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首页> 外文会议>International Conference on Cognitive Informatics and Soft Computing >Adoption of Big Data Streaming Techniques for Simultaneous Localization and Mapping (SLAM) in IoT-Aided Robotics Devices
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Adoption of Big Data Streaming Techniques for Simultaneous Localization and Mapping (SLAM) in IoT-Aided Robotics Devices

机译：采用大数据流技术，用于IOT-Aided机器人设备中的同时定位和映射（SLAM）

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The evolution of low-powered devices through the Internet of Things (IoT) has enabled the technology community to come up with solutions to problems faced by pervasive networks. IoT enables communication between devices, i.e., "machine to machine" communication. With this regard, the evolution of IoT-aided Robots was birthed. Robotic devices constantly need to communicate and share their location and the surrounding environment, a concept known as Simultaneous Localization and Mapping (SLAM). Normally this data is shared through traditional techniques, but with the exploding data universe, there is need to come up with an alternative, fast, and efficient methods for management and transfer of data. This research proposes the adoption of big data streaming techniques to manage data transfer and communication during SLAM. Ultimately, big data streaming techniques will be used in critical applications where the analytic process has to happen in real time and decisions need to be made within a short time.
机译：低功耗设备通过互联网（IOT）的演变使技术社区能够提出解决普及网络所面临的问题。 IOT使设备之间的通信，即“机器到机器”通信。众所周知，IOT-AIVED机器人的演变是诞生的。机器人设备不断需要沟通和共享他们的位置和周围环境，这是一个称为同时定位和映射（SLAM）的概念。通常，此数据通过传统技术共享，但随着爆炸数据宇宙，需要提出替代，快速，有效的管理和传输数据的方法。本研究提出了采用大数据流技术来管理在SLAM期间的数据传输和通信。最终，大数据流技术将用于关键应用中，其中分析过程必须实时发生，并且需要在短时间内进行。

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