Multi-hazard disaster studies: Monitoring, detection, recovery, and management, based on emerging technologies and optimal techniques

• Published in: International journal of disaster risk reduction Vol. 47; p. 101642
• Main Authors: Khan, Amina, Gupta, Sumeet, Gupta, Sachin Kumar
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.08.2020
• Subjects: Artificial intelligence; Big data analytics; Detection; Earthquake; Forest fire; Fuzzy logic; IoT; Landslide; Management; MANET; Monitoring; Remote sensing technique; Satellite imagery; UAV; WSN; Remote sensing technique; Big data analytics; Management; UAV; IoT; Fuzzy logic; Satellite imagery; MANET; WSN; Earthquake; Landslide; Forest fire; Detection; Artificial intelligence; Monitoring
• ISSN: 2212-4209; 2212-4209
• DOI: 10.1016/j.ijdrr.2020.101642

Every year man-made and natural disasters impact the lives of millions of people. The frequency of occurrence of such disasters is steadily increasing since the last 50 years, and this has resulted in considerable loss of life, destruction of infrastructure, and social and economic disruption. A focussed and comprehensive solution is needed encompassing all aspects, including early detection of disaster scenarios, prevention, recovery, and management to minimize the losses. This survey paper presents a critical analysis of the existing methods and technologies that are relevant to a disaster scenario, such as WSN, remote sensing technique, artificial intelligence, IoT, UAV, and satellite imagery, to encounter the issues associated with disaster monitoring, detection, and management. In case of emergency conditions arising out of a typical disaster scenario, there is a strong likelihood that the communication networks will be partially disrupted; thus the alternate networks can play a vital role in disaster detection and management. It focuses on the role of the alternate networks and the associated technologies in maintaining connectivity in various disaster scenarios. It presents a comprehensive study on multiple disasters such as landslide, forest fire, and an earthquake based on the latest technologies to monitor, detect, and manage the various disasters. It focuses on several parameters that are necessary for disaster detection and monitoring and offers appropriate solutions. It also touches upon big data analytics for disaster management. Several techniques are explored, along with their merits and demerits. Open challenges are highlighted, and possible future directions are given.