Course: Processing Sensor Data in IoT
Code: 3ФЕИТ07011А
ECTS points: 6 ECTS
Number of classes per week: 3+0+0+3
Lecturers: Asst. Dr. Hristijan Gjoreski
Course Goals (acquired competencies): Working with sensor data and purpose-built algorithms for data processing. Working with Python algorithms for automatic sensor data processing. Creating models.
Course Syllabus: Generating big data in real time from IoT devices. Storing data in Cloud systems and automatic processing of sensor data.Using RESTful API structure and data flow optimization. Defining different interfaces towards data storing in Cloud (Fog and Dew). Using Templates to learn patterns of devices and remote optimizing. Selective data storage in Cloud systems. Machine Learning methods to analyse the data. Implementing algorithms using Java or Python (Weka, sklearn, tflearn, numpy, matplotlib, pandas).
Literature:
| Required Literature | ||||
| No. | Author | Title | Publisher | Year |
| 1 | Robert Love
|
”Linux kernel development”, 3rd edition | Addison-Wesley | 2010 |
| 2 | William Stallings | “Operating Systems:Internals and Design”, Principles, 7 Ed | Prentice Hall | 2011 |
| 3 | A. S. Tanenbaum, A. S. Woodhull | ”Operating Systems Design and Implementation”, 3rd Edition | Prentice Hall | 2006 |
| Additional Literature | ||||
| No. | Author | Title | Publisher | Year |
| 1 | Silberschatz, Galvin, Gagne | “Operating Systems Concepts Essentials” | John Wiley & Sons | 2010 |
| 2 | A. S. Tanenbaum | ”Modern operating Systems”, 3rd Edition | GOAL Series,Prentice Hall | 2007 |
| 3 | J. Corbet, A. Rubini, G. Kroah-Hartman | “Linux device drivers”, 3rd edition | O’Reilly | 2005 |
