Mobile Data Science and Intelligent Apps: Concepts, AI-Based Modeling and Research Directions
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Mobile Data Science and Intelligent Apps: Concepts, AI-Based Modeling and Research Directions Iqbal H. Sarker 1,2
&
Mohammed Moshiul Hoque 2 & Md. Kafil Uddin 1 & Tawfeeq Alsanoosy 3
# Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract 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. Keywords Mobile data science . Artificial intelligence . Machine learning . Natural language processing . Expert system . Data-driven decision making . Context-awareness . Intelligent mobile apps
1 Introduction Due to the recent development of science and technology in the world, the smartphone industry has made exponential growth in the mobile phone application market [1]. These devices are well known as one of the most important Internet-of-Things (IoT) devices as well, according to their diverse capabilities including data storage and processing [2]. Today’s smartphone is also considered as “a next-generation, multi-functional cell phone that facilitates data processing as well as enhanced wireless connectivity”, i.e., a combination of “a powerful cell phone” and a “wireless-enabled PDA” [3]. In our earlier paper [4], we have shown that users’
* Iqbal H. Sarker [email protected] 1
Swinburne University of Technology, Melbourne, VIC 3122, Australia
2
Chittagong University of Engineering and Technology, Chittagong 4349, Bangladesh
3
RMIT University, Melbourne, VIC 3000, Australia
interest on “Mobile Phones” is more and more than other platforms like “Desktop Computer”, “Laptop Computer” or “Tablet Computer” for the last five years from 2014 to 2019 according to Google Trends data [5], shown in Fig. 1 . In the real world, people use smartphones not only for voice communication between individuals but also for various activities with different mobile apps like e
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