Digital Agritechnology

Digital Agritechnology: Robotics and Systems for Agriculture and Livestock Production describes how systems acquire and use data in livestock production and agricultural systems, and how researchers can extract and aggregate efficiencies. The origins of digital agritechnology are decades old, with robotic milkers available for over 20 years and GPS-based tractor controls existing for nearly 30. However, only a few capabilities of these sensing and control systems are used. This book addresses the need to educate agriculturists on the full usage scale of these arable and livestock systems. Features how-to guides on extracting and analyzing data from digital systems Describes quality standards for data security and transmission Focuses on state-of-the-art systems in livestock production, along with arable and indoor agriculture

In the age of global climate change, society will require cities that are environmentally self-sufficient, able to withstand various environmental problems and recover quickly. It is interesting to note that many "smart" solutions for cities are leading to an unsustainable future, including further electrification, an increased dependence on the Internet, Internet of Things, Big Data, and Artificial Intelligence, and basically any technology that leads us to consume more electricity. This book examines critical topics in Smart Cities such as true sustainability and the resilience required for all cities. It explores sustainability issues in agriculture and the role of agri-technology for a sustainable future, including a city’s ability to locally produce food for its residents. Features: Discusses safety, security, data management, and privacy issues in Smart Cities Examines the various emerging forms of transportation infrastructure and new vehicle technology Considers how energy efficiency can be achieved through behavioral change through specific building operations Smart Cities: Critical Debates on Big Data, Urban Development and Social Environmental Sustainability brings awareness to professionals working in the fields of environmental, civil, and transportation engineering, urban planners, and political leaders about different environmental aspects of Smart Cities and refocuses attention on critical urban infrastructure that will be necessary to respond to future challenges including climate change, food insecurity, natural hazards, energy production, and resilience.

The main goal of Smart Agritech: Robotics, AI, and Internet of Things (IoT) in Agriculture is to explore how emerging technologies such as robotics, artificial intelligence (AI), and IoT can be leveraged to improve efficiency, sustainability, and productivity in agriculture. Agriculture has always been a vital sector of the global economy, providing food and raw materials for industries and households. However, with the growing population, changing climate conditions, and limited resources, the agriculture sector faces numerous challenges. To address these challenges, farmers and agricultural companies are turning to advanced technologies such as Robotics, Artificial Intelligence (AI), and the Internet of Things (IoT). This exciting new volume provides a comprehensive overview of the latest technological advances in agriculture, focusing on these three cutting-edge technologies. The book will explore the potential benefits of these technologies in improving agricultural efficiency, productivity, and sustainability. Whether for the veteran engineer, scientist in the lab, student, or faculty, this groundbreaking new volume is a valuable resource for researchers and other industry professionals interested in the intersection of technology and agriculture.

Digital Agricultural Ecosystem The book comprehensively explores the dynamic synergy between modern technology and agriculture, showcasing how advancements such as artificial intelligence, data analytics, and smart farming practices are reshaping the landscape to ensure food security in the era of climate change, as well as bridging the gap between cutting-edge research and practical implementation. Agriculture has historically been the foundation of human civilization and benefits communities all around the world. Agriculture has a creative, adaptable, and innovative history, and as the digital age draws closer, agriculture is once again poised for change. Each of the 20 chapters explores the connection between agricultural and technological advancements, and are divided into four key areas. Part 1 covers knowledge sharing in the digital agricultural ecosystem. In the context of modern agriculture, the chapters underscore the importance of information flow. Through comprehensive reviews of literature and assessments of farmer participation on social media platforms, these chapters illustrate the value of information sharing for sustainable agriculture. Part 2 explores the adoption and impact of digital technologies in agriculture. The use of cutting-edge digital technologies in agriculture is examined thoroughly in this section. The chapters included here outline how precision, artificial intelligence, and blockchain technology have the potential to transform methods of agriculture and improve food systems. Part 3 addresses smart farming and sustainable agriculture. This section focuses on sustainability and offers details on eco-friendly production methods, the significance of smart farming in many nations, including India and the UK, and cost-effective fertilizer sprayer technologies. Part 4 examines the modeling and analysis of agricultural systems. This last section explores how mathematical modeling and data analytics are used in agricultural systems, with insights on everything from the study of credit access constraints in rural regions to water resource management in irrigation systems. Audience The diverse readership includes farmers, agronomists, agricultural researchers, policymakers, environmentalists, information technologists, and students from academic and professional fields who are eager to learn more about how digital innovation and sustainable agriculture can be used to address global issues such as climate change, food security, and smart farming.

Globalization has transformed agri-food markets, creating a single global market with reduced trade barriers. In theory, this should bring increased food security, yet challenges persist. Small farmers often need help integrating into global sourcing networks and meeting stringent food safety regulations. Additionally, there is increasing pressure on businesses and governments to address the environmental and resource consequences of agri-food production. Advanced Computational Methods for Agri-Business Sustainability offers a comprehensive analysis of agricultural sector challenges and provides practical solutions. It identifies potential issues in agri-food management and supply chains, offers mitigation strategies, and highlights opportunities for sustainable development. The book aims to bridge the gap between theory and practice, providing insights for academics, policymakers, and industry professionals.

This book in its eighteen chapters provides sustainable and smart technology-based solutions to developing nations. Smart farming is growing in importance due to the increasing demand for higher crop yield, the need for using natural resources efficiently, the rising use and sophistication of information and communication technology and the increasing need for climate-smart agriculture. Some of these chapters deal with the applications of smart agriculture to address the special challenges of the Small Island Developing States for sustainable agriculture. The book brings together scientific communities from India, Indonesia, Iraq, Malaysia, Mauritius, Myanmar, Palestine, Sri Lanka and South Africa to share their expertise to make the farming system more connected and intelligent. The smart farming techniques shared in different chapters not only help to reduce the overall cost and improve the quality and quantity of products but altogether help improve the sustainability of agriculture in the developing world. ‘Smart Farming’ is a management concept focused on providing the agricultural industry with the infrastructure to leverage advanced technologies—including artificial intelligence (AI), big data, robotics, drones and Internet of Things (IoT)—for tracking, monitoring, automating and analyzing operations. Sometimes known as precision agriculture, smart farming is software managed and sensor monitored.

This study—which includes a pilot intervention in Kenya—aims to further the state of knowledge about the emerging trend of disruptive agricultural technologies (DATs) in Africa, with a focus on supply-side dynamics. The first part of the study is a stocktaking analysis to assess the number, scope, trend, and characteristics of scalable disruptive technology innovators in agriculture in Africa. From a database of 434 existing DAT operations, the analysis identified 194 as scalable. The second part of the study is a comparative case study of Africa’s two most successful DAT ecosystems in Kenya and Nigeria, which together account for half of Sub-Saharan Africa’s active DATs. The objective of these two case studies is to understand the successes, challenges, and opportunities faced by each country in fostering a conducive innovation ecosystem for scaling up DATs. The case study analysis focuses on six dimensions of the innovation ecosystem in Kenya and Nigeria: finance, regulatory environment, culture, density, human capital, and infrastructure. The third part of the study is based on the interactions and learnings from a pilot event to boost the innovation ecosystem in Kenya. The Disruptive Agricultural Technology Innovation Knowledge and Challenge Conference in Nairobi, Kenya, brought together more than 300 key stakeholders from large technology companies, agribusiness companies, and public agencies; government representatives and experts from research and academic institutions; and representatives from financial institutions, foundations, donors, and venture capitalists. Scaling Up Disruptive Agricultural Technologies in Africa concludes by establishing that DATs are demonstrating early indications of a positive impact in addressing food system constraints. It offers potential entry points and policy recommendations to facilitate the broader adoption of DATs and improve the overall food system.

This publication, produced by FAO and Zhejiang University, examines how rural e-commerce could advance the digital transformation of agri-food systems, including increasing production efficiency, expanding farmers’ market access, improving poverty alleviation, fostering agricultural entrepreneurship, and attracting young generations back to their villages for economic revival and rural revitalization. It is highlighted that an enabling ecosystem with favourable government policies and strategies, public-private partnerships and innovative business models is of great importance to accelerate the development of rural areas in China, and generate larger economic, social and environmental impacts. As the largest developing country in the world, the experience of digital agriculture transformation in China could be shared with other developing countries. The report also discusses some of the challenges encountered and lessons learned during the development of rural e-commerce, as well as the proposals for the way forward.

This book is a collection of best-selected research papers presented at the Second World Conference on Internet of Things: Applications & Future (ITAF 2020) organized by Global Knowledge Research Foundation during 16 – 17 December 2020. It includes innovative works from researchers, leading innovators, business executives and industry professionals to examine the latest advances and applications for commercial and industrial end users across sectors within the emerging Internet of things ecosphere. It shares state-of-the-art as well as emerging topics related to Internet of things such as big data research, emerging services and analytics, Internet of things (IoT) fundamentals, electronic computation and analysis, big data for multi-discipline services, security, privacy and trust, IoT technologies and open and cloud technologies.