Context-aware Mobile Platform for Intellectual Disaster Alerts System

Chang, Hyokyung; Kang, Yongho; Ahn, Hyosik; Jang, Changbok; Choi, Euiin

doi:10.1016/j.egypro.2012.01.211

Cited by 5 publications

(3 citation statements)

References 7 publications

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“…An inappropriate threshold of high density used for individual behavior estimation by [ 6 ], and a lack of feedback to victims resulting to a high false alarm in an emergency led to an unreliable prediction of crowd conditions, such as for example crowd abnormality behavior. Chang et al [ 35 ] introduced a context-aware mobile platform for an intellectual disaster alerts system (IDAS); it focused on how environmental changes can result in accidents and disasters. According to the authors, a quick and accurate alert delivered to victims is essential in a disaster situation.…”

Section: Current Approaches In Crowd Monitoring Systemmentioning

confidence: 99%

“…Its research finds application in many domains with only few in disaster management. The extant literature highlights three methods used in context-aware framework: (i) scenario-based with a hypothetical example using a develop application, (ii) comparative analysis using a side-by-side comparison of components [ 41 ], and metric evaluation with accuracy, precision, recall, and f-score with an experiment on related activities [ 35 ]. Table 3 presents related works and highlights gaps in previous research.…”

Section: Current Approaches In Crowd Monitoring Systemmentioning

confidence: 99%

See 1 more Smart Citation

Enhanced Approach Using Reduced SBTFD Features and Modified Individual Behavior Estimation for Crowd Condition Prediction

Sadiq

Selamat

Ibrahim

et al. 2019

Entropy

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Sensor technology provides the real-time monitoring of data in several scenarios that contribute to the improved security of life and property. Crowd condition monitoring is an area that has benefited from this. The basic context-aware framework (BCF) uses activity recognition based on emerging intelligent technology and is among the best that has been proposed for this purpose. However, accuracy is low, and the false negative rate (FNR) remains high. Thus, the need for an enhanced framework that offers reduced FNR and higher accuracy becomes necessary. This article reports our work on the development of an enhanced context-aware framework (EHCAF) using smartphone participatory sensing for crowd monitoring, dimensionality reduction of statistical-based time-frequency domain (SBTFD) features, and enhanced individual behavior estimation (IBEenhcaf). The experimental results achieved 99.1% accuracy and an FNR of 2.8%, showing a clear improvement over the 92.0% accuracy, and an FNR of 31.3% of the BCF.

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Section: Current Approaches In Crowd Monitoring Systemmentioning

confidence: 99%

Section: Current Approaches In Crowd Monitoring Systemmentioning

confidence: 99%

Enhanced Approach Using Reduced SBTFD Features and Modified Individual Behavior Estimation for Crowd Condition Prediction

Sadiq

Selamat

Ibrahim

et al. 2019

Entropy

View full text Add to dashboard Cite

show abstract

“…Damages and ripple effects can happen due to disasters without notification anytime and anywhere [1]. Disaster break presents many unique logistics challenges, such as damage to transportation infrastructure, limited communication, and coordination of multiple agents [2].…”

Section: Introductionmentioning

confidence: 99%

Using Rule Base System in Mobile Platform to Build Alert System for Evacuation and Guidance

Abulkhair¹,

Ibrahim²

2016

ijacsa

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Abstract-The last few years have witnessed the widespread use of mobile technology. Billions of citizens around the world own smartphones, which they use for both personal and business applications. Thus, technologies will minimize the risk of losing people's lives. Mobile platform is one of the most popular platform technologies utilized on a wide scale and accessible to a high number of people. There has been a huge increase in natural and manmade disasters in the last few years. Such disasters can happen anytime and anywhere causing major damage to people and property. The environment affluence and the failure of people to go to other safe places are the results of catastrophic events recently in Jeddah city. Flood causes the sinking and destruction of homes and private properties. Thus, this paper describes a system that can help in determining the affected properties, evacuating them, and providing a proper guidance to the registered users in the system. This system notifies mobile phone users by sending guidance messages and sound alerts, in a real-time when disasters (fires, floods) hit. Warnings and tips are received on the mobile user to teach him/her how to react before, during, and after the disaster. Provide a mobile application using GPS to determine the user location and guide the user for the best way with the aid of rule-based system that built through the interview with the Experts domains. Moreover, the user will receive Google map updates for any added information. This system consists of two subsystems: the first helps students in our university to evacuate during a catastrophe and the second aids all people in the city. Due to all these features, the system can access the required information at the needed time.

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Ontology for cloud manufacturing based Product Lifecycle Management

Talhi

Fortineau²,

Huet

et al. 2017

J Intell Manuf

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The manufacturing environment has become increasingly competitive in the past few years, and product development is getting even more complex. The agility of an information system is a way to manage this complexity, and cloud technologies enable the sharing of tools and information in a new way. In particular, in the field of Product Lifecycle Management, a review of the literature demonstrates that there are technical issues that limit the efficient collaboration between the various stakeholders along the product lifecycle. Cloud manufacturing is a new concept that enables the virtualization of manufacturing resources and capabilities and provides them as a service. Therefore it offers new prospects for usage and collaboration in the extended enterprise, and along the product lifecycle. For instance, it helps to manage variations in production demand, by providing a large set of potential manufacturing resources on demand. However, to share the resources within the cloud manufacturing environment, a unification model of the domain information is required, to which any provider and/or user of cloud manufacturing must conform in order to dialog with the other CM stakeholders. This study provides an ontological model of the cloud manufacturing domain in order to support information exchange between the cloud manufacturing resources. The concepts of the proposed ontology are based on a literature review of models of cloud and models of manufacturing. The detailed ontology is then validated using the OntoClean methodology and within its implementation in an industrial scenario.

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Context-aware Mobile Platform for Intellectual Disaster Alerts System

Cited by 5 publications

References 7 publications

Enhanced Approach Using Reduced SBTFD Features and Modified Individual Behavior Estimation for Crowd Condition Prediction

Enhanced Approach Using Reduced SBTFD Features and Modified Individual Behavior Estimation for Crowd Condition Prediction

Using Rule Base System in Mobile Platform to Build Alert System for Evacuation and Guidance

Ontology for cloud manufacturing based Product Lifecycle Management

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