Mobile App Development |

Mobile App Development, BSc (Spring 2026)

Fri, 30 Jan 2026 00:00:00 +0000

Description

Mobile app development has grown significantly recently, mainly due to the current computational power of modern tablets and mobile phones. The development of mobile applications brings different challenges to the developer, such as where the application will run (hardware specifications) and how the application performs when running (OS specifications). This course provides fundamental knowledge on how to develop Android applications using the native programming language Kotlin and introduces the following topics:

The Android application lifecycle;
The four types of Android app components, namely: (1) activities, (2) services, (3) broadcast receivers, and (4) content providers;
The design of user interfaces using imperative programming via Android Framework UI Toolkit;
The design of user interfaces using declarative programming via Jetpack Compose;
How to share data between Android components, how to persist data using files and databases, and how to manage the internal and external file storages;
The use of concurrency to improve speed and performance in Android applications;
The integration of Android apps with mobile backend services available on Google Firebase (i.e., app authentication, cloud-based database, and cloud-based storage);
The development of multimedia applications using the built-in camera and audio resources;
The use of geolocation information to develop location-aware Android applications;
The use of device sensors (motion, position, environment, and advanced sensors) to collect additional information for Android applications; and
The security aspects of Android deployment to make an Android application safer.

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Supporting Materials

Mobile App Development, BSc (Spring 2025)

Wed, 29 Jan 2025 00:00:00 +0000

Description

The Android application lifecycle;
The four types of Android app components, namely: (1) activities, (2) services, (3) broadcast receivers, and (4) content providers;
The design of user interfaces using imperative programming via Android Framework UI Toolkit;
The design of user interfaces using declarative programming via Jetpack Compose;
How to share data between Android components, how to persist data using files and databases, and how to manage the internal and external file storages;
The use of concurrency to improve speed and performance in Android applications;
The integration of Android apps with mobile backend services available on Google Firebase (i.e., app authentication, cloud-based database, and cloud-based storage);
The development of multimedia applications using the built-in camera and audio resources;
The use of geolocation information to develop location-aware Android applications;
The use of device sensors (motion, position, environment, and advanced sensors) to collect additional information for Android applications; and
The security aspects of Android deployment to make an Android application safer.

Staff

Course Manager and Teacher:
Teaching Assistant:
Teaching Assistant:

Supporting Materials

Mobile App Development, BSc (Spring 2024)

Tue, 30 Jan 2024 00:00:00 +0000

Description

The Android application lifecycle;
The four types of Android app components, namely: (1) activities, (2) services, (3) broadcast receivers, and (4) content providers;
The design of user interfaces using imperative programming via Android Framework UI Toolkit;
The design of user interfaces using declarative programming via Jetpack Compose;
How to share data between Android components, how to persist data using files and databases, and how to manage the internal and external file storages;
The use of concurrency to improve speed and performance in Android applications;
The integration of Android apps with mobile backend services available on Google Firebase (i.e., app authentication, cloud-based database, and cloud-based storage);
The development of multimedia applications using the built-in camera and audio resources;
The use of geolocation information to develop location-aware Android applications;
The use of device sensors (motion, position, environment, and advanced sensors) to collect additional information for Android applications; and
The security aspects of Android deployment to make an Android application safer.

Staff

Course Manager and Teacher:
Teaching Assistant:
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Supporting Materials

Programming Mobile Applications (Autumn 2023)

Wed, 30 Aug 2023 00:00:00 +0000

Description

This course is a hands-on introduction to programming of mobile applications. Building on basic JavaScript programming skills, React Native is introduced as the preferred framework for cross-platform mobile application development. The concept of Location-Based-Services is also introduced in combination with React Native and is explored hands-on, in combination with programming hardware components on the phone (e.g. camera component). Student work revolves around small weekly individual tasks and readings of React Native documentation (online resources and provided course material) and a group project (3-4 students) that will be carried out in the second half of the course.

The course has two main parts:

The first part of the course provides a hands-on introduction to basic concepts and tools in support of smartphone application programming. In this first part, students, building on prior JavaScript programming knowledge, will work with React Native as the framework for developing cross-platform smartphone applications. They will engage in a series of smaller assignments progressing towards increasingly more advanced parts of the React Native (RN) framework. In this part three individual assignments need to be completed.

The second part of the course is focused on gradually introducing Location-Based Services (LBS), Geolocation/Geofencing, and ways to program/control hardware components (e.g. GPS, camera, accelerometer), aiming to expand the possibilities of interacting with mobile devices. In this second half of the course a group project (3-4 students) will be conducted focused on programming and implementing a React Native application, through exploring and demonstrating knowledge on working with main RN components, navigation, LBS and programming of smartphone hardware components. In this latter part of the course, the gradual development of the group project will emphasise the construction of mobile app prototypes as vehicles for discussing the process of programming a mobile application with React Native as a tool, through components as building blocks and blackboxing processes.

Overall, students will train how to prototype with code and slowly develop their ability to analyse, discuss, and make appropriate design decisions when prototyping a mobile app, starting from code as a design material.

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Supporting Materials

Designing and Implementing Voyager - An Intelligent Travel Companion

Fri, 26 May 2023 00:00:00 +0000

Abstract

This paper explores the development of a user-friendly mobile application that combines travel planning and itinerary management. By comparing existing apps on the market and conducting user research, we identify user needs and ways to differentiate our app from competitors. Our app incorporates state-of-the-art AI technology to generate personalized itineraries for users visiting Copenhagen. We present the results of user involvement, including user interviews and usability tests, and analyze their feedback. In addition, we compare similar apps on the market and discuss design choices for our app’s user interface. We provide detailed information on the technical implementation of our app and explore future possibilities for development and integration with AI. Overall, this paper provides insights into the creation of a travel planning and itinerary management app that offers a unique and user-friendly experience for travelers. Our approach combines user research, innovative technology, and thoughtful design choices to create an app that stands out in a competitive market.

Mobile Games for the Visually Impaired

Fri, 26 May 2023 00:00:00 +0000

Abstract

Grand View Research predicts the gaming industry to grow at an annual rate of 12.9% from 2022 to 2030. However, not everyone can enjoy everything the gaming industry provides. People can have many impairments that prevent them from enjoying a video game. There are many possible guidelines for developers to follow to improve accessibility, but they lack a focus on activating other senses than sight. This project shows the development of an application that implements features that activate multiple senses. The application is then tested on 25 individuals across 5 groups. The data analysis presents partial results and tendencies because of a lacking data set. The goal is to collect a ten times larger data set and perform a Gaussian analysis before publishing the results of this project in a conference paper.

Mobile App Development, BSc (Spring 2023)

Tue, 31 Jan 2023 00:00:00 +0000

Description

The mobile app development has seen significant growth in the recent past, mainly due to the current computational power of modern tablets and mobile phones. The development of mobile applications brings a set of different challenges to the developer, such as where the application will run (hardware specifications) and how is the application performance when running (OS specifications). This course provides fundamental knowledge on how to develop Android applications using both Java and Kotlin programming languages and introduces the following topics:

The Android application lifecycle;
The four different types of Android components, namely: (1) activities, (2) services, (3) broadcast receivers, and (4) content providers;
The design of user interfaces (UI) using layouts, resources, and a set of Android UI controls (e.g., TextView, EditText, Button, Checkbox, Progressbar, among others);
How to share data between Android components, how to persist data using files and databases, and how to manage the internal and external file storages;
The use of concurrency to improve speed and performance in Android applications;
The development of multimedia applications using the built-in camera and audio resources;
The use of geolocation information to develop location-aware Android applications;
The use of device sensors (motion, position, environment, and advanced sensors) to collect additional information for Android applications; and
The security aspects of Android deployment to make an Android application safer.

Staff

Course Manager and Teacher:
Teaching Assistant:
Teaching Assistant:

Supporting Materials

Development of App to the Restaurant Business

Wed, 24 Aug 2022 00:00:00 +0000

Abstract

This project researches whether Machine Learning (ML) and Social Media can help improve the experience for a customer who dines at restaurants. Previous studies have shown that restaurants should make their reservation and payment systems digital and online to increase customer service. Our project focus on the User Experience of the restaurant experience. We found out that ML and Social Media can contribute positively to the experience by focusing on the user-to-restaurant interaction rather than the user-to-user interaction. The limited user-to-user elements should focus on restaurant reviews and planning events to which ML can contribute positively, by identifying food images and connecting them to menu items on a menu card. This project discusses various ML and Social Media elements and how to utilize them, relying on data collected through questionnaires and interviews. Though marketing for businesses is not within this project’s scope, the test group mentioned that they would rather receive offers and news from restaurants than reading user updates, which introduces an exciting angle to how restaurants could use the proposed system further. The business aspects still need research, exploring how restaurants can use the proposed system for marketing themselves and how beneficial ML would be for business owners.

Mobile App Development, BSc (Spring 2022)

Tue, 01 Feb 2022 00:00:00 +0000

Description

The Android application lifecycle;
The four different types of Android components, namely: (1) activities, (2) services, (3) broadcast - receivers, and (4) content providers;
The design of user interfaces (UI) using layouts, resources, and a set of Android UI controls (e.g., TextView, EditText, Button, Checkbox, Progressbar, among others);
How to share data between Android components, how to persist data using files and databases, and how to manage the internal and external file storages;
The use of concurrency to improve speed and performance in Android applications;
The development of multimedia applications using the built-in camera and audio resources;
The use of geolocation information to develop location-aware Android applications;
The use of device sensors (motion, position, environment, and advanced sensors) to collect additional information for Android applications; and
The security aspects of Android deployment to make an Android application safer.

Staff

Course Manager and Teacher:
Teaching Assistant:
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Supporting Materials

Opportunities with Hand Gesture Technology in Mobile Gaming

Mon, 23 Aug 2021 00:00:00 +0000

Abstract

During the past decade, there has been steady developments in the area of computer-vision based hand-gesture recognition (HGR) technologies, and expansion in the environments they are available for. Hand-gesture input, combined with head-mounted displays, has become the principal interaction method in virtual reality games. It also shows promise in other areas, such as sign-language recognition, interactive museum exhibitions, and interactive displays available in public spaces. This paper explores the possible introduction of HGR-based interaction in mobile games, based on the identification of key concepts in literature examining the aforementioned areas. The result is a proposition of four general heuristics guiding the design and development of mobile games based on HGR as the primary interaction method.

Object Tracking System (VidIT)

Fri, 04 Jun 2021 00:00:00 +0000

Abstract

This thesis investigates, if an IT product can increase learning in an online setting. Information is included in regards of learning and the development of VidIT, which is an automated tracking system powered by a smartphone and an Arduino. The system can track people with the help of a motorized pan tilt mount. The purpose of VidIT is to enhance learning during COVID-19, by enabling students and teachers to record themselves single-handily while moving around. A survey, a user test and a performance test was conducted to gather data on the current situation of teaching in an online setting, testing of the usability and performance of VidIT. Based on the tests, it was concluded that the resulting system worked as intended. However, some improvements are needed to effectively improve learning and teaching in an online setting. These improvements includes but are not limited to, streaming functionality, movement prediction and faster computation in relation to the objection detection algorithm.

Mobile App Development, BSc (Spring 2021)

Wed, 03 Feb 2021 00:00:00 +0000

Description

The Android application lifecycle;
The four different types of Android components, namely: (1) activities, (2) services, (3) broadcast receivers, and (4) content providers;
The design of user interfaces (UI) using layouts, resources, and a set of Android UI controls (e.g., TextView, EditText, Button, Checkbox, Progressbar, among others);
How to share data between Android components, how to persist data using files and databases, and how to manage the internal and external file storages;
The use of concurrency to improve speed and performance in Android applications;
The development of multimedia applications using the built-in camera and audio resources;
The use of geolocation information to develop location-aware Android applications;
The use of device sensors (motion, position, environment, and advanced sensors) to collect additional information for Android applications; and
The security aspects of Android deployment to make an Android application safer.

Staff

Course Manager and Teacher:
Teaching Assistant:
Teaching Assistant:

Supporting Materials

Building a Gamified Habit Application

Mon, 17 Aug 2020 00:00:00 +0000

Abstract

A large part of human behaviour is a function of habits, and thus habits have a notable influence on the well-being of the individual. Although many mobile applications claim to support habit formation, there is a lack of habit applications that are based on theory of habit formation. Gamification shows promise for supporting long term behaviour change such as habit formation but is not prevalent in habit applications. Gamification is a relatively new trend that focuses on applying game techniques to non-game contexts in order to provide motivational benefits. This paper intends to elicit the design of an application that aims to support the formation of habits. Two literature was therefore conducted on habit theory and gamification. Based on these results, an initial set of requirements and a prototype was created. This prototype was used to gather feedback from three potential users leading to nine final requirements grouped into four major categories concerning the daily tracking of habits, long term goals, implementation intentions and rewards. An MVP of the application was developed based on these requirements, the prototype and user feedback.

Machine Learning in Android Applications

Fri, 29 May 2020 00:00:00 +0000

Abstract

This project is motivated by the ever-increasing popularity of machine learning techniques for solving repetitive everyday tasks, as well as the availability and importance of smartphones in today’s society. The combination of the two creates an environment in which the use of machine learning for simplifying mundane tasks in mobile applications may be experimented with. This project is a study in the use of machine learning in the context of such a mobile application, and specifically uses the Firebase ML Kit mobile SDK in that pursuit. The project includes the development of an application that allows users to generate descriptions of electronic devices they wish to post for sale on online marketplaces. The application utilizes machine learning and natural language generation to present the user with a textual description of the image submitted to the application. This project gives an overview of central machine learning principles, and goes into detail about the concepts relevant to solving the problem in question, namely classification, and neural networks. It also describes the process of implementing the application and how Firebase ML Kit provides machine learning capabilities, as well as how SimpleNLG provides natural language generation functionality to the application. The project further reflects on the application created and the use of ML Kit therein.

Implementation of the Progressive Web App - Woodle

Thu, 28 May 2020 00:00:00 +0000

Abstract

This project aims to create a native-like application on the web to test the current capabilities of Progressive Web Apps. Woodle is a Progressive Web App, which is an application run on the web, but with enhancements to create a native-like application. Progressive Web Apps bring native-like capabilities, such as geolocation, push-notifications, offline use, and more to web-platforms. Therefore, in Woodle, users can register an account and track the activities through GPS location. After completing an activity, it’s saved so the user can keep track of activity stats and previous activities. Users can add friends and see their activity history as well.

Road Safety with Android Auto and Machine Learning

Tue, 26 May 2020 00:00:00 +0000

Abstract

This thesis aims to research the question of how to predict road safety and how a driver can safely receive relevant information on road safety during a drive. This has become a relevant field of research, with sophisticated computing hardware available as a feature in cars. Additionally, operation areas and computation capability of mobile devices are expanding. The results of the experiment in this thesis has been an Android application which implements Machine Learning Models and Statistical Models to predict accidents, based on the current situation of the user. The Machine Learning Models do not provide valid scientific evidence for the predictions to be correct, due to the supervised historical traffic data, used to train the Machine Learning models, having inconsistent patterns of how accidents happen. The Machine Learning models are activated by Statistical Models using historical traffic data. The models are only compatible to some extent. This is limited by a historical weather data set, which only enables the model to predict accidents within a range incorrect with a level of abstraction. Thus the Statistical Models and the Machine Learning Models are implemented in the application using the Android System compatible with the Android Auto subsystem. Android Auto enables a safe communication channel with the drive. The application is distributable to Android Users and compatible with 60.3% of all android devices. In the future the models predictions might be invalid, as the behaviour of a car might change. Although the experiment does not provide any sophisticated pipeline for extending the models with new data.

Mobile App Development, BSc (Spring 2020)

Wed, 29 Jan 2020 00:00:00 +0000

Description

The Android application lifecycle;
The four different types of Android components, namely: (1) activities, (2) services, (3) broadcast receivers, and (4) content providers;
The design of user interfaces (UI) using layouts, resources, and a set of Android UI controls (e.g., TextView, EditText, Button, Checkbox, Progressbar, among others);
How to share data between Android components, how to persist data using files and databases, and how to manage the internal and external file storages;
The use of concurrency to improve speed and performance in Android applications;
The development of multimedia applications using the built-in camera and audio resources;
The use of geolocation information to develop location-aware Android applications;
The use of device sensors (motion, position, environment, and advanced sensors) to collect additional information for Android applications; and
The security aspects of Android deployment to make an Android application safer.

Staff

Course Manager and Teacher:
Teaching Assistant:
Teaching Assistant:

Supporting Materials

Mobile App Development, BSc (Spring 2019)

Tue, 29 Jan 2019 00:00:00 +0000

Description

This course gives a fundamental introduction to Java development of apps for the Android platform.

The following topics will be introduced:

The four fundamental Android components (activities, services, content providers and broadcast receivers) and intents
Designing user interfaces using layouts and resources
Working with files and databases on a mobile device
The Android life cycles and thread model
Using built-in camera, sensors and libraries/tasks e.g. calendar and contacts
Mobile/server communication including RESTful APIs and JSON
Android libraries for creating location aware apps.

Furthermore, Androids threading model will be introduced and related to threading and concurrency in general.

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Teacher:
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Supporting Materials

Automated Lecturer-Tracking System

Mon, 10 Sep 2018 00:00:00 +0000

Abstract

Development of technology has brought some significant changes to the educational system, resulting in some new means of gathering the knowledge. In this project, we focus on the video lectures that provide significant benefits for all the students. We aim to enhance the way video lessons are recorded by introducing the system for automatic lecturer-tracking. This thesis introduces the new approach in implementing an automated lecturer-tracking system by using a smartphone as the replacement for a camera device and a processing unit. The proposed solution uses the YOLO real-time object detection system and tracking algorithms from iOS Vision framework to detect and track the lecturer. A motorized pan-tilt head rotates the smartphone based on the input the smartphone sends to it. Experimental results show that the system can perform the desired behavior of lecturer-tracking, eliminating the need for human help in the process of recording.