Y. Liu, M. Zhao, S. Xia, E. Wu, X. Jiang
{"title":"摘要:基于无传感器无人机的室内三维气流梯度测绘系统","authors":"Y. Liu, M. Zhao, S. Xia, E. Wu, X. Jiang","doi":"10.1145/3498361.3538671","DOIUrl":null,"url":null,"abstract":"With the global spread of the COVID-19 pandemic, ventilation indoors is becoming increasingly important in preventing the spread of airborne viruses. However, while sensors exist to measure wind speed and airflow gradients, they must be manually held by a human or an autonomous vehicle, robot, or drone that moves around the space to build an airflow map of the environment. In this demonstration, we present DAE, a novel drone-based system that can automatically navigate and estimate air flow in a space without the need of additional sensors attached onto the drone. DAE directly utilizes the flight controller data that all drones use to self-stabilize in the air to estimate airflow. DAE estimates airflow gradients in a room based on how the flight controller adjusts the motors on the drone to compensate external perturbations and air currents, without the need for attaching additional wind or airflow sensors. © 2022 Owner/Author.","PeriodicalId":347635,"journal":{"name":"20th ACM International Conference on Mobile Systems, Applications and Services, MobiSys 2022","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Demo Abstract: A Sensorless Drone-based System for Mapping Indoor 3D Airflow Gradients\",\"authors\":\"Y. Liu, M. Zhao, S. Xia, E. Wu, X. Jiang\",\"doi\":\"10.1145/3498361.3538671\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the global spread of the COVID-19 pandemic, ventilation indoors is becoming increasingly important in preventing the spread of airborne viruses. However, while sensors exist to measure wind speed and airflow gradients, they must be manually held by a human or an autonomous vehicle, robot, or drone that moves around the space to build an airflow map of the environment. In this demonstration, we present DAE, a novel drone-based system that can automatically navigate and estimate air flow in a space without the need of additional sensors attached onto the drone. DAE directly utilizes the flight controller data that all drones use to self-stabilize in the air to estimate airflow. DAE estimates airflow gradients in a room based on how the flight controller adjusts the motors on the drone to compensate external perturbations and air currents, without the need for attaching additional wind or airflow sensors. © 2022 Owner/Author.\",\"PeriodicalId\":347635,\"journal\":{\"name\":\"20th ACM International Conference on Mobile Systems, Applications and Services, MobiSys 2022\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"20th ACM International Conference on Mobile Systems, Applications and Services, MobiSys 2022\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3498361.3538671\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"20th ACM International Conference on Mobile Systems, Applications and Services, MobiSys 2022","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3498361.3538671","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2