This new edition continues to focus on the nuts and bolts of wireless network access for devices on board vehicles. It has been updated to reflect on the most recent trends in the broad domain of Intelligent Transport Systems. It covers 802.11ac - a recent standard that is very useful in context where a large amount of information is to be sent in a limited time window. The new edition includes a thorough revision of the 'Vehicular Communication: Issues and Standards' chapter, with new citations and a new subsection on security. The new edition also cites numerous fresh research works to give readers an updated overview of the field. An update on the time delay incurred by applications that always run in the background (Skype, etc) is also covered. The 'Future Directions and Research Ideas' chapter is also largely re-written. An entirely new chapter on D2D communication keeping in view the vehicular context has been added in this edition. This volume will be a useful addition to the libraries for both the students of wireless communication and those studying applied probability.

"Intelligent Control" considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller.The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of the fuzzy controller is then described and finally an evolutionary algorithm is applied to the neurally-tuned-fuzzy controller in which the sigmoidal function shape of the neural network is determined.

The important issue of stability is addressed and the text demonstrates empirically that the developed controller was stable within the operating range. The text concludes with ideas for future research to show the reader the potential for further study in this area.

"Intelligent Control "will be of interest to researchers from engineering and computer science backgrounds working in the intelligent and adaptive control."

Focuses on several core aspects of Industry 4.0 on computer vision & imaging. Highlights several exciting techniques for disease prediction, NLP, image captioning, flood level assessment, crop classifications, and fabrication of smart wheelchairs. Covers several chapters on Natural Language Processing (NLP), focusing on Bangla language. Chapters presented in a step-by-step manner so that young minds can understand and implement easily.

Explores text mining and IoT applications for monitoring and controlling smart industrial systems Describes the key principles and techniques for Big-data analytics, security, and optimization for industrial applications. Provides context-aware insights, human-centric industry, smart computing for next-generation industry

Explores text mining and IoT applications for monitoring and controlling smart industrial systems Describes the key principles and techniques for Big-data analytics, security, and optimization for industrial applications. Provides context-aware insights, human-centric industry, smart computing for next-generation industry

Focusing on the nuts and bolts of wireless network access for computers on board vehicles, this volume shows how in-car computerization now does much more than merely act as a glorified map-reader. Wireless communication is transforming road travel in ways previously undreamt of, allowing vehicles to "talk" to a wider network and monitor road conditions, potential delays and traffic congestion, all automatically. Toll payments can be made without opening the driver's window on a cold day, while vehicles might themselves take active steps to avoid collisions.

It is the connection between on-board computers and wireless access points, ubiquitous in most cities now, that is a key area of research. Moving vehicles transfer their communications to new points as they progress, and this causes delays, known as "handover latency." In this book, new stochastic models are developed to map the disruption when connecting to 802.11 WLAN points. It details the application of stochastic tools to analyzing communication networks, as well as previous literature on handover latency and relevant mathematical modeling. Finally, it presents a scheme for monitoring traffic congestion using WLAN connectivity. This volume will be a useful addition to the libraries both of wireless communication students and those studying probability theory."

Opportunistic networking, by definition, allows devices to communicate whenever a window of opportunity is available. Many emerging technologies employ opportunistic exchanges of information. This book addresses this trend in communications engineering, taking into account three specific areas-vehicular, device-to-device (D2D), and cognitive radio-while describing the opportunistic communication methods of each. From smart homes to smart cities, smart agriculture to never-die-networks and beyond, the text explores the state of the art of opportunistic networking, providing the latest research, developments, and practices in one concise source.

Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller. The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of the fuzzy controller is then described and finally an evolutionary algorithm is applied to the neurally-tuned-fuzzy controller in which the sigmoidal function shape of the neural network is determined. The important issue of stability is addressed and the text demonstrates empirically that the developed controller was stable within the operating range. The text concludes with ideas for future research to show the reader the potential for further study in this area. Intelligent Control will be of interest to researchers from engineering and computer science backgrounds working in the intelligent and adaptive control.

Opportunistic networking, by definition, allows devices to communicate whenever a window of opportunity is available. Many emerging technologies employ opportunistic exchanges of information. This book addresses this trend in communications engineering, taking into account three specific areas vehicular, device-to-device (D2D), and cognitive radio while describing the opportunistic communication methods of each. From smart homes to smart cities, smart agriculture to never-die-networks and beyond, the text explores the state of the art of opportunistic networking, providing the latest research, developments, and practices in one concise source."