Indoor location tracking system using neural network based on bluetooth
dc.Affiliation | October University for modern sciences and Arts (MSA) | |
dc.contributor.author | Hassan A.M.A. | |
dc.contributor.other | Department of Electronics and Communications Engineering | |
dc.contributor.other | October University for Modern Sciences and Arts | |
dc.contributor.other | 6 October City | |
dc.contributor.other | Egypt | |
dc.date.accessioned | 2020-01-09T20:41:31Z | |
dc.date.available | 2020-01-09T20:41:31Z | |
dc.date.issued | 2016 | |
dc.description | Scopus | |
dc.description.abstract | This paper introduces the design and implementation of a Bluetooth based on indoor location tracking system. This system utilizes the integrated Bluetooth modules in any today's mobile phones to specify and display the location of the individuals in a certain building. The proposed system aim for location tracking/monitoring and marketing applications for whom want to locate individuals carrying mobile phones and advertise products and services. It is an integrated embedded and desktop system that helps the user to get the location of customers/inhabitants/employee within a certain region. The system is composed of a Server Module which is a java application that runs over desktop PC and is used to display the locations of the nearby mobile phones and send location based advertising message. This paper is aimed also to enhance the system positioning estimation accuracy by choosing the suitable number of neurons used in the neural network. � 2016 IEEE. | en_US |
dc.identifier.doi | https://doi.org/10.1109/ICEEOT.2016.7754772 | |
dc.identifier.isbn | 9.78E+12 | |
dc.identifier.other | https://doi.org/10.1109/ICEEOT.2016.7754772 | |
dc.identifier.uri | https://ieeexplore.ieee.org/document/7754772 | |
dc.language.iso | English | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.relation.ispartofseries | International Conference on Electrical, Electronics, and Optimization Techniques, ICEEOT 2016 | |
dc.subject | Accuracy | en_US |
dc.subject | Customers | en_US |
dc.subject | Mobile phones | en_US |
dc.subject | Neurons | en_US |
dc.subject | Objects | en_US |
dc.subject | Services | en_US |
dc.subject | Bluetooth | en_US |
dc.subject | Cellular telephones | en_US |
dc.subject | Java programming language | en_US |
dc.subject | Location | en_US |
dc.subject | Marketing | en_US |
dc.subject | Mobile devices | en_US |
dc.subject | Mobile phones | en_US |
dc.subject | Neural networks | en_US |
dc.subject | Neurons | en_US |
dc.subject | Telephone sets | en_US |
dc.subject | Tracking (position) | en_US |
dc.subject | Accuracy | en_US |
dc.subject | Customers | en_US |
dc.subject | Design and implementations | en_US |
dc.subject | Indoor location tracking | en_US |
dc.subject | Location-based advertising | en_US |
dc.subject | Marketing application | en_US |
dc.subject | Objects | en_US |
dc.subject | Services | en_US |
dc.subject | Cellular telephone systems | en_US |
dc.title | Indoor location tracking system using neural network based on bluetooth | en_US |
dc.type | Conference Paper | en_US |
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dcterms.source | Scopus |
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