Smart IoT multimodal emotion recognition system using deep learning networks.- Artificial Intelligence and IoT framework for the health monitoring system.- Big Data Classification: Application and Challenges.- A survey on recent deep learning architectures.- Research Progress of MapReduce Big Data Processing Platform and Algorithm.- A CNN Based Traffic Sign Recognition System.- Deep learning algorithm and its applications to IoT and Computer Vision.- Exploiting Internet of Things (IOT) Services to Autism Children Emotion Recognition System.
Dr. M. Kalaiselvi Geetha is Professor with 26 years of experience demonstrating consistent success as an educator at the undergraduate and postgraduate education in Computer Science and Engineering, Annamalai University. She has outstanding track record in assuring student success. She was committed to conceiving and building programs from the ground up through proven competencies in board of studies, grant writing, administration, program management, staff development and empowerment. She has strong attitude toward teaching and in motivating students to develop their expertise in major areas like AI, machine learning, computer vision, cloud computing and IoT. Her active participation is in continued learning through conferences and professional research. She believes in students’ abilities to learn and an inherent thirst for knowledge with the right environment. She actively works to connect students to their material to transform lives. She is associated with CSI and ISTE professional bodies.
Dr. J. Arun Nehru is currently working as Assistant Professor in SRM Institute of Science and Technology, with 4 years of professional teaching experience in the Department of Computer Science and Engineering, and committed to comprehensive problem-solving abilities, ability to cope and work with people in groups, leadership quality and analytical and interpersonal skills. He has strong attitude toward teaching and in motivating students to develop their expertise in major areas like deep learning, machine learning, AWS cloud computing and IoT. His active participation is in continuous learning through workshops, seminars, conferences and professional research and associated with ICTACT, IET, IAENG, IEDRC and ISTE professional bodies.
Dr. B. Sivaraman is Professor in the Department of Mechanical Engineering, Annamalai University with 33 years of teaching experience at both the undergraduate and postgraduate levels. He always strives hard to maintain outstanding track record in assuring student success and progression. He has commitment to conceive and build programs from the scratch. He contributed a lot in administration, program management, staff development and empowerment. He has got positive approach and attitude in teaching students to develop their knowledge in major areas like CFD, heat transfer, renewable energy and data analysis. He actively participates in continued learning through conferences and professional research. He believes in students’ abilities to learn and an inherent thirst for knowledge with the right environment. He actively works to connect students to their material to transform lives. He is associated with ISTE professional body.
This book projects a futuristic scenario that is more existent than they have been at any time earlier. To be conscious of the bursting prospective of IoT, it has to be amalgamated with AI technologies. Predictive and advanced analysis can be made based on the data collected, discovered and analyzed. To achieve all these compatibility, complexity, legal and ethical issues arise due to automation of connected components and gadgets of widespread companies across the globe. While these are a few examples of issues, the authors’ intention in editing this book is to offer concepts of integrating AI with IoT in a precise and clear manner to the research community. In editing this book, the authors’ attempt is to provide novel advances and applications to address the challenge of continually discovering patterns for IoT by covering various aspects of implementing AI techniques to make IoT solutions smarter. The only way to remain pace with this data generated by the IoT and acquire the concealed acquaintance it encloses is to employ AI as the eventual catalyst for IoT. IoT together with AI is more than an inclination or existence; it will develop into a paradigm. It helps those researchers who have an interest in this field to keep insight into different concepts and their importance for applications in real life. This has been done to make the edited book more flexible and to stimulate further interest in topics. All these motivated the authors toward integrating AI in achieving smarter IoT. The authors believe that their effort can make this collection interesting and highly attract the student pursuing pre-research, research and even master in multidisciplinary domain.