Real-Time Adaptive Data Transmission Against Various Traffic Load in Multi-LIDAR Sensor Network for Indoor Monitoring

Abstract

One of the key components in smart cities is smart monitoring, a process for collecting information to efficiently manage the infrastructures and resources and enables citizens to engage in intelligent activities. For both indoor and outdoor monitoring, light detection and ranging (LIDAR) technology has been used to collect three-dimensional data useful for smart monitoring. Blind spots can be effectively covered by aggregating point clouds from multiple LIDAR sensors (sensors hereafter) with different viewpoints. Although multiple-LIDAR (multi-LIDAR) sensor networks have been investigated, prior studies have focused on monitoring outdoor scenes with a relatively low number of sensors, mostly for road safety. For indoor use, however, ten or more sensors are required to eliminate blind spots, as the placement of sensors is limited by ceilings. When the network bandwidth is limited because of other traffic loads, the transmission size needs to be small while including the highly important points. Therefore, adaptive control is required for sensor networks. We propose a system that adaptively controls the data volume of a multi-LIDAR sensor network considering the current network state in real time. It consists of a single edge computer and multiple sensors. While aggregating data streams, the edge computer monitors the current delay status for each sensor and sends notifications to change the data volume by the sensor.We report on the results of two experimental evaluations conducted in different environments: one to validate the effectiveness of the proposed system and the other to verify its practicality.