Stem – An Iot Based Solution For Tracking Objects

Abstract

Internet Of things (IoT) is an inter-connected networking ecosystem of physical objects also called as "things" embedded with softwares, sensors, electronics provided with unique IP addresses which are accessible through internet and are capable of collecting and sharing data in a network without the intervention of humans. In this journal the author proposes a neural network guided model to track and find real-time updates of objects which will be tracked and updated bythe means of Radio Frequency identification (RFID). This will help corporate resources to be handled in an effective way. In order to assist and smoothen the process of tracking and precisely locating any physical object amongst corporate and professional environment through IoT is our idea. We propose a model called as Sensor based Tracking Enabled Model (STEM) deals with various processes in order to correctly identify, track and locate the essentials and objects used in professional environment Keywords: IOT,RFID,Objecttracking,realtime,sensorsthe help of this advancing technology, any physical object can be connected to internet which can be tagged and precise location of that object can be tracked and the data can also be used for further processing and analysis due to which it is known as Internet Of Things. In this so-called busy world where time is a constraint, we often battle with ourselves for very small fundamental crucial needs such as finding or locating our own essential belongings and stuffs . I.IOT AND RFID The accurate tracking of real time indoor objects based upon the aggregated binary measurements implemented by particle filtering was proposed which were tagged in Ultra High Frequency (UHF) Radio Frequency Identification (RFID) systems [1]. With the fusion of multiple sensors i.e. two laser sensors and camera sensors a novel scheme for object localization and tracking was presented by researchers [2]. A hybrid RFID and computer vision system for fine-grained localization and tracking of tagged objects called as TagVision along with a fusion algorithm was suggested to organically combine the position information given by the CV subsystem, and phase data output by the RFID subsystem [3].The problem of tracking dynamic objects with UHF RFID tags using a Bayesian framework with a mobile robot was addressed. The two stage dynamic motion model was combined with the dual particle filter in order to capture the dynamic motion of the object and to quickly recover from failures in tracking. And this approach was then tested on a Scitos G5 mobile robot through various experiments [4]. The researchers proposed a novel ubiquitous architecture followed by a protocol for tracking mobile objects in real-time based upon the RFID Tags [5] .An internet based concept incorporated with RFID technology was proposed to form an internet based application for the library management and the RFID reader Motorola MC9090 was used for the entire process which was carried inside the library [6]. The way of finding and navigating to an object with...