Internet of Things (IoT) has been considered as one of the emerging network and information technologies that can comprehend automatic monitoring, identification, and management through a network of smart IoT devices. The effective use of IoT in different areas has improved efficiency and reduced errors. The rapid growth of smart devices such as actuators, sensors, and wearable devices has made the IoT enable for smart and sustainable developments in the area. Physical objects are interlinked with these smart devices for the progression to analyse, process, and manage the surroundings data. Such data can then be further utilised for smarter decisions and postanalysis for different purposes. However, with the limited IoT resources, the management of data is difficult due to the restrictions of transmission power place and energy consumption, and the processing can put pressure on these smart devices. The network of IoT is connected with big data through Internet for manipulating and storing huge bulk of data on cloud storage. The secure framework based on big data through IoT is the awful need of modern society which can be energy efficient in a sustainable environment. Due to the intrinsic characteristics of sensors nodes in the IoT, like data redundancy, constrained energy, computing capabilities, and limited communication range, the issues of data loss are becoming among the main issues which mostly depend on the completeness of data. Various approaches are in practice for the recovery problem of data, such as spatiotemporal correlation and interpolation. These are used for data correlation and characteristics of sensory data. Extracting correlation data became difficult specifically as the coupling degree between diverse perceptual attributes is low. The current study has presented a comprehensive overview on big data and its V’s with Internet of Things to describe the research into the area with in-depth review of existing literature.

中文翻译：

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大数据及其 V 与物联网以发展可持续性

物联网（IoT）被认为是一种新兴的网络和信息技术，可以通过智能物联网设备网络实现自动监控、识别和管理。物联网在不同领域的有效利用提高了效率并减少了错误。执行器、传感器和可穿戴设备等智能设备的快速增长使物联网能够实现该地区的智能和可持续发展。物理对象与这些智能设备相互关联，以分析、处理和管理周围环境数据。然后可以将这些数据进一步用于更明智的决策和不同目的的后期分析。但由于物联网资源有限，受传输功率场所和能耗限制，数据管理困难，处理过程会给这些智能设备带来压力。物联网网络通过互联网与大数据连接，用于操作和存储大量数据在云存储上。通过物联网基于大数据的安全框架是现代社会的迫切需求，它可以在可持续环境中实现节能。由于物联网中传感器节点的固有特性，如数据冗余、能量受限、计算能力和通信范围有限，数据丢失问题正成为主要取决于数据完整性的主要问题之一。实践中对于数据的恢复问题有多种方法，例如时空相关和插值。这些用于数据相关性和感官数据的特征。由于不同感知属性之间的耦合度较低，因此提取相关数据变得困难。当前的研究对大数据及其与物联网的 V 进行了全面概述，以通过对现有文献的深入审查来描述该领域的研究。