Futuristic Information and Communication: A Multimodal Multidisciplinary Signal Analysis

The development of novel techniques that can easily extract information from the joint observations of measurements coming from many modalities is necessary to realise the full potential of futuristic information processing applications in communication industries. Communication is an essential process in the design, development, and operation of systems and is expanded upon by exploring the essential information available at every stage of the system lifetime, including identifying the needs and constraints, conveying that knowledge, and confirming and validating that the right actions have been taken.  Multimodal communication describes the integration of multiple communication technologies in a single interoperation system. Multimodal and cross modal applications differ from traditional interaction methods in several ways. They can use any combination of input and output modalities, including but not limited to: video, audio, radio, fax, telephone, electronic, mechanical creating a more holistic user experience. Artificial intelligence systems, like Chabot’s and virtual assistants, may comprehend and react to users more instinctively and organically when they use multimodal artificial intelligence. It contributes to improving user experience as well as the efficacy and efficiency of interactions across a range of industries. Nevertheless, in recent times, deep learning and machine learning techniques are playing a pivotal role in multimodal signal processing for biomedical, fraud prevention, autonomous vehicles, Facial recognition, Hiring, Gaming, Social media, Travel and so on. But this domain suffers in exploiting its full potent due to absence of frameworks and tools for creating cross-modal and multimodal applications, as well as the lack of a common data structure that supports several modalities. This provides a common platform to a diverse and distinguished group of domain experts worldwide, all sharing a common passion for the ever-evolving information in the form of big data and forging new frontiers and building bridges to a brighter and sustainable future in the domain of communication.

Mihir Narayan Mohanty

is presently working as a Professor in the Department of Electronics and Communication Engineering, Institute of Technical Education and Research, Siksha ‘O’ Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India. He is the senior member of IEEE, Fellow of IET and IE(I). He has published more than 400 research papers in various high index International Journals (>120) Book Chapters (>100), Conferences Proceedings (>200) over the 25 years of teaching and research experience. He has also co-edited four books of Springer in the area of Advances in Artificial Intelligence. His area of research interests includes Applied Signal and Image Processing, Biomedical Signal Processing, Microwave Communication Engineering and Speech Processing. He is having total 2394 Google scholar citation with h-index 23, and i-10 index 60. He has successfully guided six Ph.D. scholars and currently seven scholars are working under him. He has delivered number of talks and guest lecturers in various countries including China, Singapore, Malasiya, UAE, Thailand. He has organized various international conferences and faculty development programs.

Bibhuprasad Mohanty

is presently working as a Professor and Head in the Department of Electronics and Communication Engineering, Institute of Technical Education and Research, Siksha ‘O’ Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India. He is the member of IEEE, IET and IE(I). He has published more than 85 research papers in various high index International Journals with over the 25 years of teaching and research experience. He has also co-edited four books of Springer in the area of Advances in Artificial Intelligence. His area of research interests includes Applied Signal and Image Processing, Biomedical Signal Processing, Communication Engineering and Speech Processing.

Kandarpa Kumar Sarma

currently Professor and Head, Department of Electronics and Communication Engineering, GUIST, Gauhati University, India specializes in mobile communication, artificial intelligence, human-computer interaction, cognitive and software-defined radio, speech processing and antenna design. He completed MTech in Signal Processing in 2005 from IIT Guwahati, India. He also completed PhD from IIT Guwahati in the area of mobile communication in 2012. He is a Senior Member of IEEE (USA) and a fellow of the Institution of Electronics and Telecommunication Engineers (IETE) (India).

Dmitrii Kaplan

Associate Professor (2015), Lead Researcher (2020) at Saint Petersburg Electrotechnical University “LETI” (Saint Petersburg, Russia), Full Professor (2023) at China University of Mining and Technology. The current research and academic work are related with digital signal and image processing, embedded and reconfigurable systems, computer vision and machine learning. The most substantial results are in the fields of digital signal and image processing, embedded systems and machine learning. Author of more than 100 papers in journals, including leading journals, and conference proceedings. He is an Associate/Guest Editor/Editorial Board Member such journals as Frontiers in Neuroinformatics, Industrial Artificial Intelligence, Scientific Reports.