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We present methods to predict and validate home and work places of anonymized users using their mobile network data. Knowledge of home and work place of a user is essential in order to find his (and overall population) mobility profiles. There are many methods that predict home and work places using GPS data. But unlike GPS data, mobile network data using GSM do not provide the exact location of a...
In this paper, we present the performance of an RSSI based localization scheme for wireless sensor networks (WSN) that is proposed to reduce the adverse effects of shadowing caused by obstacles in the field of deployment. The proposed scheme applies spatial correlations between a set of candidate solutions that are obtained from subsets of beacon signals that are used for localization. We analyze...
Constrained particle filter is widely used in indoor localization applications. With environmental information, the cascaded hypothesis modifier can improve accuracy by rejecting particles those have invalid transitions. However, the memory requirement and computation complexity of constrained particle filter are both large, and the low spatial correlations between the sequentially accessed particles...
As the increasing amount of data is collected in mobile wireless networks for emerging pervasive applications, data-centric storage provides energy-efficient data dissemination and organization. One of the approaches in data-centric storage is that the nodes that collected data will transfer their data to other neighboring nodes that store the similar type of data. However, when the nodes are mobile,...
Location fingerprinting techniques generally make use of existing wireless network infrastructure. Consequently, the positions of the access points (APs), which constitute an integral part of a location system, will invariably be dictated by the network administrator's convenience regarding data communication. But the localization accuracy of fingerprint-based solutions is largely dependent on the...
Due to adverse aqueous environments, non-negligible node mobility and large network scale, localization for large-scale mobile underwater sensor networks is very challenging. In this paper, by utilizing the predictable mobility patterns of underwater objects, we propose a scheme, called Scalable Localization scheme with mobility prediction (SLMP), for underwater sensor networks. In SLMP, localization...
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