Semantic Sensor Network Ontology based Decision Support System for Forest Fire Management
Ritesh Chandra, Kumar Abhishek, Sonali Agarwal, Navjot Singh

TL;DR
This paper presents a decision support system utilizing Semantic Sensor Network ontologies and reasoning rules to monitor, visualize, and respond to forest fire risks based on climatic sensor data.
Contribution
It introduces a novel ontology-based framework for calculating fire weather indices and visualizing their changes over time for improved forest fire management.
Findings
Effective fire weather index calculation using SSN ontologies
Web-based visualization of fire risk over time
Decision support system with reasoning capabilities
Abstract
The forests are significant assets for every country. When it gets destroyed, it may negatively impact the environment, and forest fire is one of the primary causes. Fire weather indices are widely used to measure fire danger and are used to issue bushfire warnings. It can also be used to predict the demand for emergency management resources. Sensor networks have grown in popularity in data collection and processing capabilities for a variety of applications in industries such as medical, environmental monitoring, home automation etc. Semantic sensor networks can collect various climatic circumstances like wind speed, temperature, and relative humidity. However, estimating fire weather indices is challenging due to the various issues involved in processing the data streams generated by the sensors. Hence, the importance of forest fire detection has increased day by day. The underlying…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsFire Detection and Safety Systems
MethodsOntology
