Generating Process-based Mobile Applications for the Internet of Things using Automated Planning
Name
Kelian Kaio
Abstract
Smartphone devices are being used by more than half of the world population, and this means more opportunities to create mobile applications that help people with their daily lives. This thesis is looking into mobile apps for the Internet of Things, which are used in areas like smart homes, transportation, and healthcare. However, because of the massive scale of smart devices, supporting all of them is not feasible. Automated planning can help the application adapt to user's and device's context and support only those IoT devices which are needed by creating user-specific plans. These plans can be mapped into a business process model so the mobile application could execute them by using a business process engine. The goal of this thesis is to investigate and develop a framework that enables creating dynamic IoT mobile applications, using automated planning and business software management while taking into account user's preferences and mobile device capabilities. Furthermore, it is analyzed which type of planning algorithm fits best for the motivating scenario. A framework prototype consisting of mobile application and backend is created for the motivating scenario is created as a proof of concept. The performance and scalability of the chosen planning algorithm and the developed prototype are evaluated.
Graduation Thesis language
English
Graduation Thesis type
Master - Software Engineering
Supervisor(s)
Jakob Mass
Defence year
2020