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In order to increase the robustness of localisation and victim detection in low visibility situations it is necessary to fuse several sensors. The most common sensor used in robotics is the 2D laser scanner which delivers distance measurements. In combination with a camera the gained information can be supported by visual
information about the environment. Thermal cameras are ideal for finding objects with a certain temperature, but they do not deliver distance information. The difficulty in fusing these two sensors is, that a correspondence between each distance measurement and its corresponding pixel within the thermal image needs to be found.
As the laser scanner only displays one plane, this is not an intuitive task. A special triangular calibration target, covering all six degrees of freedom and being visible for both sensors, was developed. In the end the transformation between each laser scan point and its corresponding thermal image pixel is given. This
allows for assigning every laser measurement within the field of view a corresponding thermal pixel. The final application will enable detection of human beings and display the distance required to reach them.
The design of retrofitted energy efficient buildings is a promising option towards achieving a cost-effective improvement of the overall building sector’s energy performance. With the aim of discovering the best design for a retrofitting project in an automatic manner, a decision making (or optimization) process is usually adopted, utilizing accurate building Simulation models towards evaluating the candidate retrofitting scenarios. A major factor which affects the Overall computational time of such a process is the simulation execution time. Since high complexity and prohibitive simulation execution time are predominantly due to the full-scale, detailed simulation, in this work, the following simulation-time reduction methodologies are evaluated with respect to accuracy and computational effort in a test building: Hierarchical clustering; Koopman modes; and Meta-models. The simplified model that would be the outcome of these approaches, can be utilized by any optimization approach to discover the best retrofitting option.
The deployment of technical building management services is a requirement to further reduce energy demand of future and existing buildings. Automating the process of configuring and deploying technical building management services such as fault detection and diagnosis of technical Equipment seems to be a promising path to intensify the adoption of these services. In this work we present a data processing and analytics execution platform which allows the deployment of ontology-based, automated technical building Management services on a large-scale. We present the platform architecture and results from a reference implementation performing rule-based fault detection on offline air handling unit data.