Location
Demo Site Expected Impact
- Increased number of (tangible) city planning actions for positive clean energy districts using the (proto-)PED design, development and management digital twin tools (based on pre-market research learnings) using open-standards based components which can be reused elsewhere.
- Increased integration of existing smaller scale management systems (e.g. Building management systems) with open-standards based operational city platforms using sectorial data (e.g. building data, mobility, urban planning, etc.).
- Enhanced data gathering approaches with identification of relevant multidimensional data sets (e.g. meteorological, load profile, social, geo-spatial, etc.) high-resolution real-time data streams (e.g. renewable energy production, energy consumption), and relevant forecasting data, drawing also on the work of common European data spaces.
- Increased number of city planning departments / approaches using common data and (replicable) elements and processes.
- Consolidated city sensor network specifications, complemented by appropriate data gathering approaches for soft data.
- Improved performance of AI based self-learning systems for optimization of positive clean energy districts and bottom-up complex models.
- Enhanced innovation capacity of local/regional administrations and accelerated uptake of shared, smart and sustainable zero emission solutions.
Smart City Theme
Contact
Name
Leonīds Ribickis
Organisation
RĪGAS TEHNISKĀ UNIVERSITĀTE (RTU)
Email
leonids.ribickis@rtu.lv
Country
Latvia