Experimental Evaluation of Indoor Localization Methods for Industrial IoT Environment
With the evolution of new technology, GPS brings a lot of revolution in the Localization system but it is not an effective solution in Indoor Environment. This is because of the fact that the signals coming from the satellite are attenuated, absorbed, scattered by the walls, roofs, and other objects. Due to this, lots of errors may arise in the system. To overcome this problem sensor node based localization system is used for mobile IoT domain. Recently, in IoT based system, various sensor nodes have been used in different kinds of localization based applications such as Location-Based Services (LBS) and Proximity-Based Services (PBS). However, such sensor nodes may not be stable in every environment to provide an accurate positioning. Although there are different localization techniques are available to find out the location of any object, but there is a common challenge of finding best localization technique suitable for most of the environment. This work investigates different existing indoor localization methods for its practical suitability in Lab and actual Industrial environment for deployment on IoT nodes. A mobile application has also been developed to implement four state-of-the-art localization techniques for getting the position and calculating its accuracy in different environments. During the experiment, BLE Beacons are used as sensor nodes due to their ease of deployment, lower complexity, lower cost, and higher power consumption. The error in the accuracy of estimated position got calculated in terms of Average Error. According to the experimental result in real environments it has been revealed that the Weighted Centroid Localization technique provides better accuracy in industrial as well as laboratory environment.
BLE, GPS, Indoor environment, RSSI, WSN
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