Driven by the core technologies, i.e., sensor-based autonomous data acquisition and the cloud-based big data analysis, IoT automates the actuation of data-driven intelligent actions on the connected objects. This automation enables numerous useful real-life use-cases, such as smart transport, smart living, smart cities, and so on. However, recent industry surveys reflect that data-related challenges are responsible for slower growth of IoT in recent years. For this reason, this article presents a systematic and comprehensive survey on IoT Big Data (IoTBD) with the aim to identify the uncharted challenges for IoTBD. This article analyzes the state-of-the-art academic works in IoT and big data management across various domains and proposes a taxonomy for IoTBD management. Then, the survey explores the IoT portfolio of major cloud vendors and provides a classification of vendor services for the integration of IoT and IoTBD on their cloud platforms. After that, the survey identifies the IoTBD challenges in terms of 13 V’s challenges and envisions IoTBD as “Big Data 2.0.” Then the survey provides comprehensive analysis of recent works that address IoTBD challenges by highlighting their strengths and weaknesses to assess the recent trends and future research directions. Finally, the survey concludes with discussion on open research issues for IoTBD.

中文翻译：

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物联网大数据调查

在核心技术的驱动下，即基于传感器的自主数据采集和基于云的大数据分析，物联网将数据驱动的智能动作对连接对象的驱动自动化。这种自动化实现了许多有用的现实生活用例，例如智能交通、智能生活、智能城市等。然而，最近的行业调查表明，与数据相关的挑战是近年来物联网增长放缓的原因。出于这个原因，本文对物联网大数据 (IoTBD) 进行了系统而全面的调查，旨在确定 IoTBD 面临的未知挑战。本文分析了各个领域的物联网和大数据管理的最新学术著作，并提出了 IoTBD 管理的分类法。然后，该调查探讨了主要云供应商的物联网产品组合，并提供了供应商服务的分类，用于在其云平台上集成物联网和 IoTBD。之后，该调查根据 13 V 的挑战确定了 IoTBD 的挑战，并将 IoTBD 设想为“大数据 2.0”。然后，该调查通过突出其优缺点来评估近期趋势和未来研究方向，对解决 IoTBD 挑战的近期工作进行全面分析。最后，调查以对 IoTBD 的开放研究问题的讨论结束。” 然后，该调查通过突出其优势和劣势，对近期解决 IoTBD 挑战的工作进行全面分析，以评估近期趋势和未来研究方向。最后，调查以对 IoTBD 的开放研究问题的讨论结束。” 然后，该调查通过突出其优缺点来评估近期趋势和未来研究方向，对解决 IoTBD 挑战的近期工作进行全面分析。最后，调查以对 IoTBD 的开放研究问题的讨论结束。