MM4Drone: A Multi-spectral Image and mmWave Radar Approach for Identifying Mosquito Breeding Grounds via Aerial Drones

Mosquitoes spread disases such as Dengue and Zika that affect a significant portion of the world population. One approach to hamper the spread of the disases is to identify the mosquitoes’ breeding places. Recent studies use drones to detect breeding sites, due to their low cost and flexibility. In...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Mahima, K. T. Y., Weerasekara, Malith, Zoysa, Kasun De, Keppitiyagama, Chamath, Flierl, Markus, Mottola, Luca, Voigt, Thiemo
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Mosquitoes spread disases such as Dengue and Zika that affect a significant portion of the world population. One approach to hamper the spread of the disases is to identify the mosquitoes’ breeding places. Recent studies use drones to detect breeding sites, due to their low cost and flexibility. In this paper, we investigate the applicability of drone-based multi-spectral imagery and mmWave radios to discover breeding habitats. Our approach is based on the detection of water bodies. We introduce our Faster R-CNN-MSWD, an extended version of the Faster R-CNN object detection network, which can be used to identify water retention areas in both urban and rural settings using multi-spectral images. We also show promising results for estimating extreme shallow water depth using drone-based multi-spectral images. Further, we present an approach to detect water with mmWave radios from drones. Finally, we emphasize the importance of fusing the data of the two sensors and outline future research directions.
ISSN:1867-8211
1867-822X
DOI:10.1007/978-3-031-34586-9_27