Cloud-based simulation for services based on crowd-sensing


DFRC AG, a Swiss-based SME, operates LBASense, a service which is able to measure crowd behaviour anonymously on a city-wide scale. The service, which is currently operated in Bern (CH), Zug (CH), Skeleftea (SE), Prague (CZ) and Singapore, utilises an extensive process of “fingerprinting” the cellular network radio signals in order to calculate the location of mobile phones. The current process, which uses the Amazon EC2 cloud infrastructure, is able to extrapolate N measurement points onto a map of cellular coverage. The most expensive part of the current system is not the processing itself, but the actual process of taking measurements at specific points. This requires a lot of time and special measurement equipment.

The goal of this experiment is therefore to improve the mapping by offering a near real-time (in terms of hours) process to optimise the sampling procedure using a combination of simulation tools and actual measurements. This process, called ‘Sample, Simulate, Sample, Map (SSSM),’ is expected to reduce the city mapping time from weeks to days, and the cost by at least 50%. For DFRC, the ability to access a cost-effective and ‘one stop shop’ HPC service enables them to significantly reduce the effort required to deploy the system. It is estimated that the results of this experiment will result in a saving of around 25,000 Euros in costs for LBASense, mainly due to the significant reduction in manpower needed to deploy the system.

By taking advantage of advanced simulation services and tools running on a cloud infrastructure, DFRC will be able to offer a cheaper, faster and more targeted service, which will enhance their competitive position in the market.



DRFC AG, University of Stuttgart

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