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Engineering and Science of Biomass Feedstock Production and Provision
The biomass based energy sector, especially the one based on lignocellulosic sources such as switchgrass Miscanthus, forest residues and short rotation coppice, will play an important role in our drive towards renewable energy. The biomass feedstock production (BFP) subsystem provides the necessary material inputs to the conversion processes for energy production. This subsystem includes the agronomic production of energy crops and the physical handling and delivery of biomass, as well as other enabling logistics. Achieving a sustainable BFP system is therefore paramount for the success of the emerging bioenergy sector. However, low bulk and energy densities, seasonal and weather sensitive a...
IoT and AI in Agriculture
This book covers smart agricultural space and its further development with an emphasis on ultra-saving labor shortages using AI-based technologies. A transboundary approach, as well as artificial intelligence (AI) and big data for bioinformatics, are required to increase timeliness and supplement the labor shortages, ensure the safety of intangible labor migration system to achieve one of the sustainable development goals (SDG) to secure food security (Society 5.0, SDG 1 and 2). With this in mind, the book focuses on the solution through smart Internet of Things (IoT) and AI-based agriculture, such as automation navigation, insect infestation, and decreasing agricultural inputs such as water...
Computer Vision in Smart Agriculture and Crop Management
This book is essential for anyone interested in understanding how smart agriculture, utilizing information and technology such as computer vision and deep learning, can revolutionize agriculture productivity, resolve ongoing concerns, and enhance economic and general effectiveness in farming. The need for a reliable food supply has driven the development of smart agriculture, which leverages technology to assist farmers, especially in remote areas. A key component is computer vision (CV) technology, which, combined with deep learning, can manage agricultural productivity and enhance automation systems for improved efficiency and cost-effectiveness. Automation in agriculture ensures benefits like reduced costs, high performance, and accuracy. Aerial imaging and high-throughput research enable effective crop monitoring and management. Computer vision and AI models aid in detecting plant health, impurities, and pests, supporting sustainable farming. This book explores using CV and AI to develop smart agriculture through deep learning, data mining, and intelligent applications.
Microalgae for Environmental Biotechnology
This is the first book to present the idea of using Industry 4.0 and smart manufacturing in the microalgae industry for environmental biotechnology. It provides the latest developments on microalgae for use in environmental biotechnology, explains process analysis from an engineering point of view, and discusses the transition to smart manufacturing and how state of the art technologies can be incorporated. It covers applications, technologies, challenges, and future perspectives. • Showcases how Industry 4.0 can be applied in algae industry • Covers new ideas generated from Industry 4.0 for Industrial Internet of Things (IIoT) • Demonstrates new technologies invented to cater to Industry 4.0 in microalgae • Features worked examples related to biological systems Aimed at chemical engineers, bioengineers, and environmental engineers, this is an essential resource for researchers, academics, and industry professionals in the microalgae biotechnology field.
Recent Advances in Big Data, Machine, and Deep Learning for Precision Agriculture
Precision agriculture can be defined as applying real-time, reliable information to optimize the use of resources and the management of farming practices, minimizing environmental impacts. With the evolution of remote sensing technologies, big data that must be converted to information is being generated in the agricultural sector. When analysed with machine and deep learning approaches applied to remote sensing products, this data has been used successfully. The computational power using cloud-based systems and recent advances in farm machinery equipment providing data collection, processing, and analysis opens several opportunities to develop and adopt new technologies. Large-scale farm pr...
Cutting-edge innovations for eradicating world hunger
Overall, the book offers a detailed analysis of the current and future challenges facing global agriculture and shows practical solutions for how these can be overcome through technological and political innovations. The topicality of the book is highly rated, as it deals with central and pressing global problems that are highly topical and will continue to be of enormous importance in the coming decades.
Two Decades from the Indian Ocean Tsunami
This book presents the advancements in the disaster risk reduction and resilience building in the countries affected by the Indian Ocean Tsunami countries. The book includes a few cross-cutting issues related to governance, technology, and communities, with two major parts: (1) cross-cutting issues and (2) regional and country level experiences. At the threshold of twenty years from Indian Ocean Tsunami, the concept of disaster risk reduction field has evolved significantly in the affected countries as well as around the world. Globally, several mega disasters happened in the last 20 years, and risk landscape has become more complex. In addition, technology, governance, and people’s resilience have gained positive momentum. We had two world conferences on disaster risk reduction, resulting in two global disaster risk reduction frameworks, which aligned with development frameworks as well as climate change agreements. COVID-19 and post COVID risk landscape has brought the new dimension of compound and complex disasters and need for all hazards’ approach.
IoT and AI in Agriculture
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 ...
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