Unmanned Aerial Vehicles for Air Pollution Monitoring: A Survey

被引:34
作者
Motlagh, Naser Hossein [1 ]
Kortoci, Pranvera [1 ]
Su, Xiang [2 ]
Loven, Lauri [3 ]
Hoel, Hans Kristian [2 ]
Haugsvaer, Sindre Bjerkestrand [2 ]
Srivastava, Varun [2 ]
Gulbrandsen, Casper Fabian [2 ]
Nurmi, Petteri [1 ]
Tarkoma, Sasu [1 ]
机构
[1] Univ Helsinki, Dept Comp Sci, Helsinki 00014, Finland
[2] Norwegian Univ Sci & Technol, Dept Comp Sci, N-7034 Trondheim, Norway
[3] Univ Oulu, Ctr Ubiquitous Comp, Oulu 90570, Finland
基金
芬兰科学院;
关键词
Air quality sensing; Internet of Things (IoT); low-cost sensor; unmanned aerial vehicles (UAVs); AIRCRAFT SYSTEMS UASS; FIELD CALIBRATION; SOURCE LOCALIZATION; INSPIRED ALGORITHM; ENERGY-CONSUMPTION; UAV COMMUNICATION; SENSOR NETWORKS; TASK ASSIGNMENT; DRONE; DESIGN;
D O I
10.1109/JIOT.2023.3290508
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Unmanned aerial vehicles (UAVs) equipped with air quality sensors offer a powerful solution for increasing the spatial and temporal resolution of air quality data, searching and detecting emission sources, and monitoring emissions from fixed and mobile sources. Despite the numerous advantages of using UAVs, their use, however, presents several challenges that limit their broader adoption. For example, UAVs require efficient algorithms and components to minimize power consumption, the overall payload used on UAVs needs to be small to ensure optimal portability which poses limitations on the sensors that can be integrated with UAVs, and there is a need for specialized algorithms, e.g., for identifying and locating air pollution sources. Currently, most solutions for UAV-based air quality monitoring focus on specific challenges or demonstrating the potential of using UAVs, and there is a lack of comprehensive overview of the research field and its open challenges. In this article, we contribute a systematic review of UAV-based air quality monitoring, highlighting, and analyzing technical solutions and challenges, and identifying open challenges with the aim of providing a research roadmap for the path forward.
引用
收藏
页码:21687 / 21704
页数:18
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