Deep learning and earth observation to support the sustainable development goals: Current approaches, open challenges, and future opportunities

C Persello, JD Wegner, R Hänsch… - … and Remote Sensing …, 2022 - ieeexplore.ieee.org
The synergistic combination of deep learning (DL) models and Earth observation (EO)
promises significant advances to support the Sustainable Development Goals (SDGs). New …

A survey on vision-based outdoor smoke detection techniques for environmental safety

S Chaturvedi, P Khanna, A Ojha - ISPRS Journal of Photogrammetry and …, 2022 - Elsevier
Early stage smoke detection using image and video analysis is an important area of
research due to its enormous applications in mitigating fire hazards and ensuring …

An improved forest fire detection method based on the detectron2 model and a deep learning approach

AB Abdusalomov, BMDS Islam, R Nasimov… - Sensors, 2023 - mdpi.com
With an increase in both global warming and the human population, forest fires have
become a major global concern. This can lead to climatic shifts and the greenhouse effect …

Forest fire detection and notification method based on AI and IoT approaches

K Avazov, AE Hyun, AA Sami S, A Khaitov… - future internet, 2023 - mdpi.com
There is a high risk of bushfire in spring and autumn, when the air is dry. Do not bring any
flammable substances, such as matches or cigarettes. Cooking or wood fires are permitted …

[HTML][HTML] A deep learning based object identification system for forest fire detection

F Guede-Fernández, L Martins, RV de Almeida… - Fire, 2021 - mdpi.com
Forest fires are still a large concern in several countries due to the social, environmental and
economic damages caused. This paper aims to show the design and validation of a …

Monitoring and cordoning wildfires with an autonomous swarm of unmanned aerial vehicles

F Saffre, H Hildmann, H Karvonen, T Lind - Drones, 2022 - mdpi.com
Unmanned aerial vehicles, or drones, are already an integral part of the equipment used by
firefighters to monitor wildfires. They are, however, still typically used only as remotely …

Robotic monitoring of habitats: The natural intelligence approach

F Angelini, P Angelini, C Angiolini, S Bagella… - IEEE …, 2023 - ieeexplore.ieee.org
In this paper, we first discuss the challenges related to habitat monitoring and review
possible robotic solutions. Then, we propose a framework to perform terrestrial habitat …

Detecting rumours with latency guarantees using massive streaming data

TT Nguyen, TT Huynh, H Yin, M Weidlich, TT Nguyen… - The VLDB Journal, 2023 - Springer
Today's social networks continuously generate massive streams of data, which provide a
valuable starting point for the detection of rumours as soon as they start to propagate …

Toward an adaptable deep-learning model for satellite-based wildfire monitoring with consideration of environmental conditions

Y Kang, T Sung, J Im - Remote Sensing of Environment, 2023 - Elsevier
As the majority of active fire detection algorithms have been developed for worldwide
applications using only satellite data without considering observing conditions and …

Taking Artificial Intelligence Into Space Through Objective Selection of Hyperspectral Earth Observation Applications: To bring the “brain” close to the “eyes” of satellite …

AM Wijata, MF Foulon, Y Bobichon… - … and Remote Sensing …, 2023 - ieeexplore.ieee.org
Recent advances in remote sensing hyperspectral imaging and artificial intelligence (AI)
bring exciting opportunities to various fields of science and industry that can directly benefit …