Lecture: Mobile Crowd Sensing and Social Data Mining using Agents


Univ. Koblenz-Landau: VAK 04IN2111
Univ. of Bremen: VAK 08-29-4-FEM-1-e
Category: Course (Lecture+Laboritory), 2/4 SWS
Master Course
ECTS: 6, Winter Semester
University of Koblenz-Landau and University of Bremen
Lecturer: PD Dr. Stefan Bosse


The lecture follows the concept of research-based learning and provides a hands-on and experimental introduction to Crowd Sensing and Social Data Mining with Mobile Agents. In this lecture, students will learn the practical handling and implementation of distributed crowdsensing and social data mining applications using simple examples. As a distributed data processing and communication model mobile agents are used. The JavaScript-based execution platform JAM can be run on a variety of host platforms, including mobile devices (smartphones), desktop computers, servers, embedded computers and sensor networks, and on the Internet via a WEB browser. In the foreground is a heterogeneous distributed application with user interaction (HMI), the agent model is just a tool and serves as the "unit cell" of a self-organizing system. Therefore, only basic knowledge of agents and distributed systems is required, which will be summarized briefly in the event. It introduces the basics of mobile crowd sensing, the problems (how do I motivate users to participate, etc.), the security and privacy of personal data, and the aggregation of data.

Learning Outcomes

  1. Understanding the basics, problems, and criteria of mobile crowd sensing applications (and operative layers of a distributed sensory system)
  2. Ability to design and implement simple crowd sensing applications using WEB and smartphone interfaces with mobile agents
  3. Assess the risks and risks of crowd sensing
  4. Programming Crowd Sesning Applications at All Operational Layers (Sensing, Aggregation, Application)