Identification Of Hidden Tags Using Time Of Arrival: Iot Devices

The new algorithm for Location-of-Things (LoT) in IOT for Geospatial tagging of object is developed. The idea behind LOT applications is to use Two-Way Time –of-Arrival (low cost, off the shelf component) ranging the devices to perform localization of tags. As first step of the process the demonstration of how conventional the Two-Way Time-Of-Arrival (TW-ToA) localization algorithms may experience performance degradation in cases where some of the Access Points (APs) are outside the communication range of tags. The second step shows that one can make use of the audibility information (which indicates whether an AP is able or unable to communicate with the tags in IOT). The leveraging process on the available information, as a result reformulation of the localization problem as a statistical non-linear estimation. The information received, is coupled with the ranging observations from the audible Access Points (APs) which lead to provide a new Maximum LikeHood Estimation (MLE) algorithm for the target. The proposed approach provides the considerable improvement for the location performance by mitigating the well-known ambiguity problem that arises when only a few Access Points (Aps) are audible. The addition of Grid based localization technique is used to estimate the target location, under the proposed framework. The target location that is identified is sent to the server or base station.