range of topics such as crop monitoring, precision livestock farming, and agronomic data processing, this book is ideally designed for farmers, agriculturalists, product managers, farm holders, manufacturers, equipment suppliers, industrialists, governmental professionals, researchers, academicians, and students seeking current research on technological applications within agriculture and farming. |
| computer science in agriculture: Computer and Computing Technologies in Agriculture II, Volume 1 Daoliang Li, Chunjiang Zhao, 2009-06-12 The papers in this volume comprise the refereed proceedings of the Second IFIP International Conference on Computer and Computing Technologies in Agriculture (CCTA2008), in Beijing, China, 2008. The conference on the Second IFIP International Conference on Computer and Computing Technologies in Agriculture (CCTA 2008) is cooperatively sponsored and organized by the China Agricultural University (CAU), the National Engineering Research Center for Information Technology in Agriculture (NERCITA), the Chinese Society of Agricultural Engineering (CSAE) , International Federation for Information Processing (IFIP), Beijing Society for Information Technology in Agriculture, China and Beijing Research Center for Agro-products Test and Farmland Inspection, China. The related departments of China’s central government bodies like: Ministry of Science and Technology, Ministry of Industry and Information Technology, Ministry of Education and the Beijing Municipal Natural Science Foundation, Beijing Academy of Agricultural and Forestry Sciences, etc. have greatly contributed and supported to this event. The conference is as good platform to bring together scientists and researchers, agronomists and information engineers, extension servers and entrepreneurs from a range of disciplines concerned with impact of Information technology for sustainable agriculture and rural development. The representatives of all the supporting organizations, a group of invited speakers, experts and researchers from more than 15 countries, such as: the Netherlands, Spain, Portugal, Mexico, Germany, Greece, Australia, Estonia, Japan, Korea, India, Iran, Nigeria, Brazil, China, etc. |
| computer science in agriculture: Artificial Intelligence in Agriculture Rajesh Singh, Anita Gehlot, Mahesh Kumar Prajapat, Bhupendra Singh, 2021-11-23 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. 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. This book also covers the basics of python with example so that any anyone can easily understand and utilize artificial intelligence in agriculture field. This book is divided into two parts wherein first part talks about the artificial intelligence and its impact in the agriculture with all its branches and their basics. The second part of the book is purely implementation of algorithms and use of different libraries of machine learning, deep learning and computer vision to build useful and sightful projects in real time which can be very useful for you to have better understanding of artificial intelligence. After reading this book, the reader will an understanding of what Artificial Intelligence is, where it is applicable, and what are its different branches, which can be useful in different scenarios. The reader will be familiar with the standard workflow for approaching and solving machine-learning problems, and how to address commonly encountered issues. The reader will be able to use Artificial Intelligence to tackle real-world problems ranging from crop health prediction to field surveillance analytics, classification to recognition of species of plants etc. Note: T&F does not sell or distribute the hardback in India, Pakistan, Nepal, Bhutan, Bangladesh and Sri Lanka. This title is co-published with NIPA. |
| computer science in agriculture: Improving Data Management and Decision Support Systems in Agriculture Leisa Armstrong, 2020-03-24 Part 1 reviews general issues underpinning effective decision support systems (DSS) such as data access, standards, tagging and security. Part 2 contains case studies of the practical application of DSS in areas such as crop planting and nutrition, livestock feed and pasture management as well as supply chains. |
| computer science in agriculture: Computer and Computing Technologies in Agriculture II, Volume 2 Daoliang Li, Chunjiang Zhao, 2009-06-12 The papers in this volume comprise the refereed proceedings of the Second IFIP International Conference on Computer and Computing Technologies in Agriculture (CCTA2008), in Beijing, China, 2008. The conference on the Second IFIP International Conference on Computer and Computing Technologies in Agriculture (CCTA 2008) is cooperatively sponsored and organized by the China Agricultural University (CAU), the National Engineering Research Center for Information Technology in Agriculture (NERCITA), the Chinese Society of Agricultural Engineering (CSAE) , International Federation for Information Processing (IFIP), Beijing Society for Information Technology in Agriculture, China and Beijing Research Center for Agro-products Test and Farmland Inspection, China. The related departments of China’s central government bodies like: Ministry of Science and Technology, Ministry of Industry and Information Technology, Ministry of Education and the Beijing Municipal Natural Science Foundation, Beijing Academy of Agricultural and Forestry Sciences, etc. have greatly contributed and supported to this event. The conference is as good platform to bring together scientists and researchers, agronomists and information engineers, extension servers and entrepreneurs from a range of disciplines concerned with impact of Information technology for sustainable agriculture and rural development. The representatives of all the supporting organizations, a group of invited speakers, experts and researchers from more than 15 countries, such as: the Netherlands, Spain, Portugal, Mexico, Germany, Greece, Australia, Estonia, Japan, Korea, India, Iran, Nigeria, Brazil, China, etc. |
| computer science in agriculture: Agricultural Informatics Amitava Choudhury, Arindam Biswas, Manish Prateek, Amlan Chakrabarti, 2021-04-06 Despite the increasing population (the Food and Agriculture Organization of the United Nations estimates 70% more food will be needed in 2050 than was produced in 2006), issues related to food production have yet to be completely addressed. In recent years, Internet of Things technology has begun to be used to address different industrial and technical challenges to meet this growing need. These Agro-IoT tools boost productivity and minimize the pitfalls of traditional farming, which is the backbone of the world's economy. Aided by the IoT, continuous monitoring of fields provides useful and critical information to farmers, ushering in a new era in farming. The IoT can be used as a tool to combat climate change through greenhouse automation; monitor and manage water, soil and crops; increase productivity; control insecticides/pesticides; detect plant diseases; increase the rate of crop sales; cattle monitoring etc. Agricultural Informatics: Automation Using the IoT and Machine Learning focuses on all these topics, including a few case studies, and they give a clear indication as to why these techniques should now be widely adopted by the agriculture and farming industries. |
| computer science in agriculture: Modern Techniques for Agricultural Disease Management and Crop Yield Prediction Pradeep, N., Kautish, Sandeep, Nirmala, C.R., Goyal, Vishal, Abdellatif, Sonia, 2019-08-16 Since agriculture is one of the key parameters in assessing the gross domestic product (GDP) of any country, it has become crucial to transition from traditional agricultural practices to smart agriculture. New agricultural technologies provide numerous opportunities to maximize crop yield by recognizing and analyzing diseases and other natural variables that may affect it. Therefore, it is necessary to understand how computer-assisted technologies can best be utilized and adopted in the conversion to smart agriculture. Modern Techniques for Agricultural Disease Management and Crop Yield Prediction is an essential publication that widens the spectrum of computational methods that can aid in agriculture disease management, weed detection, and crop yield prediction. Featuring coverage on a wide range of topics such as soil and crop sensors, swarm robotics, and weed detection, this book is ideally designed for environmentalists, farmers, botanists, agricultural engineers, computer engineers, scientists, researchers, practitioners, and students seeking current research on technology and techniques for agricultural diseases and predictive trends. |
| computer science in agriculture: Internet of Things for Agriculture 4.0 Rajesh Singh, Amit Kumar Thakur, Anita Gehlot, Ajay Kumar Kaviti, 2022-02-24 This new book provides an insightful look at the varied and exciting uses and applications of Wi-Fi and the Internet of Things in agriculture. With internet-enabled communications becoming more widely available, farms and agricultural establishments can take advantage of these new technologies for a wide range of farm operations, such as crop management, farm vehicle tracking, livestock monitoring, storage monitoring, and more. The collected data from these devices can be stored in the cloud system or server and accessed by the farmers via the internet or mobile phones. This book shows the many benefits to farmers from applying IoT, including better utilizing information for monitoring crops, optimizing water use, planning effective fertilization strategies, and saving time and reducing the operation expenses. Topics include using IoT for vertical farming, IoT-based smart irrigation system, landslide susceptibility assessment, automated aeroponics systems, crop survival analysis, and more. The volume also considers the challenges of IoT in agriculture, such as the requirements of applications of wireless sensor networks, the threat of attacks and the detection of vulnerabilities in wireless sensor networks, and more. Internet of Things for Agriculture 4.0: Impact and Challenges provides a better understanding of the time- and resourcing-saving benefits of wireless sensors and remote monitoring devices in agriculture. The volume will be useful for those involved in agricultural operations as well as scientists and researchers, and faculty and students in agriculture and computer and information science engineering. |
| computer science in agriculture: Innovations in the Industrial Internet of Things (IIoT) and Smart Factory Goundar, Sam, Avanija, J., Sunitha, Gurram, Madhavi, K. Reddy, Bhushan, S. Bharath, 2021-01-22 Industrial internet of things (IIoT) is changing the face of industry by completely redefining the way stakeholders, enterprises, and machines connect and interact with each other in the industrial digital ecosystem. Smart and connected factories, in which all the machinery transmits real-time data, enable industrial data analytics for improving operational efficiency, productivity, and industrial processes, thus creating new business opportunities, asset utilization, and connected services. IIoT leads factories to step out of legacy environments and arcane processes towards open digital industrial ecosystems. Innovations in the Industrial Internet of Things (IIoT) and Smart Factory is a pivotal reference source that discusses the development of models and algorithms for predictive control of industrial operations and focuses on optimization of industrial operational efficiency, rationalization, automation, and maintenance. While highlighting topics such as artificial intelligence, cyber security, and data collection, this book is ideally designed for engineers, manufacturers, industrialists, managers, IT consultants, practitioners, students, researchers, and industrial industry professionals. |
| computer science in agriculture: AI-Based Services for Smart Cities and Urban Infrastructure Lyu, Kangjuan, Hu, Min, Du, Juan, Sugumaran, Vijayan, 2020-09-04 Cities are the next frontier for artificial intelligence to permeate. As smart urban environments become possible, probable, and even preferred, artificial intelligence offers the chance for even further advancement through infrastructure and industry boosting. Opportunity overflows, but without thorough research to guide a complicated development and implementation process, urban environments can become disorganized and outright dangerous for citizens. AI-Based Services for Smart Cities and Urban Infrastructure is a collection of innovative research that explores artificial intelligence (AI) applications in urban planning. In addition, the book looks at how the internet of things and AI can work together to enable a real smart city and discusses state-of-the-art techniques in urban infrastructure design, construction, operation, maintenance, and management. While highlighting a broad range of topics including construction management, public transportation, and smart agriculture, this book is ideally designed for engineers, entrepreneurs, urban planners, architects, policymakers, researchers, academicians, and students. |
| computer science in agriculture: Rethinking Food and Agriculture Amir Kassam, Laila Kassam, 2020-10-18 Given the central role of the food and agriculture system in driving so many of the connected ecological, social and economic threats and challenges we currently face, Rethinking Food and Agriculture reviews, reassesses and reimagines the current food and agriculture system and the narrow paradigm in which it operates. Rethinking Food and Agriculture explores and uncovers some of the key historical, ethical, economic, social, cultural, political, and structural drivers and root causes of unsustainability, degradation of the agricultural environment, destruction of nature, short-comings in science and knowledge systems, inequality, hunger and food insecurity, and disharmony. It reviews efforts towards 'sustainable development', and reassesses whether these efforts have been implemented with adequate responsibility, acceptable societal and environmental costs and optimal engagement to secure sustainability, equity and justice. The book highlights the many ways that farmers and their communities, civil society groups, social movements, development experts, scientists and others have been raising awareness of these issues, implementing solutions and forging 'new ways forward', for example towards paradigms of agriculture, natural resource management and human nutrition which are more sustainable and just. Rethinking Food and Agriculture proposes ways to move beyond the current limited view of agro-ecological sustainability towards overall sustainability of the food and agriculture system based on the principle of 'inclusive responsibility'. Inclusive responsibility encourages ecosystem sustainability based on agro-ecological and planetary limits to sustainable resource use for production and livelihoods. Inclusive responsibility also places importance on quality of life, pluralism, equity and justice for all and emphasises the health, well-being, sovereignty, dignity and rights of producers, consumers and other stakeholders, as well as of nonhuman animals and the natural world. - Explores some of the key drivers and root causes of unsustainability , degradation of the agricultural environment and destruction of nature - Highlights the many ways that different stakeholders have been forging 'new ways forward' towards alternative paradigms of agriculture, human nutrition and political economy, which are more sustainable and just - Proposes ways to move beyong the current unsustainable exploitation of natural resources towards agroecological sustainability and overall sustainability of the food and agriculture system based on 'inclusive responsibility' |
| computer science in agriculture: The Digital Agricultural Revolution Roheet Bhatnagar, Nitin Kumar Tripathi, Nitu Bhatnagar, Chandan Kumar Panda, 2022-06-15 THE DIGITAL AGRICULTURAL REVOLUTION The book integrates computational intelligence, applied artificial intelligence, and modern agricultural practices and will appeal to scientists, agriculturists, and those in plant and crop science management. There is a need for synergy between the application of modern scientific innovation in the area of artificial intelligence and agriculture, considering the major challenges from climate change consequences viz. rising temperatures, erratic rainfall patterns, the emergence of new crop pests, drought, flood, etc. This volume reports on high-quality research (theory and practice including prototype & conceptualization of ideas, frameworks, real-world applications, policy, standards, psychological concerns, case studies, and critical surveys) on recent advances toward the realization of the digital agriculture revolution as a result of the convergence of different disruptive technologies. The book touches upon the following topics which have contributed to revolutionizing agricultural practices. Applications of Artificial Intelligence in Agriculture (AI models and architectures, system design, real-world applications of AI, machine learning and deep learning in the agriculture domain, integration & coordination of systems and issues & challenges). IoT and Big Data Analytics Applications in Agriculture (theory & architecture and the use of various types of sensors in optimizing agriculture resources and final product, benefits in real-time for crop acreage estimation, monitoring & control of agricultural produce). Robotics & Automation in Agriculture Systems (Automation challenges, need and recent developments and real case studies). Intelligent and Innovative Smart Agriculture Applications (use of hybrid intelligence in better crop health and management). Privacy, Security, and Trust in Digital Agriculture (government framework & policy papers). Open Problems, Challenges, and Future Trends. Audience Researchers in computer science, artificial intelligence, electronics engineering, agriculture automation, crop management, and science. |
| computer science in agriculture: Smart Agriculture Govind Singh Patel, Amrita Rai, Nripendra Narayan Das, R.P. Singh, 2021-02-10 This book endeavours to highlight the untapped potential of Smart Agriculture for the innovation and expansion of the agriculture sector. The sector shall make incremental progress as it learns from associations between data over time through Artificial Intelligence, deep learning and Internet of Things applications. The farming industry and Smart agriculture develop from the stringent limits imposed by a farm's location, which in turn has a series of related effects with respect to supply chain management, food availability, biodiversity, farmers' decision-making and insurance, and environmental concerns among others. All of the above-mentioned aspects will derive substantial benefits from the implementation of a data-driven approach under the condition that the systems, tools and techniques to be used have been designed to handle the volume and variety of the data to be gathered. Contributions to this book have been solicited with the goal of uncovering the possibilities of engaging agriculture with equipped and effective profound learning algorithms. Most agricultural research centres are already adopting Internet of Things for the monitoring of a wide range of farm services, and there are significant opportunities for agriculture administration through the effective implementation of Machine Learning, Deep Learning, Big Data and IoT structures. |
| computer science in agriculture: Cloud IoT Systems for Smart Agricultural Engineering Saravanan Krishnan, J. Bruce Ralphin Rose, N. R. Rajalakshmi, N. Narayanan Prasanth, 2022 Agriculture plays a vital role in a country's growth. Modern-day technologies drive every domain toward smart systems. The use of traditional agricultural procedures to satisfy modern-day requirements is a challenging task. Cloud IoT Systems for Smart Agricultural Engineering provides substantial coverage of various challenges of the agriculture domain through modern technologies such as the Internet of Things (IoT), cloud computing, and many more. This book offers various state-of-the-art procedures to be deployed in a wide range of agricultural activities. The concepts are discussed with the necessary implementations and clear examples. Necessary illustrations are depicted in the chapters to ensure the effective delivery of the proposed concepts. It presents the rapid advancement of the technologies in the existing agricultural model by applying the cloud IoT techniques. A wide variety of novel architectural solutions are discussed in various chapters of this book. This book provides comprehensive coverage of the most essential topics, including: New approaches on urban and vertical farming Smart crop management for Indian farmers Smart livestock management Precision agriculture using geographical information systems Machine learning techniques combined with IoT for smart agriculture Effective use of drones in smart agriculture This book provides solutions for the diverse domain of problems in agricultural engineering. It can be used at the basic and intermediary levels for agricultural science and engineering graduate students, researchers, and practitioners. |
| computer science in agriculture: IoT and Analytics for Agriculture Prasant Kumar Pattnaik, Raghvendra Kumar, Souvik Pal, S. N. Panda, 2019-10-01 This book presents recent findings on virtually every aspect of wireless IoT and analytics for agriculture. It discusses IoT-based monitoring systems for analyzing the crop environment, and methods for improving the efficiency of decision-making based on the analysis of harvest statistics. In turn, it addresses the latest innovations, trends, and concerns, as well as practical challenges encountered and solutions adopted in the fields of IoT and analytics for agriculture. In closing, it explores a range of applications, including: intelligent field monitoring, intelligent data processing and sensor technologies, predictive analysis systems, crop monitoring, and weather data-enabled analysis in IoT agro-systems. |
| computer science in agriculture: Science Breakthroughs to Advance Food and Agricultural Research by 2030 National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Board on Environmental Change and Society, Health and Medicine Division, Food and Nutrition Board, Division on Earth and Life Studies, Water Science and Technology Board, Board on Life Sciences, Board on Atmospheric Sciences and Climate, Board on Agriculture and Natural Resources, Committee on Science Breakthroughs 2030: A Strategy for Food and Agricultural Research, 2019-04-21 For nearly a century, scientific advances have fueled progress in U.S. agriculture to enable American producers to deliver safe and abundant food domestically and provide a trade surplus in bulk and high-value agricultural commodities and foods. Today, the U.S. food and agricultural enterprise faces formidable challenges that will test its long-term sustainability, competitiveness, and resilience. On its current path, future productivity in the U.S. agricultural system is likely to come with trade-offs. The success of agriculture is tied to natural systems, and these systems are showing signs of stress, even more so with the change in climate. More than a third of the food produced is unconsumed, an unacceptable loss of food and nutrients at a time of heightened global food demand. Increased food animal production to meet greater demand will generate more greenhouse gas emissions and excess animal waste. The U.S. food supply is generally secure, but is not immune to the costly and deadly shocks of continuing outbreaks of food-borne illness or to the constant threat of pests and pathogens to crops, livestock, and poultry. U.S. farmers and producers are at the front lines and will need more tools to manage the pressures they face. Science Breakthroughs to Advance Food and Agricultural Research by 2030 identifies innovative, emerging scientific advances for making the U.S. food and agricultural system more efficient, resilient, and sustainable. This report explores the availability of relatively new scientific developments across all disciplines that could accelerate progress toward these goals. It identifies the most promising scientific breakthroughs that could have the greatest positive impact on food and agriculture, and that are possible to achieve in the next decade (by 2030). |
| computer science in agriculture: Agriculture and Environment Perspectives in Intelligent Systems A. Muñoz, J. Park, 2019-06-20 The eventual aim when applying digital technologies in agriculture is to replace or reduce the human labor required for agricultural production. Large amounts of heterogeneous data are essential for integration studies of automated agriculture, and the digitalization of agriculture is helping to fulfill the demand for this data, but management of the data gathered presents its own challenges. That is where the Intelligent Environment (IE) paradigm comes into play to guide the design of the systems, techniques and algorithms able to analyze the data and provide recommendations for farmers, managers and other stakeholders. This book, Agriculture and Environment Perspectives in Intelligent Systems, is divided into 5 chapters. Chapter 1 explores the use of intelligent systems in Controlled Environment Agriculture (CEA) facilities; Chapter 2 reviews the adoption of intelligent systems in the research field of biomonitoring; Chapter 3 proposes an intelligent system to acquire and pre-process data for precision agriculture applications; Chapter 4 illustrates the use of intelligent algorithms to make more efficient use of scarce resources such as water; and Chapter 5 focuses on the generation of intelligent models to predict frosts in crops in south-eastern Spain. There is still a need to bridge the gap between the needs of farmers, environmental managers and stakeholders and the solutions offered by information and communication technology. This book will be of interest to all those working in the field. |
| computer science in agriculture: Computer and Computing Technologies in Agriculture, Volume II Daoliang Li, 2010-11-19 The papers in this volume comprise the refereed proceedings of the First Int- national Conference on Computer and Computing Technologies in Agriculture (CCTA 2007), in Wuyishan, China, 2007. This conference is organized by China Agricultural University, Chinese Society of Agricultural Engineering and the Beijing Society for Information Technology in Agriculture. The purpose of this conference is to facilitate the communication and cooperation between institutions and researchers on theories, methods and implementation of computer science and information technology. By researching information technology development and the - sources integration in rural areas in China, an innovative and effective approach is expected to be explored to promote the technology application to the development of modern agriculture and contribute to the construction of new countryside. The rapid development of information technology has induced substantial changes and impact on the development of China’s rural areas. Western thoughts have exerted great impact on studies of Chinese information technology devel- ment and it helps more Chinese and western scholars to expand their studies in this academic and application area. Thus, this conference, with works by many prominent scholars, has covered computer science and technology and information development in China’s rural areas; and probed into all the important issues and the newest research topics, such as Agricultural Decision Support System and Expert System, GIS, GPS, RS and Precision Farming, CT applications in Rural Area, Agricultural System Simulation, Evolutionary Computing, etc. |
| computer science in agriculture: Computers In Agriculture Manish Kumar Sharma, Anil Bhat, M. Iqbal Jeelani Bhat, 2016-10-20 Computer applications are gaining importance in recent times with the growth and development of electronic, communication, information technology and computer industry. The book is designed in such a way that it not only serves as comprehensive knowledge base, but also helps the readers in understanding the fundamentals of computer applications. The book also explains data analysis using Ms-Excel which gives opportunity to the students to analyze their statistical research data. Starting with an introductory chapter, the book goes to cover all topics of computers as well as use of statistical tools in solving the problems. First chapter gives an introduction to computers. This chapter provides an overview of anatomy, generation and classification of computers. In addition to this, it discusses about the personal computers, booting and viruses. Second chapter entitled “Operating Systems” describes about disk operating system and its commands. Chapter three discusses Working in Windows. Chapter four describes word processing and creating, saving, opening and editing a document. Besides formatting options has also been described in chapter four. Introduction to Ms-Excel and creating, editing and saving a document are explained in chapter five and chapter six. Chapter seven describes Mathematical Functions and their use in excel. The various features of data analysis using excel which deals with data analysis tools, tests, graphs and ANOVA along with illustrated examples are described in chapter eight and nine. The tenth chapter introduces the reader with Ms-Access database. Chapter number eleven gives the basic concepts of internet. Chapter number twelve discusses with pictures flow chart and algorithm. |
| computer science in agriculture: Push Button Agriculture K. R. Krishna, 2017-03-16 This book covers three main types of agricultural systems: the use of robotics, drones (unmanned aerial vehicles), and satellite-guided precision farming methods. Some of these are well refined and are currently in use, while others are in need of refinement and are yet to become popular. The book provides a valuable source of information on this developing field for those involved with agriculture and farming and agricultural engineering. The book is also applicable as a textbook for students and a reference for faculty. |
| computer science in agriculture: Progress in Agricultural Physics and Engineering John Matthews, 1991 The physical sciences and engineering play an important part in the advance and activities of agriculture and related industries and in the preservation and improvement of rural and amenity environments. This book provides an account of new developments in these disciplines as applied to such industries. Chapters have been commissioned on topics perceived to have made important recent advances, and these are reviewed. The book should therefore be of interest to research workers, lecturers and professionals in agricultural engineering and applied aspects of soil science, horticulture, food science and other disciplines. |
| computer science in agriculture: Computational Methods for Agricultural Research: Advances and Applications do Prado, Hrcules Antonio, Barreto Luiz, Alfredo Jose, Filho, Homero Chaib, 2010-10-31 This book brings computing solutions to ancient practices and modern concerns, sowing the seeds for a sustainable, constant food supply, utilizing cutting-edge computational techniques--Provided by publisher. |
| computer science in agriculture: Agriculture 5.0 Latief Ahmad, Firasath Nabi, 2021-03-24 Agriculture 5.0: Artificial Intelligence, IoT & Machine Learning provides an interdisciplinary, integrative overview of latest development in the domain of smart farming. It shows how the traditional farming practices are being enhanced and modified by automation and introduction of modern scalable technological solutions that cut down on risks, enhance sustainability, and deliver predictive decisions to the grower, in order to make agriculture more productive. An elaborative approach has been used to highlight the applicability and adoption of key technologies and techniques such WSN, IoT, AI and ML in agronomic activities ranging from collection of information, analysing and drawing meaningful insights from the information which is more accurate, timely and reliable.It synthesizes interdisciplinary theory, concepts, definitions, models and findings involved in complex global sustainability problem-solving, making it an essential guide and reference. It includes real-world examples and applications making the book accessible to a broader interdisciplinary readership. This book clarifies hoe the birth of smart and intelligent agriculture is being nurtured and driven by the deployment of tiny sensors or AI/ML enabled UAV’s or low powered Internet of Things setups for the sensing, monitoring, collection, processing and storing of the information over the cloud platforms. This book is ideal for researchers, academics, post-graduate students and practitioners of agricultural universities, who want to embrace new agricultural technologies for Determination of site-specific crop requirements, future farming strategies related to controlling of chemical sprays, yield, price assessments with the help of AI/ML driven intelligent decision support systems and use of agri-robots for sowing and harvesting. The book will be covering and exploring the applications and some case studies of each technology, that have heavily made impact as grand successes. The main aim of the book is to give the readers immense insights into the impact and scope of WSN, IoT, AI and ML in the growth of intelligent digital farming and Agriculture revolution 5.0.The book also focuses on feasibility of precision farming and the problems faced during adoption of precision farming techniques, its potential in India and various policy measures taken all over the world. The reader can find a description of different decision support tools like crop simulation models, their types, and application in PA. Features: Detailed description of the latest tools and technologies available for the Agriculture 5.0. Elaborative information for different type of hardware, platforms and machine learning techniques for use in smart farming. Elucidates various types of predictive modeling techniques available for intelligent and accurate agricultural decision making from real time collected information for site specific precision farming. Information about different type of regulations and policies made by all over the world for the motivation farmers and innovators to invest and adopt the AI and ML enabled tools and farming systems for sustainable production. |
| computer science in agriculture: Handbook of Intelligent Computing and Optimization for Sustainable Development Mukhdeep Singh Manshahia, Valeriy Kharchenko, Elias Munapo, J. Joshua Thomas, Pandian Vasant, 2022-02-11 HANDBOOK OF INTELLIGENT COMPUTING AND OPTIMIZATION FOR SUSTAINABLE DEVELOPMENT This book provides a comprehensive overview of the latest breakthroughs and recent progress in sustainable intelligent computing technologies, applications, and optimization techniques across various industries. Optimization has received enormous attention along with the rapidly increasing use of communication technology and the development of user-friendly software and artificial intelligence. In almost all human activities, there is a desire to deliver the highest possible results with the least amount of effort. Moreover, optimization is a very well-known area with a vast number of applications, from route finding problems to medical treatment, construction, finance, accounting, engineering, and maintenance schedules in plants. As far as optimization of real-world problems is concerned, understanding the nature of the problem and grouping it in a proper class may help the designer employ proper techniques which can solve the problem efficiently. Many intelligent optimization techniques can find optimal solutions without the use of objective function and are less prone to local conditions. The 41 chapters comprising the Handbook of Intelligent Computing and Optimization for Sustainable Development by subject specialists, represent diverse disciplines such as mathematics and computer science, electrical and electronics engineering, neuroscience and cognitive sciences, medicine, and social sciences, and provide the reader with an integrated understanding of the importance that intelligent computing has in the sustainable development of current societies. It discusses the emerging research exploring the theoretical and practical aspects of successfully implementing new and innovative intelligent techniques in a variety of sectors, including IoT, manufacturing, optimization, and healthcare. Audience It is a pivotal reference source for IT specialists, industry professionals, managers, executives, researchers, scientists, and engineers seeking current research in emerging perspectives in the field of artificial intelligence in the areas of Internet of Things, renewable energy, optimization, and smart cities. |
| computer science in agriculture: Application of Machine Learning in Agriculture Mohammad Ayoub Khan, Rijwan Khan, Mohammad Aslam Ansari, 2022-05-14 Application of Machine Learning in Smart Agriculture is the first book to present a multidisciplinary look at how technology can not only improve agricultural output, but the economic efficiency of that output as well. Through a global lens, the book approaches the subject from a technical perspective, providing important knowledge and insights for effective and efficient implementation and utilization of machine learning. As artificial intelligence techniques are being used to increase yield through optimal planting, fertilizing, irrigation, and harvesting, these are only part of the complex picture which must also take into account the economic investment and its optimized return. The performance of machine learning models improves over time as the various mathematical and statistical models are proven. Presented in three parts, Application of Machine Learning in Smart Agriculture looks at the fundamentals of smart agriculture; the economics of the technology in the agricultural marketplace; and a diverse representation of the tools and techniques currently available, and in development. This book is an important resource for advanced level students and professionals working with artificial intelligence, internet of things, technology and agricultural economics. - Addresses the technology of smart agriculture from a technical perspective - Reveals opportunities for technology to improve and enhance not only yield and quality, but the economic value of a food crop - Discusses physical instruments, simulations, sensors, and markets for machine learning in agriculture |
| computer science in agriculture: The Convergent Evolution of Agriculture in Humans and Insects Ted R Schultz, Richard Gawne, Peter N Peregrine, 2022-02-22 Contributors explore common elements in the evolutionary histories of both human and insect agriculture resulting from convergent evolution. During the past 12,000 years, agriculture originated in humans as many as twenty-three times, and during the past 65 million years, agriculture also originated in nonhuman animals at least twenty times and in insects at least fifteen times. It is much more likely that these independent origins represent similar solutions to the challenge of growing food than that they are due purely to chance. This volume seeks to identify common elements in the evolutionary histories of both human and insect agriculture that are the results of convergent evolution. The goal is to create a new, synthetic field that characterizes, quantifies, and empirically documents the evolutionary and ecological mechanisms that drive both human and nonhuman agriculture. The contributors report on the results of quantitative analyses comparing human and nonhuman agriculture; discuss evolutionary conflicts of interest between and among farmers and cultivars and how they interfere with efficiencies of agricultural symbiosis; describe in detail agriculture in termites, ambrosia beetles, and ants; and consider patterns of evolutionary convergence in different aspects of agriculture, comparing fungal parasites of ant agriculture with fungal parasites of human agriculture, analyzing the effects of agriculture on human anatomy, and tracing the similarities and differences between the evolution of agriculture in humans and in a single, relatively well-studied insect group, fungus-farming ants. |
| computer science in agriculture: Of Computers, Myths and Modelling Cees Leeuwis, 1993 |
| computer science in agriculture: Computer and Computing Technologies in Agriculture, Volume I Daoliang Li, 2008-02-26 The papers in this volume comprise the refereed proceedings of the the First International Conference on Computer and Computing Technologies in Ag- culture (CCTA 2007), in Wuyishan, China, 2007. This conference is organized by China Agricultural University, Chinese Society of Agricultural Engineering and the Beijing Society for Information Technology in Agriculture. The purpose of this conference is to facilitate the communication and cooperation between institutions and researchers on theories, methods and implementation of computer science and information technology. By researching information technology development and the - sources integration in rural areas in China, an innovative and effective approach is expected to be explored to promote the technology application to the development of modern agriculture and contribute to the construction of new countryside. The rapid development of information technology has induced substantial changes and impact on the development of China’s rural areas. Western thoughts have exerted great impact on studies of Chinese information technology devel- ment and it helps more Chinese and western scholars to expand their studies in this academic and application area. Thus, this conference, with works by many prominent scholars, has covered computer science and technology and information development in China’s rural areas; and probed into all the important issues and the newest research topics, such as Agricultural Decision Support System and Expert System, GIS, GPS, RS and Precision Farming, CT applications in Rural Area, Agricultural System Simulation, Evolutionary Computing, etc. |
| computer science in agriculture: Computer and Computing Technologies in Agriculture, Volume I Daoliang Li, 2010-11-23 The papers in this volume comprise the refereed proceedings of the the First International Conference on Computer and Computing Technologies in Ag- culture (CCTA 2007), in Wuyishan, China, 2007. This conference is organized by China Agricultural University, Chinese Society of Agricultural Engineering and the Beijing Society for Information Technology in Agriculture. The purpose of this conference is to facilitate the communication and cooperation between institutions and researchers on theories, methods and implementation of computer science and information technology. By researching information technology development and the - sources integration in rural areas in China, an innovative and effective approach is expected to be explored to promote the technology application to the development of modern agriculture and contribute to the construction of new countryside. The rapid development of information technology has induced substantial changes and impact on the development of China’s rural areas. Western thoughts have exerted great impact on studies of Chinese information technology devel- ment and it helps more Chinese and western scholars to expand their studies in this academic and application area. Thus, this conference, with works by many prominent scholars, has covered computer science and technology and information development in China’s rural areas; and probed into all the important issues and the newest research topics, such as Agricultural Decision Support System and Expert System, GIS, GPS, RS and Precision Farming, CT applications in Rural Area, Agricultural System Simulation, Evolutionary Computing, etc. |
Computer - Wikipedia
A computer is a machine that can be programmed to automatically carry out sequences of arithmetic or logical operations (computation). Modern digital electronic computers can …
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A computer is a programmable device for processing, storing, and displaying information. Learn more in this article about modern digital electronic computers and their design, constituent …
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What is a computer? A computer is an electronic device that manipulates information, or data. It has the ability to store, retrieve, and process data. You may already know that you can use a …
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Oct 9, 2024 · A computer is a programmable machine that responds to specific instructions and uses hardware and software to perform tasks. Different types of computers, including …
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What is Computer? Definition, Characteristics and Classification
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Computer - Wikipedia
A computer is a machine that can be programmed to automatically carry out sequences of arithmetic or logical operations (computation). Modern digital electronic computers can …
Computer | Definition, History, Operating Systems, & Facts
A computer is a programmable device for processing, storing, and displaying information. Learn more in this article about modern digital electronic computers and their design, constituent …
What is a Computer?
Feb 6, 2025 · What is a Computer? A computer is a programmable device that stores, retrieves, and processes data. The term "computer" was originally given to humans (human computers) …
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Shop Micro Center for electronics, PCs, laptops, Apple products, and much more. Enjoy in-store pickup, top deals, and expert same-day tech support.
What is a Computer? - GeeksforGeeks
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Computer Basics: What is a Computer? - GCFGlobal.org
What is a computer? A computer is an electronic device that manipulates information, or data. It has the ability to store, retrieve, and process data. You may already know that you can use a …
What is a Computer? (Definition & Meaning) - Webopedia
Oct 9, 2024 · A computer is a programmable machine that responds to specific instructions and uses hardware and software to perform tasks. Different types of computers, including …
Computer - Simple English Wikipedia, the free encyclopedia
A computer is a machine that uses electronics to input, process, store, and output data. Data is information such as numbers, words, and lists. Input of data means to read information from a …
Laptop & Desktop Computers - Staples
Buy the computer that fits your exact needs. Choose from laptops, desktops PCs, notebooks, and accessories. Invest in a quality computer for work or personal use.
What is Computer? Definition, Characteristics and Classification
Aug 7, 2024 · A computer is an electronic device wherein we need to input raw data to be processed with a set of programs to produce a desirable output. Computers have the ability to …
