As reported earlier WeAreDots Ltd. and EDI are working on project “iTrEMP: Intelligent transport and emergency management platform” ( Project).
The project objective is to develop an innovative platform for traffic data acquisition, distribution and management (Platform) which could serve as a basis for new products supporting greener and more efficient development and management of cities.
The 2nd period of the project has successfully completed. Four project activities are ongoing in parallel:
- Methods for more efficient and universal data aggregation from sensors:
- Subactivity 1.1 – Design of data model – completed;
- Subactivity 1.2 – Data acquisition methodology – completed;
- Subactivity 1.3 – Laboratory validation of a data synthesis method – ongoing.
- Machine learning for data analysis and decision making:
- Subactivity 2.1 – Analysis of applicable machine learning model – completed;
- Subactivity 2.2 – Development of selected machine learning models – ongoing;
- Subactivity 2.3 – Laboratory validation of machine learning models – ongoing.
- Methods for acquisition and analysis of bulk (video) data:
- Subactivity 3.1 – Analysis of applicable methods for local metadata extraction – completed;
- Subactivity 3.2 – Analysis of applicable distributed data processing methods – completed;
- Subactivity 3.3 – Development of selected bulk data acquisition and analysis methods – ongoing;
- Subactivity 3.4 – Laboratory validation of bulk data acquisition and analysis methods – ongoing.
- Development of platform prototype:
- Subactivity 4.1 – Central data storage and distribution platform prototype – ongoing;
- Subactivity 4.2 – Data acquisition, processing and analysis module prototypes – ongoing;
- Subactivity 4.3 – Platform prototype validation – ongoing.
The total costs of the project are planned 878 510,21 EUR, of which ERDF support is 599 316,15 EUR or 68,22%. Project has been started on April 1, 2019 and will continue for total of 18 months till end of September, 2020.
At this moment five deliverables have been successfully completed:
- D1: Data model design document
- D2: Report on local metadata acquisition methods
- D3: Report on applicable machine learning models
- D4: Report on distributed data processing methods
- D5: Report on data acquisition methodologies