The Devices of the Internet of Things Based on the Recognition of Handwriting Words with Mobile Assisted
Dublin Core
Title
The Devices of the Internet of Things Based on the Recognition of Handwriting Words with Mobile Assisted
Subject
Handwriting Recognition
Neural Networks
Internet of Things (IoF). Mobile
Description
At the moment, all observed forms of communication are reduced either to a person-to-person scheme or person-to-device. But the Internet of Things (IoT) offers us a tremendous Internet future, in which will appear the communication type machine-machine (M2M). This makes it possible to integrate all communications into a common infrastructure, allowing not only to manage everything that is around us but also providing information about the state of these things. The purpose of this paper is to create the client part of the client-server system for remote control of home appliances using cloud services through commands entered using handwritten words. For this, we develop algorithms and methods for handwriting recognition using neural networks and implement a mobile application on the Android platform, which allows remote control of devices via cloud services based on commands entered using handwritten words. Anyway, this article will give a good understanding to other researchers who want to start their research on the IoT and will contribute to the effective accumulation of knowledge.
Creator
Shakah, Ghazi Hussein
Source
International Journal of Interactive Mobile Technologies (iJIM); Vol. 14 No. 04 (2020); pp. 74-85
1865-7923
Publisher
International Association of Online Engineering (IAOE), Vienna, Austria
Date
2020-03-12
Rights
Copyright (c) 2020 ghazi hussein shakah
Relation
Format
application/pdf
Language
eng
Type
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
Identifier
Citation
Ghazi Shakah Hussein, The Devices of the Internet of Things Based on the Recognition of Handwriting Words with Mobile Assisted, International Association of Online Engineering (IAOE), Vienna, Austria, 2020, accessed November 7, 2024, https://igi.indrastra.com/items/show/1610