CdSARTIFICIAL INTELLIGENCE AND DATA ENGINEERING
Codice885II
CFU6
PeriodoSecondo semestre
LinguaInglese
The course is aimed at providing students with an overview of issues, solutions, methods and technologies related to mobile, wearable and social sensing systems. Key principles and techniques are discussed covering the collection, filtering and analysis of information from both mobile and social platforms, with a specific focus on data from physical and human sensors.
During the oral exam the student must be able to demonstrate his/her knowledge of the course material and be able to discuss the reading matter thoughtfully and with propriety of expression. - The student must demonstrate the ability to put into practice and to execute, with critical awareness, the activities illustrated or carried out under the guidance of the teacher during the course.
Methods:
Final oral exam
- Project (1/2 people per project)
At the end of the course students are expected to:
- acquire hands-on experience with mobile computing, sensor-based systems and technologies, and social sensing applications
- develop the skills required to design and implement mobile and wireless sensing applications
The practical aspects concerning the design and implementation of pervasive applications will be assessed through a project.
The theoretical aspects underlying pervasive and mobile computing will be assessed through oral exam.
The student will be able to critically evaluate the most recent advancements in the area of pervasive and mobile computing.
Students will be required to read a research article concerning pervasive and mobile computing. The paper will be assigned by teachers during class hours and will be presented by students during class hours.
Fundamentals of distributed programming.
Delivery: face to face
Learning activities:
- attending lectures
- participation in seminar
- individual study
- group work
- laboratory work
Attendance: Advised
Teaching methods:
- lectures
- seminars
- laboratory
- project work
Design and development of smartphone applications (Android):
- Kotlin basics
- Android application model
- Android components
- graphical user interfaces
- using the sensors and the network
- the smartphone as a sensing platform
- context-aware computing
- location-based services
Principles and technologies in mobile/wearable computing:
- energy efficiency
- Bluetooth Low Energy
- non-GPS-based localization techniques
- human activity monitoring/recognition
- Publish/Subscribe, Distributed Hash Tables
Principles and technologies in social sensing:
- Social Media Sources and Networks
- Social Bot Detection
- Humans-as-sensors paradigm
Material and recommended reading indicated by the teacher.
Presentation of a research article (10 minutes).
Project presentation and discussion (20-30 minutes).
Oral exam (approximately 30 minutes).