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Amongst all the major hazard aspects for the health of people in big conglomerates is the increase of the particulate matter concentration. Traditional systems for particulate matter (PM) monitoring have a great number of drawbacks but the main issues are economical and are related to the installation costs and never ending periodical maintenance expenses. After all there are installations of such systems but their number is limited and having in mind the growth of population, cities and industry areas, there is even a bigger need for more information on air quality because PM changes non-linearly, has a wide range and different sources. In this paper, we propose an approach, based on low-cost sensor nodes, for real-time measuring and obtaining information about the PM concentration. The adoption of that approach allows for a detailed study of the intensities of pollution and its sources. The system power supply is powered by a PV module. The power supply unit is designed using a model-based design that is a new approach to prototyping power-operated electronic devices with guaranteed performance.
This paper presents an approach for implementing an automated hit detection and score calculation system for a steel dartboard using a standard webcam. First, the rectilinear field separations of the dartboard are described mathematically by means of line slopes and are than stored. These slopes serve as a basis for later score calculation. In addition, thrown darts have to be detected and the pixel at which the dart cuts the dartboard has to be determined. When this information is known, a comparison is made using the line slopes, allowing the field number of the hit to be detected. The decision for single, double or triple hit is made by evaluating the defined colors on the dartboard. All these functions are then packaged in a Matlab GUI.
The paper describes a systematic approach for a precise short-time cloud coverage prediction based on an optical system. We present a distinct pre-processing stage that uses a model based clear sky simulation to enhance the cloud segmentation in the images. The images are based on a sky imager system with fish-eye lens optic to cover a maximum area. After a calibration step, the image is rectified to enable linear prediction of cloud movement. In a subsequent step, the clear sky model is estimated on actual high dynamic range images and combined with a threshold based approach to segment clouds from sky. In the final stage, a multi hypothesis linear tracking framework estimates cloud movement, velocity and possible coverage of a given photovoltaic power station. We employ a Kalman filter framework that efficiently operates on the rectified images. The evaluation on real world data suggests high coverage prediction accuracy above 75%.
Comparison of Time Warping Algorithms for Rail Vehicle Velocity Estimation in Low Speed Scenarios
(2017)
In this contribution, we propose an system setup for the detection andclassification of objects in autonomous driving applications. The recognition algo-rithm is based upon deep neural networks, operating in the 2D image domain. Theresults are combined with data of a stereo camera system to finally incorporatethe 3D object information into our mapping framework. The detection systemis locally running upon the onboard CPU of the vehicle. Several network archi-tectures are implemented and evaluated with respect to accuracy and run-timedemands for the given camera and hardware setup.
A novel approach for synchronization and calibration of a camera and an inertial measurement unit (IMU) in the research-oriented visual-inertial mapping-and localization-framework maplab is presented. Mapping and localization are based on detecting different features in the environment. In addition to the possibility of creating single-case maps, the included algorithms allow merging maps to increase mapping accuracy and obtain large-scale maps. Furthermore, the algorithms can be used to optimize the collected data. The preliminary results show that after appropriate calibration and synchronization maplab can be used efficiently for mapping, especially in rooms and small building environments.
The precise positioning of mobile systems is a prerequisite for any autonomous behavior, in an industrial environment as well as for field robotics. The paper describes the set up for an experimental platform and its use for the evaluation of simultaneous localization and mapping (SLAM) algorithms. Two approaches are compared. First, a local method based on point cloud matching and integration of inertial measurement units is evaluated. Subsequent matching makes it possible to create a three-dimensional point cloud that can be used as a map in subsequent runs. The second approach is a full SLAM algorithm, based on graph relaxation models, incorporating the full sensor suite of odometry, inertial sensors, and 3D laser scan data.
Mit der Implementierung sowie einer anschließenden aussagekräftigen Evaluierung, soll das, visuelle-inertiale Kartierungs- und Lokalisierungssystem maplab analysiert werden. Hierbei basiert die Kartierung bzw. Lokalisierung auf der Detektion von Umgebungsmerkmalen. Neben der Möglichkeit der Kartenerstellung besteht ferner die Option, mehrere Karten zu fusionieren und somit weitreichende Gebiete zu kartieren sowie für weitere Datenauswertungen zu nutzen. Aufgrund der Durchführung und Bewertung der Ergebnisse in unterschiedlichen Anwendungsszenarien zeigt sich, dass maplab besonders zur Kartierung von Räumen bzw. kleinen Gebäudekomplexen geeignet ist. Die Möglichkeit der Kartenfusionierung bietet weiterhin die Option, den Informationsgehalt von Karten zu erhöhen, welches die Effektivität für eine anschließende Lokalisierung steigert. Bei wachsender Kartierungsgröße hingegen zeigt sich jedoch eine Vergrößerung geometrischer Inkonsistenzen.
Bei dem vorgestellten Ansatz soll der Auftreffpunkt des Pfeils durch die Kreuzkorrelation von Audio-Signalen bestimmt werden. Das Auftreffen des Pfeils erzeugt ein charakteristisches Geräusch, welches von mehreren Mikrofonen in bestimmter Anordnung um die Dartscheibe herum in elektrische Signale umgewandelt wird. Mithilfe der Schallgeschwindigkeit und den Zeitdifferenzen, welche die Schallwelle zu den einzelnen Mikrofonen benötigt soll dann der Auftreffpunkt berechnet werden.
The need to measure basic aerosol parameters has increased dramatically in the last decade. This is due mainly to their harmful effect on the environment and on public health. Legislation requires that particle emissions and ambient levels, workplace particle concentrations and exposure to them are measured to confirm that the defined limits are met and the public is not exposed to harmful concentrations of aerosols.