Data collection in IoT networks: Architecture, solutions, protocols and challenges

Author:

Abba Ari Ado Adamou12ORCID,Aziz Hamayadji Abdoul12,Njoya Arouna Ndam3,Aboubakar Moussa1,Djedouboum Assidé Christian14,Thiare Ousmane5,Mohamadou Alidou1

Affiliation:

1. LaRI Lab University of Maroua Maroua Cameroon

2. CREATIVE Lab Insitute of Fine Arts and Innovation University of Garoua Garoua Cameroon

3. Department of Computer Engineering University Institute of Technology University of Ngaoundéré Ngaoundéré Cameroon

4. Department of Computer Science and Telecommunications University of Moundou Moundou Chad

5. LANI Lab Gaston Berger University of Saint‐Louis Saint‐Louis Senegal

Abstract

AbstractThe Internet of Things (IoT) is the recent technology intended to facilitate the daily life of humans by providing the power to connect, control and automate objects in the physical world. In this logic, the IoT helps to improve our way of producing and working in various areas (e.g. agriculture, industry, healthcare, transportation etc). Basically, an IoT network comprises physical devices, equipped with sensors and transmitters, that are interconnected with each other and/or connected to the Internet. Its main objective is to gather and transmit data to a storage system such as a server or cloud to enable processing and analysis, ultimately facilitating rapid decision‐making or enhancements to the user experience. In the realm of Connected Objects, an effective IoT data collection system plays a vital role by providing several benefits, such as real‐time data monitoring, enhanced decision‐making, increased operational efficiency etc. However, because of the resource limitations linked to connected objects, such as low memory and battery, or even single‐use devices etc. IoT data collecting presents several challenges including scalability, security, interoperability, flexibility etc. for both researchers and companies. The authors categorise current IoT data collection techniques and perform a comparative evaluation of these methods based on the topics analysed and elaborated by the authors. In addition, a comprehensive analysis of recent advances in IoT data collection is provided, highlighting different data types and sources, transmission protocols from connected sensors to a storage platform (server or cloud), the IoT data collection framework, and principles for streamlining the collection process. Finally, the most important research questions and future prospects for the effective collection of IoT data are summarised.

Publisher

Institution of Engineering and Technology (IET)

Reference206 articles.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3