Название: Multimodal Intelligent Sensing in Modern ApplicationsАвтор: Masood Ur Rehman, Ahmed Zoha, Muhammad Ali Jamshed, Naeem Ramzan
Издательство: Wiley-IEEE Press
Год: 2025
Страниц: 307
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB
Discover the design, implementation, and analytical techniques for multi-modal intelligent sensing in this cutting-edge text.
The Internet of Things (IoT) is becoming ever more comprehensively integrated into everyday life. The intelligent systems that power smart technologies rely on increasingly sophisticated sensors in order to monitor inputs and respond dynamically. Multi-modal sensing offers enormous benefits for these technologies, but also comes with greater challenges; it has never been more essential to offer energy-efficient, reliable, interference-free sensing systems for use with the modern Internet of Things.
Multimodal Intelligent Sensing in Modern Applications provides an introduction to systems which incorporate multiple sensors to produce situational awareness and process inputs. It is divided into three parts—physical design aspects, data acquisition and analysis techniques, and security and energy challenges—which together cover all the major topics in multi-modal sensing. The result is an indispensable volume for engineers and other professionals looking to design the smart devices of the future.
Key topics discussed include sensor design, deployment efficiency, energy management, data fusion, and information extraction through Machine Learning, Deep Learning, and Federated Learning to showcase the latest developments in this dynamic field. By considering challenges and future prospects, the book caters to a diverse readership within the scientific community.
Multimodal Intelligent Sensing in Modern Applications readers will also find:
A field of multidisciplinary contributors in fields like wireless communications, signal processing, and sensor design
Coverage of both software and hardware solutions to sensing challenges
Detailed treatment of advanced topics like efficient deployment, data fusion, Machine Learning, and more
Chapter 1 delves into the realm of multimodal intelligent sensing, uncovering the various sensor types and the integration of multiple sensors for enhanced capabilities. The chapter also explores the applications of multimodal sensing in different sectors and the challenges and opportunities that come with this dynamic field.
Chapter 2 focuses on antennas for wireless sensors, emphasizing their crucial role as the sensory gateway for wireless networks. Readers will gain insights into fundamental antenna parameters, fabrication methods, and the different types of antennas utilized in sensing networks.
Chapter 3 discusses the sensor design for environmental monitoring, shedding light on combating deforestation through wireless sensor networks and the design considerations involved in creating effective systems for environmental conservation.
Chapter 4 explores the applicability of wireless sensors for multimodal health monitoring, detailing the use of wearable and implantable sensors, multimodal healthcare sensing devices, and the use of AI methods in healthcare systems for enhanced monitoring and diagnosis.
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Lastly, Chapter 12 paves the way for the future of multimodal intelligent sensing in the deep learning era, outlining the challenges, perspectives, and ethical considerations that will shape the evolution of sensor technology in the years to come.
Multimodal Intelligent Sensing in Modern Applications is ideal for experienced engineers and designers who need to apply their skills to Internet of Things and 5G/6G networks. It can also act an introductory text for graduate researchers into understanding the background, design, and implementation of various sensor types and data analytics tools.
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