Real-time safety early warning system for cross passage construction in Yangtze Riverbed Metro Tunnel based on the internet of things

2013 ◽  
Vol 36 ◽  
pp. 25-37 ◽  
Author(s):  
L.Y. Ding ◽  
C. Zhou ◽  
Q.X. Deng ◽  
H.B. Luo ◽  
X.W. Ye ◽  
...  
Author(s):  
Mohamad Jamil ◽  
Hafid Saefudin ◽  
Sarby Marasabessy

Forests have an important role in the life of living things. Nowadays forest fires (Karhutla) become a serious problem that can disrupt the symbiosis and life chain of living things. This problem has become a concern for the community, government and the world. Data obtained until August 2019 recorded 328,724 hectares and burned forest land. To overcome this problem, the government has made various efforts in the form of appeals or legal sanctions on actions that threaten forest sustainability whether carried out individually or in groups. Many cases of forest fires are known when a fire has occurred and little can be detected early. Information on the occurrence of many fires was obtained by residents around the location of the fire. To get the help of the fire department, community participation is needed, to contact the fire department so that they can anticipate the fire disaster early. The aim of this research is to develop a forest fire early warning system using the nodemcu module and the Telegram BOT with the Internet of Things (IOT) concept. Based on the test results of the Forest Fire early warning system using the Nodemcu module and the Telegram BOT with the concept of the Internet of Things (IOT) it is very helpful to provide quick information to find out fires that occur in the forest, by using the Internet of Things method, the officer will be able to know the conditions in real time, because this technology is capable of monitoring hardware using internet communication tools such as Telegram so that distance and location are not affected as long as the sensor used detects changes that occur.Keywords: Internet Of Things, Nodemcu, Telegram, Thingspeak, Forest fires


2013 ◽  
Vol 846-847 ◽  
pp. 1711-1715 ◽  
Author(s):  
Wen Jie Ji ◽  
Xiao Qiong Li ◽  
Jing Yang Chen

Mountain torrent is one of major natural disasters for humans. With the development of the Internet of things, the instrumented terminals, through which the host PC could obtain the real-time water and rainfall information and could alert to a coming disaster, have been widely applied to mountain torrent warning system. In order to ensure the effectiveness of network alerting, the program in the terminals need to be updated for some specific situations, but large quantities of terminals are usually built in complex terrain and fragmented geographically, so that it is difficult and expensive to update or repair the programs. In this paper, a method of remote update, realized on the BAM-4300 hydrologic remote terminal to update the complex programs via GPRS modules, was highly reliable. Experiments show that this method is of safety and reliability, and cumbersome processes of onsite update and maintenance could be avoided.


2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Haoran Song ◽  
Hao Yu ◽  
Dianliang Xiao ◽  
Yuexiang Li

Real-time and effective early warning of highway engineering construction sites is the key to ensuring the safety of highway engineering construction. At present, highway engineering construction safety early warning is limited by the experience of relevant personnel at the site and the dynamic changes of the project site environment. Therefore, the creation of a more active, smarter, and more effective real-time early warning model for construction safety is a strong complement to current research and has important theoretical and practical implications. The Internet of Things is the third wave of the information industry after computers, the Internet, and mobile communication networks. It is of great significance to promote the development of science and technology, economic growth, and social progress. Aiming at the shortcomings of the inadequate safety management methods for highway engineering construction in China, the inefficient efficiency of safety production supervision and management, and the emphasis on single and sporty supervision methods, a real-time early warning model for highway engineering construction safety based on the Internet of Things technology was constructed. By quantifying, scoring, and statistics of the safety situation during the construction process, the model achieves the goals of real-time monitoring, early warning, and handling hidden safety hazards. It overcomes problems such as untimely and unscientific safety issues in the past and effectively improves China’s highway engineering construction. The experimental comparison between the real-time early warning model and the traditional early warning model in this paper shows that the accuracy of the early warning model proposed in this paper is improved by nearly 5%, and the false alarm rate is reduced by nearly 4%.


2021 ◽  
Vol 3 (1) ◽  
pp. 42-58
Author(s):  
Vito Hafizh Cahaya Putra ◽  
Mokhamad Hendayu ◽  
Purnomo Yustianto

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.


Author(s):  
Sonia Verma ◽  
Manoj Kumar Phadwas

Our goal is to develop an environment to monitor and controlling a corona virus of 2019 (COVID-19) with I2OT i. e. Intelligent Internet of Things. Analytics have changed the way disease outbreaks are tracked and managed, hence saving lives. Using technology smart sensor, facial recognition and location, existing surveillance cameras to identify, trace, and monitor people that may have contracted the coronavirus. The Internet of Things, a network of interconnected systems and advances in data analytics, artificial intelligence and ubiquitous connectivity can help by providing an early warning system to curb the spread of infectious diseases.


Sign in / Sign up

Export Citation Format

Share Document