A Wildfire Prediction Based on Fuzzy Inference System for Wireless Sensor Networks

The study of forest fires has been traditionally considered as an important application due to the inherent danger that this entails. This phenomenon takes place in hostile regions of difficult access and large areas. Introduction of new technologies such as Wireless Sensor Networks (WSNs) has allowed us to monitor such areas. In this paper, an intelligent system for fire prediction based on wireless sensor networks is presented. This system obtains the probability of fire and fire behavior in a particular area. This information allows firefighters to obtain escape paths and determine strategies to fight the fire. A firefighter can access this information with a portable device on every node of the network. The system has been evaluated by simulation analysis and its implementation is being done in a real environment.Junta de Andalucía P07-TIC-02476Junta de Andalucía TIC-570

Design of a WSN Platform for Long-Term Environmental Monitoring for IoT Applications

The Internet of Things (IoT) provides a virtual view, via the Internet Protocol, to a huge variety of real life objects, ranging from a car, to a teacup, to a building, to trees in a forest. Its appeal is the ubiquitous generalized access to the status and location of any "thing" we may be interested in. Wireless sensor networks (WSN) are well suited for long-term environmental data acquisition for IoT representation. This paper presents the functional design and implementation of a complete WSN platform that can be used for a range of long-term environmental monitoring IoT applications. The application requirements for low cost, high number of sensors, fast deployment, long lifetime, low maintenance, and high quality of service are considered in the specification and design of the platform and of all its components. Low-effort platform reuse is also considered starting from the specifications and at all design levels for a wide array of related monitoring application

Estimating Fire Weather Indices via Semantic Reasoning over Wireless Sensor Network Data Streams

Wildfires are frequent, devastating events in Australia that regularly cause significant loss of life and widespread property damage. Fire weather indices are a widely-adopted method for measuring fire danger and they play a significant role in issuing bushfire warnings and in anticipating demand for bushfire management resources. Existing systems that calculate fire weather indices are limited due to low spatial and temporal resolution. Localized wireless sensor networks, on the other hand, gather continuous sensor data measuring variables such as air temperature, relative humidity, rainfall and wind speed at high resolutions. However, using wireless sensor networks to estimate fire weather indices is a challenge due to data quality issues, lack of standard data formats and lack of agreement on thresholds and methods for calculating fire weather indices. Within the scope of this paper, we propose a standardized approach to calculating Fire Weather Indices (a.k.a. fire danger ratings) and overcome a number of the challenges by applying Semantic Web Technologies to the processing of data streams from a wireless sensor network deployed in the Springbrook region of South East Queensland. This paper describes the underlying ontologies, the semantic reasoning and the Semantic Fire Weather Index (SFWI) system that we have developed to enable domain experts to specify and adapt rules for calculating Fire Weather Indices. We also describe the Web-based mapping interface that we have developed, that enables users to improve their understanding of how fire weather indices vary over time within a particular region.Finally, we discuss our evaluation results that indicate that the proposed system outperforms state-of-the-art techniques in terms of accuracy, precision and query performance.Comment: 20pages, 12 figure

Unmanned Aerial Systems for Wildland and Forest Fires

Wildfires represent an important natural risk causing economic losses, human death and important environmental damage. In recent years, we witness an increase in fire intensity and frequency. Research has been conducted towards the development of dedicated solutions for wildland and forest fire assistance and fighting. Systems were proposed for the remote detection and tracking of fires. These systems have shown improvements in the area of efficient data collection and fire characterization within small scale environments. However, wildfires cover large areas making some of the proposed ground-based systems unsuitable for optimal coverage. To tackle this limitation, Unmanned Aerial Systems (UAS) were proposed. UAS have proven to be useful due to their maneuverability, allowing for the implementation of remote sensing, allocation strategies and task planning. They can provide a low-cost alternative for the prevention, detection and real-time support of firefighting. In this paper we review previous work related to the use of UAS in wildfires. Onboard sensor instruments, fire perception algorithms and coordination strategies are considered. In addition, we present some of the recent frameworks proposing the use of both aerial vehicles and Unmanned Ground Vehicles (UV) for a more efficient wildland firefighting strategy at a larger scale.Comment: A recent published version of this paper is available at: https://doi.org/10.3390/drones501001

An algorithm of the wildfire classification by its acoustic emission spectrum using Wireless Sensor Networks

Crown fires are extremely dangerous as the speed of their distribution is dozen times higher compared to surface fires. Therefore, it is important to classify the fire type as early as possible. A method for forest fires classification exploits their computed acoustic emission spectrum compared with a set of samples of the typical fire acoustic emission spectrum stored in the database. This method implies acquisition acoustic data using Wireless Sensors Networks (WSNs) and their analysis in a central processing and a control center. The paper deals with an algorithm which can be directly implemented on a sensor network node that will allow reducing considerably the network traffic and increasing its efficiency. It is hereby suggested to use the sum of the squares ratio, with regard to amplitudes of low and high frequencies of the wildfire acoustic emission spectrum, as the indicator of a forest fire type. It is shown that the value of the crown fires indicator is several times higher than that of the surface ones. This allows classifying the fire types (crown, surface) in a short time interval and transmitting a fire type indicator code alongside with an alarm signal through the network

An algorithm of the wildfire classification by its acoustic emission spectrum using Wireless Sensor Networks

Crown fires are extremely dangerous as the speed of their distribution is dozen times higher compared to surface fires. Therefore, it is important to classify the fire type as early as possible. A method for forest fires classification exploits their computed acoustic emission spectrum compared with a set of samples of the typical fire acoustic emission spectrum stored in the database. This method implies acquisition acoustic data using Wireless Sensors Networks (WSNs) and their analysis in a central processing and a control center. The paper deals with an algorithm which can be directly implemented on a sensor network node that will allow reducing considerably the network traffic and increasing its efficiency. It is hereby suggested to use the sum of the squares ratio, with regard to amplitudes of low and high frequencies of the wildfire acoustic emission spectrum, as the indicator of a forest fire type. It is shown that the value of the crown fires indicator is several times higher than that of the surface ones. This allows classifying the fire types (crown, surface) in a short time interval and transmitting a fire type indicator code alongside with an alarm signal through the network

Wireless Environmental Weather Monitor

The goal of this senior design/honors project is to create a device that monitors environmental conditions in order to detect a wildfire. This device should notify a user of the status of the environment. The device should also last for 6 months without any human interaction. My role on the team is to design the power supply system that maximizes efficiency and uses renewable energy

Wireless Sensor Networks for Fire Detection and Control

Due to current technological progress, the manufacturing of tiny and low price sensors became technically and economically feasible. Sensors can measure physical surroundings related to the environment and convert them into an electric signal. A huge quantity of these disposable sensors is networked to detect and monitor fire. This paper provides an analysis of utilisation of wireless sensor networks for fire detection and control

Forest Fire Monitoring

Thousands of hectares around the globe destroyed by forest fires every year causing tragic loss of houses, properties, lives, fauna and flora. Forest fires are a great menace to ecologically healthy grown forests and protection of the environment. This problem has been the research interest for years, and there are a number of solutions available to resolve this problem. In this chapter, a summary is given for all the technologies that have been used for forest fire detection with explanation of what parameters these systems looking for to understand the fire behaviour