1. cHiPSet – CS8 Final Report
CS8 - Big Data Processing, Analytics and Applications in Mobile Cellular Networks Title
cHiPSet – CS8 Final Report
Sanja Brdar
Vilnius, March 28-29, 2019 1 1

2. Team members Team Profile Team members
Countries: Serbia, Greece, Romania, Ireland, Austria, Norway
Partners: 1 Research Institute, 5 Universities, 1 Company
Team members
Sanja Brdar
Olivera Novović
Nastasija Grujić
Apostolos Papadopoulos
Ciprian-Octavian Truică
Kenth Engø-Monsen
Horacio Gonzalez-Velez
Siegfried Benkner
Enes Bajrović

3. Workflow
Mobile Cellular Networks - From Location Data to Applications

4. Telcom data Call Detail Records Data from 3 cities:
Milan, Trentino (Italy), Telecom Italia
Novi Sad (Serbia), Telecom Serbia
Activity, Connectivity, Mobility…

5. Telcom data - Activity, Connectivity, Mobility

6. Timely dilevery of information
Big Data Processing
Timely dilevery of information
Real-time settings raise critical issues!
Challenges: Lack of research and benchmark studies that evaluate different computational architectures and big data frameworks
Only a few studies tackled issues of parallelization and distributed processing

7. Knowledge discovery and predictive models
Data Analytics
Knowledge discovery and predictive models
Graph analytics and machine learning - indispensable tools for telecom data analytics
Challenges: streaming nature of data demands for change detection and online adaption

8. Fusion with other sources
Understand
spatio-temporal
context better
Challenges: mismatch in the resolutions, multimodal and dynamic nature of data
External data sources are also advancing (new satellites launched, enhanced IoT ecosystems…)

9. Better decision making in the domains of application
Applications
Better decision making in the domains of application
Telecom data significantly enriched many different fields and external social good applications: transportation, urban and energy planning, public health, economy, tourism...

10. CS work - community detection
Apache Spark, Apache Hive and programming language Scala fully exploited in new pipeline
Results presented at the 20th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK, September 2018

11. CS work- detection of frequent patterns
Detection of frequent patterns in community structure for selected location
External sources: POI and land cover maps
FP-Growth algorithm
Scala implementation in Apache Spark’s Mllib

12. CS work- Visualisations
Automatization of visualisation pieline using Python QGIS API

13. CS work- Social pulse
City during large summer festival – Exit festival Novi Sad, Serbia

14. CS work- Social pulse
Mobilities trajectories, location entropy, agent based modelling

15. Future work
Negotiation for a new dataset from another telco provider in Serbia
Next dissemination of results: NetMob 2019, 8-10 July Mathematical Institute, Oxford University, Oxford
Project proposals to continue activities
Bilateral
H2020 – Marie Skłodowska-Curie Actions
(RISE, ITN), RIA, IA
Eureka