Virtual sensors - Synthesizing dynamic crowdsensing data into information on static instances

There has been a steady increase in applications that rely on crowdsensing to gather data for analysis purposes. Crowdsensing enables the use of dynamic sensors to collect data on static objects of interest. However, using dynamic sensors in this way causes a problem. The focus of the collected data is on the position of the sensor, not on the object of interest. This results in difficulties in tracking the object of interest in terms of what part of the data from the dynamic sensor describes the object of interest. To shift the focus from the dynamic sensors to a static object, the virtual sensor is introduced. A virtual sensor enables the grouping of data from different dynamic sensors into a single virtual sensor based on measurement positions. The data from the multiple dynamic sensors can be analyzed to provide information per virtual sensor. The data structure of a visual sensor is close to the SensorThings API data structure, which can be expanded to support virtual sensors by adding an additional entity.Architecture and the Built EnvironmentOLD Department of GIS TechnologyOptical and Laser Remote Sensin

Using Existing Wi-Fi networks to Provide Information on Occupancy and Exploitation of Educational Facilities using at Delft University of Technology

This executive summary provides an overview of the work done by project in_sight for the TU Delft MSc Geomatics for the Built Environment. The research subject is the usage of WiFi monitoring data to calculate the occupation of the TU Delft campus in order to determine the exploitation of the educational facilities.Architecture and The Built EnvironmentGeo-information TechnologyGeomatics for the Built Environmentin_sigh

In_sight: Using Existing Wi-Fi networks to Provide Information on Occupancy and Exploitation of Educational Facilities using at Delft University of Technology

The distribution of people in buildings, the occupancy of lecture-, work- and study places and the accessibility of facilities are essential information at university campuses who have to cope with limited and even shrinking budgets and huge, rising real estate costs. Only little insight is gained in both occupancy and movement patterns with traditional counting techniques and user-based questionnaires. Management teams state that rooms and facilities are hardly used, though staff and students complain about overcrowded facilities and limited flexibility. Actual and accurate data on a 24/7 scale with high-granularity is missing.In general Facility- and Asset Management lacks efficient methods for realtime, comprehensive and high-granularity information of location, capacity and use of tangible and intangible assets. Asset management could benefit from more detailed, more accurate and longitudinal data on assets, providing more insight into efficiency and effectiveness on different levels of scale through time.Existing technologies could provide a platform delivering those required insights. Navigation- and communication technologies such as GNSS, Wi-Fi, Bluetooth, RFID can be used to ‘locate’ users, estimate intensities and reveal patterns of movement and patterns of use. For Asset management indoor localisation is essential.OLD Urban DesignOLD Department of GIS Technolog