This version is not peer-reviewed
Mobile Data Science and Intelligent Apps: Concepts, AI-Based Modeling and Research Directions
: Received: 12 September 2020 / Approved: 14 September 2020 / Online: 14 September 2020 (00:01:39 CEST)
A peer-reviewed article of this Preprint also exists.
Journal reference: Mobile Networks and Applications 2020
Artificial intelligence (AI) techniques have grown rapidly in recent years in the context of computing with smart mobile phones that typically allows the devices to function in an intelligent manner. Popular AI techniques include machine learning and deep learning methods, natural language processing, as well as knowledge representation and expert systems, can be used to make the target mobile applications intelligent and more effective. In this paper, we present a comprehensive view on mobile data science and intelligent apps in terms of concepts and AI-based modeling that can be used to design and develop intelligent mobile applications for the betterment of human life in their diverse day-to-day situation. This study also includes the concepts and insights of various AI-powered intelligent apps in several application domains, ranging from personalized recommendation to healthcare services, including COVID-19 pandemic management in recent days. Finally, we highlight several research issues and future directions relevant to our analysis in the area of mobile data science and intelligent apps. Overall, this paper aims to serve as a reference point and guidelines for the mobile application developers as well as the researchers in this domain, particularly from the technical point of view.
Mobile data science; artificial intelligence; machine learning; natural language processing; expert system; data-driven decision making; context-awareness; intelligent mobile apps
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
We encourage comments and feedback from a broad range of readers. See criteria for comments and our diversity statement.