2026-04-07 スタンフォード大学
A figure of drone imagery of possible tires, analyzed by AI, developed for publication in Remote Sensing Applications: Society and Environment | Mehedy Hassan
＜関連情報＞
- https://news.stanford.edu/stories/2026/04/mosquito-borne-disease-breeding-sites-drones-ai
- https://www.sciencedirect.com/science/article/abs/pii/S2352938526001448
- https://link.springer.com/article/10.1186/s44263-026-00250-5
ネッタイシマカの繁殖地検出の強化：インドネシアの都市部における無人航空機画像からのタイヤ識別のための深層学習アプローチ Enhancing Aedes aegypti breeding site detection: A deep learning approach to tire identification in unmanned aerial vehicle imagery from urban Indonesia
Mohammad Mehedy Hassan, Andrew J. Chamberlin, Morgan S. Tarpenning, Whitney C. Weber, Kavita Dave Coombe, Giulio A. De Leo, Muhammad Junaid, Andang Suryana Soma, Ansariadi, Joelle I. Rosser
Remote Sensing Applications: Society and Environment Available online: 7 April 2026
DOI:https://doi.org/10.1016/j.rsase.2026.102011
Highlights
- Discarded tires are high-risk breeding sites for Aedes aegypti mosquitoes.
- UAV and CNN models enable automated tire detection in urban environments.
- UAV imagery is a promising tool to support improved vector control strategies
Abstract
Discarded tires remain a significant public health problem in tropical urban environments, serving as high-risk breeding sites for Aedes aegypti, the mosquitoes which transmit dengue, chikungunya, and Zika viruses. Identifying these habitats using ground-based surveillance methods can be resource-intensive and often misses fenced-off areas and tires on roofs. This study presents a novel approach using unmanned aerial vehicle (UAV) imagery combined with deep learning to automatically detect discarded tires across the Tallo sub-district of Makassar, Indonesia, an area with historically high dengue incidence. We trained and compared U-Net++ and DeepLabV3++ convolutional neural network architectures for tire segmentation. We evaluated the models’ ability to identify the locations, shapes, and spatial distribution of discarded tires in the study area. Both models demonstrated high prediction accuracy, with F1 scores of 0.87 and 0.82, respectively, with modestly superior performance by the U-Net++. The strong detection performance was largely attributable to the distinctive circular morphology and spectral characteristics of tires in aerial imagery, though this same characteristic occasionally led to false positives when encountering tire-mimicking objects such as outdoor air conditioning condenser units, water tank lids, and similar circular items. Identifying, locating, and eliminating potential larval breeding sites is a primary strategy for the control of Aedes aegypti -transmitted viruses. Accurate, rapid detection of high-risk Aedes aegypti breeding sites from UAV imaging is a promising new tool to improve vector control.
地球の健康研究における無人航空機の新たな可能性 New frontiers for unmanned aerial vehicles in planetary health research
Juliet T. Bramante,Morgan S. Tarpenning,Katherine E. Woo,Andrew J. Chamberlin,Kavita D. Coombe & Joelle I. Rosser
BMC Global and Public Health Published:13 March 2026
DOI:https://doi.org/10.1186/s44263-026-00250-5
Abstract
Unmanned aerial vehicles (UAVs) are a revolutionary new surveillance and transport technology with important implications for healthcare systems, particularly in the era of climate change. Rapid shifts in environmental systems are reshaping global climates. These changes have led to increasingly common extreme weather events that threaten population health. Mitigating the impacts of climate change on human health depends on our ability to predict, detect, and rapidly respond to changing ecosystem dynamics. The use of UAVs to tackle these new environmental health challenges is gaining momentum across multiple disciplines. This review identified four main areas where UAVs are being used or piloted to address climate change and health-related concerns: (1) Disease vector management, (2) environmental risk factors management, (3) environmental resource management, and (4) medical deliveries. Over the coming decades, UAVs are likely to play an increasing role in our efforts to keep pace with monitoring and mitigating the accelerating impacts of climate change on human health.
