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Tracing-vector hierarchical storage mechanism for internet-of-things perception data

A technology of perceiving data and hierarchical storage, applied in database indexing, database updating, electronic digital data processing, etc., can solve the problem that semantic query does not have much meaning

Inactive Publication Date: 2017-08-11
BEIJING UNIV OF TECH
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AI Technical Summary

Problems solved by technology

[0008] In addition, multimedia sampling data is unstructured data, which itself does not have much meaning for semantic query. Only the semantic information extracted through multimedia analysis is valuable.

Method used

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  • Tracing-vector hierarchical storage mechanism for internet-of-things perception data

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Embodiment Construction

[0044] The present invention is explained and elaborated below in conjunction with relevant accompanying drawings:

[0045] The present invention takes taxi traffic data in Beijing as an example to study, and the original collected data is as follows: Figure 2.1 shown.

[0046] (1) Storage efficiency test

[0047] Inspired by the Bezier curve fitting algorithm, the function of storing trajectory data is designed, the state vector is extracted from the sampled data, and the vector sequence of storing trajectory data information is generated;

[0048] According to the trajectory data, the position of the vehicle is marked with latitude and longitude. In the case of ensuring accuracy, set the threshold value u=0.0005 to extract vector activities, store all trajectory data information in the vector sequence, and count the total amount of sampled data and vector activities. The number of updates is obtained, and the results are shown in Table 1 and Figure 2.1 shown.

[0049] ...

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Abstract

The invention discloses a tracing-vector hierarchical storage mechanism for internet-of-things perception data. The storage of the internet-of-things perception big data is divided into two layers: a tracing storage layer and a vector storage layer. In the tracing storage layer, a simple and quick storage method is adopted for realizing efficient storage of original sampling data, and vector data is uploaded to the vector storage layer through vector fitting and updating policies. In the vector storage layer, through a vector sequence-based perception big data storage model and query and analysis methods, efficient processing of the perception big data is realized. A vector is defined as a state change mode of a monitored object; and a state of the internet-of-things monitored object lasts for a relatively long time according to a law generally, and the state, lasting for the relatively long time, of the monitored object can be described by using the vector, so that while the data precision is ensured, the data updating and storage costs of the vector storage layer are greatly reduced.

Description

technical field [0001] The invention belongs to the field of big data analysis and management, and relates to a method for variable speed and hierarchical storage of data perceived by the Internet of Things. Background technique [0002] With the rapid development of the Internet of Things technology and its related applications (such as smart cities, sensing China, intelligent transportation, emergency management, intelligent security, etc.), how to effectively store, query and analyze massive Internet of Things sensing data has become an urgent problem to be solved. The key issue. IoT sensing data refers to sampling data dynamically collected by various sensing devices (including various sensor devices and multimedia monitoring devices) in the IoT system. According to the forecast of the authoritative organization IDC, the global data volume will reach 35ZB in 2020, which is 45 times that of 2009. For example, in terms of intelligent traffic monitoring, Beijing currently...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/23G06F16/22
Inventor 丁治明曹阳段立娟才智陈军成任付杰
Owner BEIJING UNIV OF TECH
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