Computer Vision and IoT-Based Sensors in Flood Monitoring and Mapping: A Systematic Review - Archive ouverte HAL Access content directly
Journal Articles (Review Article) Sensors Year : 2019

Computer Vision and IoT-Based Sensors in Flood Monitoring and Mapping: A Systematic Review

Abstract

Floods are amongst the most common and devastating of all natural hazards. The alarming number of flood-related deaths and financial losses suffered annually across the world call for improved response to flood risks. Interestingly, the last decade has presented great opportunities with a series of scholarly activities exploring how camera images and wireless sensor data from Internet-of-Things (IoT) networks can improve flood management. This paper presents a systematic review of the literature regarding IoT-based sensors and computer vision applications in flood monitoring and mapping. The paper contributes by highlighting the main computer vision techniques and IoT sensor approaches utilised in the literature for real-time flood monitoring, flood modelling, mapping and early warning systems including the estimation of water level. The paper further contributes by providing recommendations for future research. In particular, the study recommends ways in which computer vision and IoT sensor techniques can be harnessed to better monitor and manage coastal lagoons—an aspect that is under-explored in the literature
Fichier principal
Vignette du fichier
sensors-19-05012.pdf (962.67 Ko) Télécharger le fichier
Origin : Publication funded by an institution

Dates and versions

hal-02871089 , version 1 (02-04-2024)

Identifiers

Cite

Bilal Arshad, Robert Ogie, Johan Barthelemy, Biswajeet Pradhan, Nicolas Verstaevel, et al.. Computer Vision and IoT-Based Sensors in Flood Monitoring and Mapping: A Systematic Review. Sensors, 2019, 19 (22), pp.5012. ⟨10.3390/s19225012⟩. ⟨hal-02871089⟩
30 View
0 Download

Altmetric

Share

Gmail Facebook X LinkedIn More