A Disaster Management Framework Using Internet of Things-Based Interconnected Devices

Sharma, Kaljot; Anand, Darpan; Sabharwal, Munish; Tiwari, Pradeep Kumar; Cheikhrouhou, Omar; Frikha, Tarek

doi:10.1155/2021/9916440

Cited by 51 publications

(22 citation statements)

References 71 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The image receives an arrow in every pixel by repeating this technique for every pixel in the image. These arrows are known as gradients, and they indicate the transition of light to dark throughout the whole image [11][12][13][14][15][16][17][18][19][20]. The upper right most section of the pie charts shows the flood duration in days.…”

Section: Resultsmentioning

confidence: 99%

Implementation of Flood Emergency Response System with Face Analytics

Mardaid¹,

Abidin²,

Asmai³

et al. 2023

IJACSA

View full text Add to dashboard Cite

Disaster management system is developed to monitor flood, tsunami and earthquake, which is effectively preparing for and responding to the disaster. In fact, Malaysia is building the emergency response system for managing the flood disaster since it is highly occurred. However, the current flood emergency response system has limitations, which, has no integration that data entered into spreadsheets and transferred to different storages, and, data analytics that assist in data collection and decision-making. Even though flood emergency response system have been improved, which introducing sirens and loudspeakers to reach flood victims but still difficult to access the basic facilities and receive flood responses. Therefore, this study implements a flood emergency response system with face analytics to assist data acquisition, which analyze flood victim's faces using CCTV infrastructure with HOG algorithm that incorporated with a dashboard. The dashboard categorizes the number of flood occurrence, maximum flood period (days), the number of displaced flood victims and loss assessment. Findings have shown that the dashboard helps the enforcement agencies to implement the real-time information about flood victims. Based on the number flood frequency occurrence in Malaysia from 2017 to 2021, the percentage produced was 27%, 19%, 12%, 19% and 23%. Moreover, the duration of floods has been decreased from 30% to 17% in 5 years that shows the flood emergency response helps the Malaysia government to improve the infrastructure. The significant of this study beneficial to the local enforcement unit and evacuation centers in identifying the flood victims.Keywords-Disaster management system; flood emergency response system; flood emergency response system with face analytics; flood emergency response system with face analytics using HOG algorithm; flood emergency response system dashboard I.

show abstract

Section: Resultsmentioning

confidence: 99%

Implementation of Flood Emergency Response System with Face Analytics

Mardaid¹,

Abidin²,

Asmai³

et al. 2023

IJACSA

View full text Add to dashboard Cite

show abstract

“…The number of devices connected via the Internet has been significantly increased in the past few years, and the IoT has inspired new ways to connect associate with various devices. To date, about 30 billion users connect to each other through the Internet and about 5 billion IoT devices have been deployed or connected (Sharma et al 2021 ). A complete IoT system may also include a controller, data transceiver, protocol stack, and data analysis system.…”

Section: New Technologies Applied In Idpmimentioning

confidence: 99%

Digital twin-driven intelligence disaster prevention and mitigation for infrastructure: advances, challenges, and opportunities

Dong

2022

Nat Hazards

View full text Add to dashboard Cite

Natural hazards, which have the potential to cause catastrophic damage and loss to infrastructure, have increased significantly in recent decades. Thus, the construction demand for disaster prevention and mitigation for infrastructure (DPMI) systems is increasing. Many studies have applied intelligence technologies to solve key aspects of infrastructure, such as design, construction, disaster prevention and mitigation, and rescue and recovery; however, systematic construction is still lacking. Digital twin (DT) is one of the most promising technologies for multi-stage management which has great potential to solve the above challenges. This paper initially puts forward a scientific concept, in which DT drives the construction of intelligent disaster prevention and mitigation for infrastructure (IDPMI) systematically. To begin with, a scientific review of DT and IDPMI is performed, where the development of DT is summarized and a DT-based life cycle of infrastructures is defined. In addition, the intelligence technologies used in disaster management are key reviewed and their relative merits are illustrated. Furthermore, the development and technical feasibility of DT-driven IDPMI are illustrated by reviewing the relevant practice of DT in infrastructure. In conclusion, a scientific framework of DT-IDPMI is programmed, which not only provides some guidance for the deep integration between DT and IDPMI but also identifies the challenges that inspire the professional community to advance these techniques to address them in future research.

show abstract

“…The integration of WSN and IoT with advancements in information and communication technology (ICT) becomes highly intellectual and connected infrastructures, where a massive quantity of data can be collected and investigated. The use of heterogeneous resources and advanced artificial intelligence (AI) techniques can be utilized to design next generation of disaster management systems [4,5]. Owing to distinct weather situations, forest fires have undergone rapid variations which result in challenging monitoring processes.…”

Section: Introductionmentioning

confidence: 99%

Internet of Things Enabled Energy Aware Metaheuristic Clustering for Real Time Disaster Management

Santhanaraj¹,

Rajendran²,

Romero³

et al. 2023

Computer Systems Science and Engineering

View full text Add to dashboard Cite

Wireless Sensor Networks (WSNs) are a major element of Internet of Things (IoT) networks which offer seamless sensing and wireless connectivity. Disaster management in smart cities can be considered as a safety critical application. Therefore, it becomes essential in ensuring network accessibility by improving the lifetime of IoT assisted WSN. Clustering and multihop routing are considered beneficial solutions to accomplish energy efficiency in IoT networks. This article designs an IoT enabled energy aware metaheuristic clustering with routing protocol for real time disaster management (EAMCR-RTDM). The proposed EAMCR-RTDM technique mainly intends to manage the energy utilization of nodes with the consideration of the features of the disaster region. To achieve this, EAMCR-RTDM technique primarily designs a yellow saddle goatfish based clustering (YSGF-C) technique to elect cluster heads (CHs) and organize clusters. In addition, enhanced cockroach swarm optimization (ECSO) based multihop routing (ECSO-MHR) approach was derived for optimal route selection. The YSGF-C and ECSO-MHR techniques compute fitness functions using different input variables for achieving improved energy efficiency and network lifetime. The design of YSGF-C and ECSO-MHR techniques for disaster management in IoT networks shows the novelty of the work. For examining the improved outcomes of the EAMCR-RTDM system, a wide range of simulations were performed and the extensive results are assessed in terms of different measures. The comparative outcomes highlighted the enhanced outcomes of the EAMCR-RTDM algorithm over the existing approaches.

show abstract

A Disaster Management Framework Using Internet of Things-Based Interconnected Devices

Cited by 51 publications

References 71 publications

Implementation of Flood Emergency Response System with Face Analytics

Implementation of Flood Emergency Response System with Face Analytics

Digital twin-driven intelligence disaster prevention and mitigation for infrastructure: advances, challenges, and opportunities

Internet of Things Enabled Energy Aware Metaheuristic Clustering for Real Time Disaster Management

Contact Info

Product

Resources

About