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

IF 1.5 Q3 TELECOMMUNICATIONS
Ado Adamou Abba Ari, Hamayadji Abdoul Aziz, Arouna Ndam Njoya, Moussa Aboubakar, Assidé Christian Djedouboum, Ousmane Thiare, Alidou Mohamadou
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Abstract

The 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.

Abstract Image

物联网网络中的数据收集:架构、解决方案、协议和挑战
物联网(IoT)是一种最新技术,旨在通过提供连接、控制和自动化物理世界中物体的能力,为人类的日常生活提供便利。按照这种逻辑,物联网有助于改善我们在各个领域(如农业、工业、医疗保健、交通等)的生产和工作方式。从根本上说,物联网网络由配备传感器和发射器的物理设备组成,这些设备相互连接和/或连接到互联网。其主要目的是收集数据并将数据传输到服务器或云等存储系统,以便进行处理和分析,最终促进快速决策或提升用户体验。在 "互联对象 "领域,一个有效的物联网数据收集系统发挥着至关重要的作用,它能带来多种益处,如实时数据监控、增强决策、提高运营效率等。然而,由于与联网对象相关的资源限制,如内存和电池不足,甚至是一次性设备等。物联网数据收集给研究人员和企业带来了可扩展性、安全性、互操作性和灵活性等方面的挑战。作者对当前的物联网数据收集技术进行了分类,并根据作者分析和阐述的主题对这些方法进行了比较评估。此外,作者还全面分析了物联网数据收集的最新进展,重点介绍了不同的数据类型和来源、从连接的传感器到存储平台(服务器或云)的传输协议、物联网数据收集框架以及简化收集流程的原则。最后,总结了有效收集物联网数据的最重要研究问题和未来前景。
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来源期刊
IET Wireless Sensor Systems
IET Wireless Sensor Systems TELECOMMUNICATIONS-
CiteScore
4.90
自引率
5.30%
发文量
13
审稿时长
33 weeks
期刊介绍: IET Wireless Sensor Systems is aimed at the growing field of wireless sensor networks and distributed systems, which has been expanding rapidly in recent years and is evolving into a multi-billion dollar industry. The Journal has been launched to give a platform to researchers and academics in the field and is intended to cover the research, engineering, technological developments, innovative deployment of distributed sensor and actuator systems. Topics covered include, but are not limited to theoretical developments of: Innovative Architectures for Smart Sensors;Nano Sensors and Actuators Unstructured Networking; Cooperative and Clustering Distributed Sensors; Data Fusion for Distributed Sensors; Distributed Intelligence in Distributed Sensors; Energy Harvesting for and Lifetime of Smart Sensors and Actuators; Cross-Layer Design and Layer Optimisation in Distributed Sensors; Security, Trust and Dependability of Distributed Sensors. The Journal also covers; Innovative Services and Applications for: Monitoring: Health, Traffic, Weather and Toxins; Surveillance: Target Tracking and Localization; Observation: Global Resources and Geological Activities (Earth, Forest, Mines, Underwater); Industrial Applications of Distributed Sensors in Green and Agile Manufacturing; Sensor and RFID Applications of the Internet-of-Things ("IoT"); Smart Metering; Machine-to-Machine Communications.
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