Weather data analytics for safe drone operations in low-altitude urban environments

• Main Authors: Lee, Lewis, Pang, Bizhao, Low, Kin Huat
• Other Authors: School of Mechanical and Aerospace Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2022
• Subjects: Engineering::Civil engineering::Transportation; Engineering::Computer science and engineering::Mathematics of computing; Unmanned Aerial Vehicles; Weather Data Analytics; Environmental Risk-Map; ANOVA
• Online Access: https://hdl.handle.net/10356/157183
• Institution: Nanyang Technological University

Drone operations in low-altitude urban airspace might be influenced by weather conditions such as wind and rainfall. Severe weather conditions may exceed the threshold of drone tolerability and cause crash accidents, posing risks to people and property. To investigate the influence of weather conditions on drone operation, this paper presents a data-driven method for analysis of weather data and to identify different levels of risk for safe drone operations. Obtained weather data is first collected across Singapore’s 63 weather stations, and trend analysis are conducted to test if there are any significant trends in the yearly weather data. The risk standards in low-altitude urban environments are then classified based on the risk cost model. Similar levels of risk are clustered depending on the geographical location. Preliminary results show that the present weather data can be used to model our simulations as past historical weather data have no significant deviations. The results also concluded that low to high rainfall usually occurs at low wind speeds while high wind speeds tend to have low rainfall. The weather data analysis results can be used to generate an environmental risk-map for safe airspace planning and UAV path optimization.