HOTSPOTS - Holistic thermographic screening of urban physical objects at transient scales
HOTSPOTS enables new insights and perspectives for city development. According to the project idea innovations in acquisition and sensing as well as densification of geo-referenced city related data are supplemented by novel processing chains in city data analytics. Driven by an integrated scientific approach we develop a novel method in the selection, evaluation and prioritization of infrastructural city development measures which is directly derived from sensed data, hence reducing the risk of ad-hoc decisions or lack in impact.
City-related data are stored fragmented at different data holders in different quality, captured at different time stamps and with varying spatial resolution. Thus, there is a lack of a common data base of consolidated and harmonized data sets. But is already all relevant information recorded and available? Energy efficiency is an important criterion of modern urban planning and optimization. Which data collection ensures that knowledge about the actual energy consumption, the user behavior and the causation are stored promptly and site-specific, in contrast to temporally / spatially blended recorded data?
Contents and Objectives
HOTSPOTS pursues the goal of providing tools and scientific methods to cities in order to capture the current condition of existing buildings in terms of energy efficiency and of providing a decision-making basis for improving this condition. As part of the planned project, a continuous process chain will be developed and validated in the model city Gleisdorf, which aims to help cities in the future to identify, assess and accurately address optimization potentials. Future selection processes in the field of structural measures of urban development are to be made in a transparent and (measurable) data-driven basis, which reduces the risk of ad-hoc decisions or bad investments.
HOTSPOTS is a methodically closed process chain, realized by overlapping project modules.
A 3D Thermal Register, which is created from aerial imagery, forms the data basis for the project. The task is the region-wide collection of thermal data in the urban area. These single frames are linked to a holistic city-wide data base and lifted into the third dimension by deriving a 3D model from the image data.
Within the 3D Thermal Register, "critical spots" are then identified. Critical spots in the city define infrastructure cells at the district level, which have a particularly large potential for optimization. These areas are then analyzed in detail in the following project modules.
A close-range data acquisition is then performed in order to perform a selective expansion of the database within a selected infrastructure cell. This includes a mobile data acquisition using a UAV in for the generation of 3D building models. From these models, relevant geometric parameters and detailed thermal information can be derived and serves as input for simulations of optimization scenarios. Another research aspect is the exploitation of selective acquisition and densification of the data in terms of a three-dimensional gas layer model.
Based on this data, a cell-wide but focused critical point analysis takes place. This is followed by the creation of an effective catalog of measures, including impact factors influencing the defined critical spots in the city, which have a particularly large potential for optimization.
Furthermore, a decision support tool is applied for the interactive selection, localization of energy efficiency measures and the simulation of the resulting effects with the calculation of optimal combinations of measures for subspaces.
The highlights of the project can be summarized as follows:
- Metrological and data driven innovations
- Region-wide thermography of Gleisdorf in 3D captured by a specially developed measuring unit
- Acquisition and generation of a three-dimensional gas layer model
- Use of air balloons and UAVs for data acquisition
- Correction of measured thermal data by semantically interpreting the image content
- Methodological access to the integration of thermal and statistical data
- Semi-automatic update of the state data by additional flights and thus the possibility of monitoring the effects of energy efficiency and heating optimization measures with regard to the fulfillment of Smart City goals
- Simulation of individual energy saving measures at different spatial scales
- Identification of realistically implementable solutions for renewable and CO2 neutral implementation of renovation strategies
- Development of specific implementation scenarios in terms of short-, medium-and longer-term action plans
- Generation of methods and evaluation metrics which allow transferability of the findings to other small towns and districts
Prospects / Suggestions for future research
The processing chain developed in this project was successfully evaluated in the "model city" of Gleisdorf. The suggested optimization measures were verified via on-site inspections. The implemented methods are applicable to any town or city.
Data acquisition for generating the 3D Thermal Register was carried out using a hot air balloon. This method proved to be feasible and low-cost in principle, but heavily depends on weather and – especially - wind conditions. In future scenarios, using a light plane or a helicopter instead could be of interest, to identify alternatives.
Future application of the processing chain could also help in developing a deeper understanding of thermal and air quality data. Especially the differentiation of relevant information from weather-induced, temporal phenomena is of special interest.
The suitability of the approach will be put to test when it comes to concrete rehabilitation projects derived from or suggested by the simulations, involving owners and decision-makers.
Siemens AG Österreich
DI Claudia Windisch
Project- or cooperation partners
Siemens AG Österreich
DI Claudia Windisch, Video Analytics
Straßganger Straße 315
Tel.: +43 (0) 664 8011763607