Open data - Download the Knowledge base
You are free to download the data of this Knowledge base.
To do this you must be an authenticated user: log in or sign in now.
All the data are licensed as Creative Common CC-BY 4.0.
Virtuose DE
A Cloud-based video platform to analyse traffic movements. The German part of the project by Fraunhofer HHS aims to develop low-complexity, real-time algorithms for analysis of large-scale visual data. In consideration of increasingly growing cities in European industrial countries it becomes more and more important that the traffic situation has to be optimised. The service tries to solve this issue by analysing data streams to discover free park spaces for
Type of content:
Assets
Type of asset:
Platform
Big data potential
Yes
Policy domains:
Urban Planning & Transport
Phase in the policy cycle:
Policy Design and Analysis
TRL
7
Implementation/customisation cost
Low
Open license availability
Yes
Ease of use
High
Tags:
Smart City
Smart Government
Process and resource optimisation
Real time information
Strategic planning
Serves:
Addresses:
| SWOT Analysis for Virtuose DE |
||
|---|---|---|
| Helpful | Harmful | |
Internal |
Strengths• Flexible usage of different computing platforms for robust and scalable video delivery and analysis. • Develop low-complexity, real-time algorithms for analysis of large-scale visual data. • Developing low-complexity algorithms that mainly operate on compressed video data to vastly reduce storage and processing requirements. • Investigation of Hierarchical approaches that combine deep learning-based computer vision techniques with compressed domain processing. • Crowd control • Project consortium consists of 19 partners from Germany, Finland, Spain, Turkey and Romania |
Weaknesses• Large-scale visual data • Plenty of different video services, will need to be started rapidly, scaled up or down, or moved to another computing platform • Poorly designed interface • Storage and processing requirements. • Data privacy • System prototype demonstration in operational environment |
External |
Opportunities• Develop low-complexity, real-time algorithms for analysis of large-scale visual data. • Parking lot management and surveillance as well as smart on-street parking in the frame of the emerging smart-City concept, and video-based security in public transportation. • Utilising the most recent advancements in cloud, virtualisation and video delivery techniques. • Analyse the business case for selected video services. • Investigation of Hierarchical approaches that combine deep learning-based computer vision techniques with compressed domain processing. |
Threats• Large-scale visual data • Plenty of different video services, will need to be started rapidly, scaled up or down, or moved to another computing platform • Poorly designed interface • Storage and processing requirements. • Data privacy • Actual system not proven in operational environment |
