Artificial Intelligence, Internet of Thing & Big Data: Recent Trends, Challenges & Future Applications

Internet of Things, Artificial Intelligence systems, Deep Learning, and Big Data, are becoming more and more attractive both for the academic and industrial world, since such technological ecosystem enables the development of smart environments and novel services with limited costs (Gochhayat et al. 2019). The number of applications of IoT, Big Data, and AI technologies is booming and will continue to grow exponentially in the coming years and decades. IoT is an interdisciplinary field that intersects with device, sensor network, stream analytics, and machine learning. AI for IoT focuses on technologies to enable machine learning algorithms to run on resource constrained, secure, and connected devices. The new technologies find their way into every aspect of our lives, and appear in a multitude of forms and applications.

The enormous emerging progresses and applications of IoT & AI have been witnessed in a broad range of interdisciplinary and multidisciplinary fields that has high impact on applied and theoretical research areas like sensor networks, equipment infrastructure, machine learning, big data analytics, image processing, pattern recognition, search engines, medical informatics, digital economy, robotics, finance, digital humanities, social sciences, text mining, security, smart education environment, crowd management, forensic, speech recognition, business intelligence and health care.

This special issue aims to bring together the researchers to highlight the significant scientific impact of current technologies, and major applications related to AI, IoT, Data Science, & Big Data, particularly, to address the above-mentioned domains and their recent trends, advances and possible challenges.

Topics of interest include, but are not limited to:

•   Real-time computer vision and speech processing
•   Learning-enabled IoT applications
•   AI for IoT security and privacy
•   IoT technologies in Transportation and Low Carbon Products
•   IoT technologies in Sustainable Energy and Environment
•   e-health
•   Big Data, cloud computing and data-intensive systems
•   Multimodal emotion recognition and sentiment analysis
•   Affective human-agent, -computer, and-robot interaction
•   Architectures of IoT systems
•   Machine-to-Machine Communication and IoT
•   Modeling of IoT applications
•   AI & IoT in sustainable Growth
•   AI, IoT & & Big Data Trends & Challenges
•   Machine Learning for Intelligent Systems
•   Optimized Blockchain for IoT
•   Collaborating IoT, digital transformation & enterprise security
•   Data Visualization
•   Image Informatics
•   Personalized Medicine
•   Information Security
•   Industry/Manufacturing 4.0
•   AI, Big Data ,Deep Learning & IoT Use Cases
•   Data-intensive applications in medicine, finance, transportation, education, legal, etc.