scholarly journals Early-warning analysis of crowd stampede in metro station commercial area based on internet of things

2018 ◽  
Vol 78 (21) ◽  
pp. 30141-30157
Author(s):  
Kefan Xie ◽  
Yanlan Mei ◽  
Ping Gui ◽  
Yang Liu
Keyword(s):  
Internet Of Things ◽  
Early Warning ◽  
Metro Station ◽  
Commercial Area

scholarly journals Sistem Peringatan Dini Banjir Secara Real-Time Berbasis Web Menggunakan Arduino dan Ethernet

2017 ◽  
Vol 1 (1) ◽  
pp. 1 ◽  
Author(s):  
Dedi Satria ◽  
Syaifuddin Yana ◽  
Rizal Munadi ◽  
Saumi Syahreza
Keyword(s):  
Information System ◽  
Internet Of Things ◽  
Real Time ◽  
Early Warning ◽  
Major Influence ◽  
Google Maps ◽  
Flood Monitoring ◽  
Arduino Uno ◽  
Internet Of Things Technology ◽  
Monitoring Information

a b s t r a c tThe development of flood early warning technology has grown rapidly. The technology has led to an increase in technology in terms of communication and information. Internet of Things technology (IoTs) has provided a major influence on the development of early warning information system. In this article a protipe-based flood monitoring information system of Google Maps have been designed by integrating Ultrasonic sensors as the height of the detector, the Arduino Uno as a processor, U-Blox GPS modules Neo 6 m GSM module and as the sender of data is the height of the water and the coordinates to the station of the system informais flood. The design of the prototype produces information flood elevations along with location based Google Maps interface.Keywords:Flood, Arduino, Internet of Things Technology (IoTs), Ethernet a b s t r a kPengembangan teknologi peringatan dini banjir telah tumbuh dengan cepat. Teknologi tersebut telah mengarah kepada peningkatan di segi teknologi komunikasi dan informasi. Teknologi Internet of Things (IoTs) telah memberikan pengaruh besar terhadap perkembangan sistem informasi peringatan dini. Didalam artikel ini sebuah protipe sistem informasi monitoring banjir berbasis Google Maps telah dirancang dengan mengintegrasikan sensor ultrasonik sebagai pendeteksi ketinggian, Arduino Uno sebagai pemroses, modul GPS U-Blox Neo 6m dan modul GSM sebagai pengirim data ketinggian air dan koordinat ke stasion sistem informais banjir. Perancangan prototipe menghasilkan informasi ketinggian banjir beserta lokasinya berbasis antarmuka Google Maps.Kata Kunci: Banjir, Arduino, Internet of Things Technology (IoTs), Ethernet

scholarly journals Development of a support vector machine learning and smart phone Internet of Things-based architecture for real-time sleep apnea diagnosis

2020 ◽  
Vol 20 (S14) ◽  
Author(s):  
Bin Ma ◽  
Zhaolong Wu ◽  
Shengyu Li ◽  
Ryan Benton ◽  
Dongqi Li ◽  
...  
Keyword(s):  
Support Vector Machine ◽  
Sleep Apnea ◽  
Internet Of Things ◽  
Real Time ◽  
Early Warning ◽  
Smart Phone ◽  
Physiological Parameters ◽  
Classification Model ◽  
Support Vector ◽  
Obstructive Sleep

Abstract Background The breathing disorder obstructive sleep apnea syndrome (OSAS) only occurs while asleep. While polysomnography (PSG) represents the premiere standard for diagnosing OSAS, it is quite costly, complicated to use, and carries a significant delay between testing and diagnosis. Methods This work describes a novel architecture and algorithm designed to efficiently diagnose OSAS via the use of smart phones. In our algorithm, features are extracted from the data, specifically blood oxygen saturation as represented by SpO2. These features are used by a support vector machine (SVM) based strategy to create a classification model. The resultant SVM classification model can then be employed to diagnose OSAS. To allow remote diagnosis, we have combined a simple monitoring system with our algorithm. The system allows physiological data to be obtained from a smart phone, the data to be uploaded to the cloud for processing, and finally population of a diagnostic report sent back to the smart phone in real-time. Results Our initial evaluation of this algorithm utilizing actual patient data finds its sensitivity, accuracy, and specificity to be 87.6%, 90.2%, and 94.1%, respectively. Discussion Our architecture can monitor human physiological readings in real time and give early warning of abnormal physiological parameters. Moreover, after our evaluation, we find 5G technology offers higher bandwidth with lower delays ensuring more effective monitoring. In addition, we evaluate our algorithm utilizing real-world data; the proposed approach has high accuracy, sensitivity, and specific, demonstrating that our approach is very promising. Conclusions Experimental results on the apnea data in University College Dublin (UCD) Database have proven the efficiency and effectiveness of our methodology. This work is a pilot project and still under development. There is no clinical validation and no support. In addition, the Internet of Things (IoT) architecture enables real-time monitoring of human physiological parameters, combined with diagnostic algorithms to provide early warning of abnormal data.

Mountain Torrent Disaster Monitoring and Early-Warning System Based on Internet of Things

2014 ◽  
Vol 484-485 ◽  
pp. 577-580
Author(s):  
Chen Ping Zeng
Keyword(s):  
Internet Of Things ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
Information Support ◽  
Flood Prevention ◽  
Automation And Control ◽  
Disaster Monitoring ◽  
Water Conservancy ◽  
Monitoring And Early Warning

As a wisdom water conservancy, mountain torrent disaster monitoring and early-warning system is an especially information part of flood prevention and drought resisting information support, and plays a very important role in the flood prevention and drought resisting in the water conservancy industry. The integration of mountain torrent disaster monitoring and early-warning system in water conservancy with the internet of things and the establishment of intelligent things networking system based on automation and control provide decision-making supports for flood prevention and mountain torrent disaster early-warning, aiming at safeguard the life and property securities of people. Therefore, by taking Zhaojue County of Liangshan Yi autonomous prefecture (an area with frequent mountain torrent disaster in Sichuan province) as an example, the implementation plan of mountain torrent disaster monitoring and early-warning system is reviewed in this paper.

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