Location-Based Services
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Course informations
| Study program level |
Undergraduate |
| Study program |
Electrical Engineering |
| Study program direction |
Telecommunications and informatics |
| Course year |
3. |
| Course semester |
VI |
| Course status |
Elective |
| ECTS |
6 |
| Lectures (h) |
30 |
| Excercises (h) |
30 |
| Seminars (h) |
- |
Course objectives
The main objective of the course is to acquire theoretical knowledge in the field of telecommunication services based on location, procedures and systems for determining the position of mobile users, geospatial data, and public mobile networks. The course also aims to enable the acquisition of knowledge and skills required for the development, implementation and maintenance of location-based services.
Course outcomes
- Describe and understand the concept of location-based services and the network architecture that supports them.
- Explain telecommunication network elements that support location-based services and understand its use.
- Explain and apply network protocols that support location-based services.
- Distinguish the procedures for determining the position of mobile users.
- Describe and understand the structure and ways of using geospatial data.
- Describe and understand the process of managing the location data in public mobile networks.
- Describe the business environment for the establishment of location-based services and apply acquired knowledge in practical projects.
Course content
Introduction to location intelligence (Introduction and motivation, basic concepts, location and place, location landscape, location intelligence, location based services, location based information model), geospatial Data (geospatial data, reference coordinate system, descriptions and formats of geospatial data processing, geospatial data Processing, geostatistics), location and location information sources (public mobile networks, network positioning procedures, satellite navigation, satellite positioning procedures, error and satellite positioning limitations, fusion information and sensor readings, location data acquisition, localization, spatial data alignment, projection and contextual mapping), process location information and location information (location intelligence, statistical and machine learning, descriptive statistics, categorization info location analysis, correlation chart, hypothesis setup and testing, observational model development, tree model, random forest model, linear and superimposed linear regression model, neural and deep neural network, advanced concepts in computer science, validation of models) and examples of application on massive data sets from public mobile networks. Problem-oriented practical work which takes place in program environment R.
