Design of Forest Fire Monitoring, Early Warning and Fire Extinguishing System of Internet of Things Based on the Integration of UAV and Robot Land and Sky

2021 ◽  
Vol 11 (05) ◽  
pp. 1264-1267
Author(s):  
宏伟 马
Keyword(s):  
Internet Of Things ◽  
Forest Fire ◽  
Early Warning ◽  
Fire Monitoring ◽  
Fire Extinguishing ◽  
Fire Extinguishing System

Autonomic Indoor Fire Extinguishing System

2011 ◽  
Vol 480-481 ◽  
pp. 841-844
Author(s):  
Dong Xing Wang ◽  
Su Chen
Keyword(s):  
Early Warning ◽  
Early Stage ◽  
Automated Guided Vehicle ◽  
Fire Extinguishing ◽  
Fire Extinguishing System

The most commonly used indoor fire extinguishing systems are automatic sprinkling fire extinguishing systems. However, such systems have disadvantages of difficult to maintenance and low in reliability. The design of a composite indoor fire distinguishing system has been proposed, which consists of a fixed fire early warning subsystem and a moveable fire detecting and extinguishing subsystem. The moveable fire detecting and extinguishing subsystem is established on an automated guided vehicle. The system is fully autonomic, robust, and easy to maintenance. In addition, it can promptly and precisely detect fire in its early stage, and extinguish it in time. Experiments have demonstrated that the system is applicable.

scholarly journals SISTEM PERINGATAN DINI KEBAKARAN HUTAN MENGGUNAKAN MODUL NODEMCU DAN BOT TELEGRAM DENGAN KONSEP INTERNET OF THINGS (IOT)

2019 ◽  
Vol 3 (1) ◽  
Author(s):  
Mohamad Jamil ◽  
Hafid Saefudin ◽  
Sarby Marasabessy
Keyword(s):  
Internet Of Things ◽  
Forest Fire ◽  
Early Warning ◽  
Forest Fires ◽  
Early Warning System ◽  
Warning System ◽  
Fire Department ◽  
The Internet ◽  
Living Things ◽  
The Internet Of Things

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

Construction of a multi-source heterogeneous hybrid platform for big data

2021 ◽  
pp. 1-10
Author(s):  
Ying Wang ◽  
Yiding Liu ◽  
Minna Xia
Keyword(s):  
Big Data ◽  
Data Analysis ◽  
Forest Fire ◽  
Original Data ◽  
Big Data Analysis ◽  
Multiple Sources ◽  
Data Types ◽  
Fire Monitoring ◽  
Data Platform

Big data is featured by multiple sources and heterogeneity. Based on the big data platform of Hadoop and spark, a hybrid analysis on forest fire is built in this study. This platform combines the big data analysis and processing technology, and learns from the research results of different technical fields, such as forest fire monitoring. In this system, HDFS of Hadoop is used to store all kinds of data, spark module is used to provide various big data analysis methods, and visualization tools are used to realize the visualization of analysis results, such as Echarts, ArcGIS and unity3d. Finally, an experiment for forest fire point detection is designed so as to corroborate the feasibility and effectiveness, and provide some meaningful guidance for the follow-up research and the establishment of forest fire monitoring and visualized early warning big data platform. However, there are two shortcomings in this experiment: more data types should be selected. At the same time, if the original data can be converted to XML format, the compatibility is better. It is expected that the above problems can be solved in the follow-up research.

Infra-red line camera data-driven edge detector in UAV forest fire monitoring

2021 ◽  
Vol 111 ◽  
pp. 106574
Author(s):  
Francesco De Vivo ◽  
Manuela Battipede ◽  
Eric Johnson
Keyword(s):  
Forest Fire ◽  
Data Driven ◽  
Edge Detector ◽  
Fire Monitoring ◽  
Infra Red ◽  
Red Line
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