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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-today 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.

Traditional flood design methods are increasingly supplemented by risk‐oriented methods based on comprehensive risk analysis. This analysis requires: (1) the estimation of flood hazard that represents intensity of a flood, (2) estimation of vulnerability, e.g. percentage of damage to total property as a function of flood depth and duration, and (3) the consequences of flooding, e.g. loss of life and damage to property. In this study, flood hazard maps of the Balu‐Tongikhal River system within the eastern part of Dhaka City are prepared using geoprocessing tools and a hydrodynamic model. The raster‐based vulnerability maps and expected damage maps of several return period floods are then produced. In comparison with the classical inundation maps, these damage maps generate more information about the flooding events. Consequently, the produced maps are useful in evaluating policy alternatives and minimising property loss because of floods in the study area.

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