Smart Mobile Platforms and IoT Ecosystems

Dear Colleagues,

We take our smart mobile devices with us everywhere; they are true “extensions of the individual”. They accompany us and keep us company; they know where and with whom we are; they monitor, analyze, predict, suggest. Smart devices are an integral part of our reality, even filtering it and merging with it—which clearly creates challenges. It is, nevertheless, undeniable that smart devices have a unique ability to perceive the individual and their context; smart mobile platforms and IoT ecosystems can open doors to a world of opportunities.

Location, movement, activity, environment: these are all sensory data that make it possible to develop truly customized mobile applications and smart systems, tailored to the user's needs. Context awareness takes advantage of the fact that modern devices are packed with sensors and are increasingly aware of their environment, which provides developers with the opportunity to build personalized, contextualized experiences. Combining user state with the results from a dozen different sensors—providing contextual information ranging from “where” to “when”, “who” and “what”—is a challenging proposition, which allows smart mobile platforms and IoT ecosystems to interact with their users in an increasingly less artificial and more intelligent way.

Smart mobile platforms and IoT ecosystems are expected to continue playing a disruptive role in the future; artificial intelligence and machine learning (AI/ML) will remain a trending buzzwords—and for good reasons.

AI/ML provides developers with Cognitive Computing features that mimic human characteristics to help improve human decision-making. Cognitive Computing describes technologies and platforms that are based on AI/ML and signal processing, and examples of real-world use cases include computer vision, natural language processing, speech recognition, human–computer interaction, dialog and narrative generation, and sentiment analysis, among others. Cognitive computing systems make context computable by wading through massive collections of diverse information to find patterns and then applying those patterns to respond to the needs of the moment, acting virtually autonomously in many problem-solving situations.

We encourage submissions that describe innovative solutions and advances on the application of Artificial Intelligence and Machine Learning to Mobile Platforms and IoT Ecosystems, particularly on the following topics: Smart Mobile and Ubiquitous Systems; IoT Intelligent Systems; Digital Twins for Industry 4.0; Edge AI and Cloud Computing; Ambient Assisted Living; mHealth and eHealth; Cognitive Computing; Context Aware Systems; Applications of Computer Vision, Natural Language Processing, Dialog and Narrative Generation, Sentiment Analysis, or Emotion Recognition; among others.

Dr. José Carlos Bregieiro Ribeiro
Dr. Rolando Miragaia
Guest Editors

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• mHealth
• ambient-assisted living
• smart homes
• smart cities
• on-device machine learning
• edge AI
• digital twins
• Industry 4.0
• smart sensing
• wearable devices
• unmanned vehicles
• computer vision
• natural language processing
• conversational agents
• sentiment analysis and emotion recognition