Fuzzy-based forest fire prevention and detection by wireless sensor networks
Authors: J Toledo-Castro, I Santos-González, P Caballero-Gil, C Hernández-Goya, N Rodríguez-Pérez, R Aguasca-Colomo
AI-generated Key Points
- Forest fires can have devastating effects on ecosystems and human lives
- Proposal suggests using IoT and wireless sensor networks for forest fire prevention
- Real-time monitoring system gathers and analyzes information on meteorological conditions, polluting gases, and oxygen levels
- Unusual measurements of environmental variables can help detect potential risks before fires escalate
- Forest fire risk controller based on fuzzy logic implemented through web service and mobile application
- Security mechanisms proposed to ensure integrity and confidentiality of measured environmental information transmission
- Technology has potential to play important role in mitigating impact of natural disasters by providing real-time data analysis for improved forest fire prevention.
Abstract: Forest fires may cause considerable damages both in ecosystems and lives. This proposal describes the application of Internet of Things and wireless sensor networks jointly with multi-hop routing through a real time and dynamic monitoring system for forest fire prevention. It is based on gathering and analyzing information related to meteorological conditions, concentrations of polluting gases and oxygen level around particular interesting forest areas. Unusual measurements of these environmental variables may help to prevent wildfire incidents and make their detection more efficient. A forest fire risk controller based on fuzzy logic has been implemented in order to activate environmental risk alerts through a Web service and a mobile application. For this purpose, security mechanisms have been proposed for ensuring integrity and confidentiality in the transmission of measured environmental information. Lamport's signature and a block cipher algorithm are used to achieve this objective.
Tools for this paper
Ask questions about this paper to our AI assistant
You can also chat with multiple papers at once here.
⚠The license of the paper does not allow us to build upon its content and the AI assistant only knows about the paper metadata rather than the full article.
The previous summary was created more than a year ago and can be re-run (if necessary) by clicking on the Run button below.
⚠The license of this specific paper does not allow us to build upon its content and the summarizing tools will be run using the paper metadata rather than the full article. However, it still does a good job, and you can also try our tools on papers with more open licenses.
Similar papers summarized with our AI tools
Navigate through even more similar papers through a
tree representationLook for similar papers (in beta version)
We compare the title and abstract with papers indexed in our database. For arXiv papers, we search within the same category; for DOI and other sources, we search across sources and subjects. You can rerun the search as our database grows.
Disclaimer: The AI-based summarization tool and virtual assistant provided on this website may not always provide accurate and complete summaries or responses. We encourage you to carefully review and evaluate the generated content to ensure its quality and relevance to your needs.