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Designing and Developing Innovative Mobile Applications

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  • Дата: 1-05-2023, 01:30
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Designing and Developing Innovative Mobile ApplicationsНазвание: Designing and Developing Innovative Mobile Applications
Автор: Debabrata Samanta
Издательство: IGI Global
Год: 2023
Страниц: 464
Язык: английский
Формат: epub (true)
Размер: 32.5 MB

Since mobile communication has become so ingrained in our daily lives, many people find it difficult to function without a cellphone. When the phone first came out, the only commonly used features were calling and sending text messages (texts). The intelligent mobile phone has proven to be a multipurpose tool that works best for communication and aids in learning, earning, and having fun. This in turn prompted several developers to consider creating mobile applications. Designing and Developing Innovative Mobile Applications focuses on the fundamentals of the Android OS and its device features, the deployment of any Android application, and the activities and intents of Android programming. Covering key topics such as mobile pages, software development, and communication, this premier reference source is ideal for computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

Chapter 1: Only with the aid of a sound architecture and the guiding principles that underpin it is it feasible to create effective software or mobile applications. Applications that adhere to architectural principles have been found to perform well in terms of scalability, maintainability, availability, interoperability, and other factors. The creation of mobile applications should be built on SOLID principles which leads to high-quality code without any additional work on the part of the developer.

Chapter 2: The suggested wellness mobile application employs numerous procedures, both automatic and manual, to continuously record different metrics. In order to encourage the user to change their lifestyle, the Wellness App also calculates and monitors the appropriate indicators for tracking nutrition, physical activity, and sleep quality. These indicators are analyzed by an inference reasoning module to determine the kinds of suggestions the subject will require to adopt the desired behaviors. These recommendations may include things like improving the activity schedule or adhering to the Mediterranean diet, which is known to be the best diet for reducing cardiovascular disease. Flutter, a wellness software for Android and iOS, takes care of guidance, exercise, sleep, and mindfulness, among other related issues.

Chapter 9: The reader is introduced to numerous unique and recent advancements in the field of Machine Learning in this chapter, which also provides a wide overview of Machine Learning and Artificial Intelligence. This compilation's first half offers a comprehensive overview of the traditional Machine Learning ideas, including ensemble learning, the idea of large data, how to handle Big Data, and predictive data analytics using Big Data. Computer vision (C.V.), the Swarm Algorithm, network science/graph theory and applications in Machine Learning, bioinformatics employing Machine Learning, and the Internet of Things are addressed as examples of Machine Learning (ML) frameworks (IoT). The second most popular language used globally for Machine Learning, R, is added as a side note, and this chapter focuses mostly on Python for ML. The next section elaborates on deep learning, machine learning ideas, models, types, and algorithms before giving a thorough introduction to neural networks, weight initialization, propagation, and the vanishing gradient problem.

This chapter provides a general overview of machine learning using the Scikit-learn module on Android mobile devices. The reader is introduced to the Python language in the first section. After that, a quick historical note on Python implementations on Android mobile phones is followed by an introduction to Python on Android. The following section introduces Pydroid3. Instructions for configuring an Android phone for machine learning are provided after this. os, pathlib, Pandas, NumPy, SciPy, Matplotlib, Seaborn, PySimpleGUI, NetworkX, Biopython, WordCloud, Kivy, and Jupyter Notebook are examples of supporting modules for machine learning that are available for Pydroid3.

Chapter 20: Reusable answers to typical design issues, design patterns offer a consistent user experience across many apps. With a focus on the user-centered approach to design, this article examines the best practices in mobile app design patterns and tools. Design tools including Sketch, Figma, Adobe XD, and InVision are explored along with design patterns like navigation bars, tab bars, list views, and card views.

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