Eun-Kyung Jo, Eun-Seok Lee, Byeong-Seok Shin

KIPS Transactions on Computer and Communication Systems, Vol. 11, No. 10, pp. 345-352, Oct. 2022
https://doi.org/10.3745/KTCCS.2022.11.10.345,   PDF Download:
Keywords: Edge Computing, LIDAR, Guard System, Point cloud, Data Transformation
Abstract

Recent LiDAR(Light Detection And Ranging) sensor is used for scanning object around in real-time. This sensor can detect movement of the object and how it has changed. As the production cost of the sensors has been decreased, LiDAR begins to be used for various industries such as facility guard, smart city and self-driving car. However, LiDAR has a large input data size due to its real-time scanning process. So another way for processing a large amount of data are needed in LiDAR system because it can cause a bottleneck. This paper proposes edge computing to compress massive point cloud for processing quickly. Since laser’s reflection range of LiDAR sensor is limited, multiple LiDAR should be used to scan a large area. In this reason multiple LiDAR sensor’s data should be processed at once to detect or recognize object in real-time. Edge computer compress point cloud efficiently to accelerate data processing and decompress every data in the main cloud in real-time. In this way user can control LiDAR sensor in the main system without any bottleneck. The system we suggest solves the bottleneck which was problem on the cloud based method by applying edge computing service.

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