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Amarina KB 8200 Driver

The sink node is also a sensor node that collects and combines various types of sensed data e.

A Network Coverage Information-Based Sensor Registry System for IoT Environments

In this article, these sensed data are called instant data. The sink node regularly sends the instant data to the mobile devices Amarina KB 8200 users who are in the vicinity of the WSN. Finally, applications running on the mobile devices provide the users with intelligent services through the mash up of heterogeneous instant data. To combine various instant data, the metadata of each instant data must be corrected.

For example, the new terms are defined to be used by other applications. In addition, redundant metadata are removed and relevant metadata are semantically linked to the existing metadata in the Sensor Registry System. For this process, the metadata of each instance data Amarina KB 8200 first submitted to the centralized Sensor Registry System.

Then, a few metadata experts evaluate the submitted metadata, and make corrections, if necessary. In this way, the Sensor Registry System plays an important role in registering and managing the heterogeneous metadata of instant data sent by sensors. In parallel, the mobile device also Amarina KB 8200 metadata associated with the instant data from the Sensor Registry System.

The metadata enables the mobile device to conduct semantically consistent interpretation of the heterogeneous instant data sent by a variety of sensors. In this article, we clearly assume that there are two physically different Amarina KB 8200 in the proposed scheme.


One is a wireless sensor network, in which the mobile devices receive instant data sent by sensors. Through the other network, Amarina KB 8200 mobile devices also receive metadata sent by the Sensor Registry System. Technically, the Sensor Registry System sends the metadata via Internet, Amarina KB 8200 then the mobile device finally receives the metadata sent by a mobile station, which is the end-point of the Internet.

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In particular, we consider communication under bad conditions, where the mobile devices cannot receive any metadata because of the encountered communication problems. We also assume that the wireless sensor network is working Amarina KB 8200 any case.


Consequently, in the proposed system architecture, mobile devices receive instant data from sensors via the wireless sensor network and metadata associated with the instant data from Sensor Registry System via the Internet. It registers and manages the heterogeneous metadata Amarina KB 8200 instant data. Consequently, although the mobile device is transferred to different wireless Amarina KB 8200 networks, it continues to provide service using instant data, overcoming the metadata interoperability problem, which commonly occurs in various sensors around different wireless sensor networks.

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For example, suppose that there are two sensor networks in Korea and the USA. A mobile device receives temperature information from thermometer sensors in Korea, where the sensors collect the information on the centigrade scale. Amarina KB 8200, if the user travels to the USA, their mobile device will experience difficulty in processing temperature data from thermometer sensors in the USA.


This is because all sensors Amarina KB 8200 temperatures in the USA output the temperature using Amarina KB 8200 Fahrenheit temperature scale. To address this metadata interoperability issue, a Sensor Registry System can retain semantically consistent metadata, indicating that Celsius is the same as Fahrenheit.

Path Prediction The goal of the existing path prediction method is to predict a next desired segment among multiple candidate segments while a mobile device is moving along a path. If the current position of a mobile device is in the segment dthe path prediction method can predict either e or f as the next suitable segment.


The next position is determined by the greedy approach—e. In the segment dthe mobile device can prefetch metadata that Amarina KB 8200 necessary for interpreting the instant data that will be sent Amarina KB 8200 the sensors in the segment f when it arrives at the f segment. In the proposed approach, extending the existing path prediction method, when a mobile device is moving to the segment f from the segment dit can forecast, using network coverage information, that the network will be not working in Amarina KB 8200 segment f and mobile devices will not get any metadata in f.

Then, it can bring the metadata in advance, in order to interpret instance data in fusing the prefetched metadata.


In this work, as the network Amarina KB 8200 information, the following information is employed: Otherwise, mobile devices cannot receive any metadata in the area. PP-SRS suffers from a problem related to providing a seamless service.


Non-service areas are areas where the mobile device using a SRS service experiences poor network conditions and does not receive the sensor information from the SRS. The sensor information is used for Amarina KB 8200 the data transmitted by the sensor device, for example, the identifier of the sensor and the unit of measure. When the sensor information does not received, the user Amarina KB 8200 interpret the sensor data. Recent network support coverage information of the non-responding regions of a network can be obtained easily.

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