A Conceptual Framework for the Design of an Urban Flood Early-Warning System Using a Context-Awareness Approach in Internet-of-Things Platform

2016 ◽  
pp. 1295-1305 ◽  
Author(s):  
Jeerana Noymanee ◽  
Wimol San-Um ◽  
Thanaruk Theeramunkong
Keyword(s):  
Internet Of Things ◽  
Conceptual Framework ◽  
Early Warning ◽  
Context Awareness ◽  
Early Warning System ◽  
Warning System ◽  
Urban Flood

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.

scholarly journals Early Warning System and Monitoring of River Water Quality Based on Internet of Things

2021 ◽  
Vol 3 (1) ◽  
pp. 42-58
Author(s):  
Vito Hafizh Cahaya Putra ◽  
Mokhamad Hendayu ◽  
Purnomo Yustianto
Keyword(s):  
Water Quality ◽  
Internet Of Things ◽  
River Water ◽  
Early Warning ◽  
Early Warning System ◽  
Warning System ◽  
River Water Quality ◽  
The Internet ◽  
Acceptance Test ◽  
Average Value

River conditions in Bandung City are currently in critical condition. This study aims to create an early warning system and monitoring of river water quality based on the Internet of Things in the hope that early warnings sent through the telegram application belonging to the Bandung City DLHK officer and the Twitter social media website, can inform the Bandung City DLHK officer that a river is in a polluted condition and the officer can immediately go to the location of river water to carry out mitigation, and give warnings to the community. The research method used using the waterfall method which consists of: needs analysis, system design, implementation, testing, and maintenance with sequential implementation. Data collection methods were carried out in several ways, namely: interviews, giving questionnaires, and literature studies used in this study sourced from books, journals, seminar presentations, and the internet as references in the research conducted. Based on the research that has been carried out, the following test results are obtained: black box testing is carried out in accordance with those contained in the test plan with the results of each test having valid results. The results obtained from the user acceptance test which are calculated using the Likert scale have an average value of 86.94% which fall into the category of strongly agree, and there are three guidelines which are a follow-up to the output of the early warning system that can be carried out either by the Environmental Service. and Cleanliness (DLHK) of Bandung City and the community.

An IoT-Based Earthquake Warning System for Smart Cities

2019 ◽  
pp. 208-227
Author(s):  
Suja Priyadharsini S. ◽  
Ramalakshmi S.
Keyword(s):  
Internet Of Things ◽  
Early Warning ◽  
Early Warning System ◽  
Smart Cities ◽  
Warning System ◽  
Earthquake Magnitude ◽  
Transfer Data ◽  
Earthquake Early Warning System ◽  
The Individual ◽  
Magnitude Determination

Earthquakes are the most common natural disasters that occur in India. An earthquake warning system minimizes damage and saves countless lives. A seismic wave analysis helps develop an early warning system. The bigger the earthquake, the stronger the shaking. Hence, magnitude determination is critical to developing an earthquake early warning system. The chapter deals with detecting earthquake magnitude by identifying the individual magnitude of earthquakes. An early warning system can be effectively implemented by the proposed method, along with high-end processors and the IoT (internet of things), which has the ability to collect and transfer data over networks with no manual intrusion. The proposed early earthquake warning (EEW) system can be used to support the development of smart cities so earthquake-prone zones are made less susceptible to disaster.

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