Details
| Original language | English |
|---|---|
| Pages (from-to) | 444-449 |
| Number of pages | 6 |
| Journal | International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives |
| Volume | 38 |
| Publication status | Published - 2010 |
| Event | Joint International Conference on Theory, Data Handling and Modelling in GeoSpatial Information Science - Hong Kong, Hong Kong Duration: 26 May 2010 → 28 May 2010 |
Abstract
This paper presents a concept for the collaborative distributed acquisition and refinement of geo-related information. The underlying idea is to start with a massive amount of moving sensors which can observe and measure a spatial phenomenon with an unknown, possibly low accuracy. Linking these measurements with a limited number of measuring units with higher order accuracy leads to an information and quality augmentation in the mass sensor data. This is achieved by distributed information integration and processing in a local communication range. The approach will be demonstrated with the example where cars measure rainfall indirectly by the wiper frequencies. The a priori unknown relationship between wiper frequency and rainfall is incrementally determined and refined in the sensor network. For this, neighboring information of both stationary rain gauges of higher accuracy and neighboring cars with their associated measurement accuracy are integrated. In this way, the quality of the measurement units can be enhanced. In the paper the concept for the approach is presented, together with first experiments in a simulation environment. Each sensor is described as an individual agent with certain processing and communication possibilities. The movement of cars is based on given traffic models. Experiments with respect to the dependency of car density, station density and achievable accuracies are presented. Finally, extensions of this approach to other applications are outlined.
Keywords
- Cooperation, Data acquisition, Distributed processing, Geosensor network, Mapping quality, Meteorology, Mobile, Simulation environment
ASJC Scopus subject areas
- Computer Science(all)
- Information Systems
- Social Sciences(all)
- Geography, Planning and Development
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In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, Vol. 38, 2010, p. 444-449.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Cooperative information augmentation in a geosensor network
AU - Schulze, Malte Jan
AU - Brenner, Claus
AU - Sester, Monika
PY - 2010
Y1 - 2010
N2 - This paper presents a concept for the collaborative distributed acquisition and refinement of geo-related information. The underlying idea is to start with a massive amount of moving sensors which can observe and measure a spatial phenomenon with an unknown, possibly low accuracy. Linking these measurements with a limited number of measuring units with higher order accuracy leads to an information and quality augmentation in the mass sensor data. This is achieved by distributed information integration and processing in a local communication range. The approach will be demonstrated with the example where cars measure rainfall indirectly by the wiper frequencies. The a priori unknown relationship between wiper frequency and rainfall is incrementally determined and refined in the sensor network. For this, neighboring information of both stationary rain gauges of higher accuracy and neighboring cars with their associated measurement accuracy are integrated. In this way, the quality of the measurement units can be enhanced. In the paper the concept for the approach is presented, together with first experiments in a simulation environment. Each sensor is described as an individual agent with certain processing and communication possibilities. The movement of cars is based on given traffic models. Experiments with respect to the dependency of car density, station density and achievable accuracies are presented. Finally, extensions of this approach to other applications are outlined.
AB - This paper presents a concept for the collaborative distributed acquisition and refinement of geo-related information. The underlying idea is to start with a massive amount of moving sensors which can observe and measure a spatial phenomenon with an unknown, possibly low accuracy. Linking these measurements with a limited number of measuring units with higher order accuracy leads to an information and quality augmentation in the mass sensor data. This is achieved by distributed information integration and processing in a local communication range. The approach will be demonstrated with the example where cars measure rainfall indirectly by the wiper frequencies. The a priori unknown relationship between wiper frequency and rainfall is incrementally determined and refined in the sensor network. For this, neighboring information of both stationary rain gauges of higher accuracy and neighboring cars with their associated measurement accuracy are integrated. In this way, the quality of the measurement units can be enhanced. In the paper the concept for the approach is presented, together with first experiments in a simulation environment. Each sensor is described as an individual agent with certain processing and communication possibilities. The movement of cars is based on given traffic models. Experiments with respect to the dependency of car density, station density and achievable accuracies are presented. Finally, extensions of this approach to other applications are outlined.
KW - Cooperation
KW - Data acquisition
KW - Distributed processing
KW - Geosensor network
KW - Mapping quality
KW - Meteorology
KW - Mobile
KW - Simulation environment
UR - http://www.scopus.com/inward/record.url?scp=84923653528&partnerID=8YFLogxK
M3 - Conference article
AN - SCOPUS:84923653528
VL - 38
SP - 444
EP - 449
JO - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
JF - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
SN - 1682-1750
T2 - Joint International Conference on Theory, Data Handling and Modelling in GeoSpatial Information Science
Y2 - 26 May 2010 through 28 May 2010
ER -