Disaster management using Internet of Things

Saha, Himadri Nath; Auddy, Supratim; Pal, Subrata; Kumar, Shubham; Pandey, Sujata; Singh, Rakhee; Singh, Amrendra K.; Banerjee, Swarnadeep; Ghosh, Debmalya; Saha, Sanhita

doi:10.1109/iemecon.2017.8079566

Cited by 46 publications

(10 citation statements)

References 6 publications

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“…It has enabled the deployment of a large number of applications in various fields. Saha et al [61] presented the use of sensors on trees for predicting fire outbreaks in forests. The sensors measure features, such as temperature, CO levels, greenhouse gases, and moisture.…”

Section: Applications Of Machine Learning Models In Predisaster Manag...mentioning

confidence: 99%

Disaster and Pandemic Management Using Machine Learning: A Survey

Chamola

Hassija

Gupta

et al. 2021

IEEE Internet Things J.

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This article provides a literature review of state-of-the-art machine learning (ML) algorithms for disaster and pandemic management. Most nations are concerned about disasters and pandemics, which, in general, are highly unlikely events. To date, various technologies, such as IoT, object sensing, UAV, 5G, and cellular networks, smartphone-based system, and satellite-based systems have been used for disaster and pandemic management. ML algorithms can handle multidimensional, large volumes of data that occur naturally in environments related to disaster and pandemic management and are particularly well suited for important related tasks, such as recognition and classification. ML algorithms are useful for predicting disasters and assisting in disaster management tasks, such as determining crowd evacuation routes, analyzing social media posts, and handling the post-disaster situation. ML algorithms also find great application in pandemic management scenarios, such as predicting pandemics, monitoring pandemic spread, disease diagnosis, etc. This article first presents a tutorial on ML algorithms. It then presents a detailed review of several ML algorithms and how we can combine these algorithms with other technologies to address disaster and pandemic management. It also discusses various challenges, open issues and, directions for future research.

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Section: Applications Of Machine Learning Models In Predisaster Manag...mentioning

confidence: 99%

Disaster and Pandemic Management Using Machine Learning: A Survey

Chamola

Hassija

Gupta

et al. 2021

IEEE Internet Things J.

View full text Add to dashboard Cite

show abstract

“…It is important to supply data that envisions Augmented reality based solutions that classifies a hazardous environment and provides a safe evacuation route at the site of fire. This portrays the infrastructural plan in both physical and virtual realm of buildings [9].…”

Section: Intelligent Servicementioning

confidence: 99%

June 2021

2021

JTCSST

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The disasters can be either natural or man-made. Control and management of disaster of any kind is possible in effective and robust way by the implementation of IoT in the system. The objective of implementing IoT into the disaster management system is the quick and effective recovery from the disaster. The various methods that can be deployed after the disaster is outlined through utilization of IoT. This paper gives an insight on the various methods that can be effectively used after the disaster using IoT. The existing techniques are very well monitored and has the ability to react to the situation as per needs, this paper significantly provides the contribution in analyzing these techniques for appropriate disaster management development block.

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“…The LED on the sensor starts flashing with every heartbeat and this is recorded by the Arduino. It will function according to the principle of light modulation by blood flow through the nerves of the finger at every single pulse [9] [10]. Another major parameter is the body movement of the patient which is observed using ADXL345 which is a 3-axis, low power, thin and small MEMS acceleration sensor which has a high resolution measurement (13 bit) upto +/-16g.…”

Section: A Data Compilationmentioning

confidence: 99%

Remote Healthcare Monitoring System with Home Automation.

Sawant¹

2019

IJRASET

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In this paper, Internet of Things (IoT) based healthcare monitoring system is studied. Several number of sensors are used to extract data of various health parameters of a patient, which is then reserved into the cloud. The data stored in cloud can be further displayed through website. The performance of a healthcare monitoring system is investigated where a short message service (SMS) notification helps a patient to remember the timing of medication and create an optimum surrounding as per the patient's condition. Under any emergency condition, the system also generates list of nearby doctors using their geographical coordinates, which is given by GPS module. The closest doctor is then located by comparing the distance of each doctor from the patient using a distance algorithm.

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Disaster management using Internet of Things

Cited by 46 publications

References 6 publications

Disaster and Pandemic Management Using Machine Learning: A Survey

Disaster and Pandemic Management Using Machine Learning: A Survey

June 2021

Remote Healthcare Monitoring System with Home Automation.

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