Wildfire Monitoring Research Articles

Efficient Encryption Technique for H.264/AVC Videos Based on CABAC and Logistic Map

Nowadays, the demands of real-time video communication are increased rapidly. Search and rescue(SAR) applications like earthquake rescue, avalanche victims, wildfire monitoring in addition to highway surveillance are considered examples of real-time applications. In which, communication time is considered the most important metric to be optimized to ensure support for victims’ lives. Thus finding a simple and time efficient encryption technique for securing the transmitted data become mandatory. In this paper, we present an efficient encryption technique which has low computation complexity, low processing time and highly chaotic encrypted videos. The proposed technique is based on CABAC where the bin-string of Intra-Prediction Mode is encrypted with chaotic signals and the sign of MVD is toggled randomly. For residue coefficients the sign of the AC coefficients are flipped randomly and the first value of DC coefficients is encrypted by XORing the bin-string with random stream. All random streams are generated with chaotic systems using Logistic map. The experimental results shows that the proposed technique is highly effective for real-time application and robust against different <br /> types of attacks.

Determining Resilience Gains From Anomaly Detection for Event Integrity in Wireless Sensor Networks

Measurements collected in a wireless sensor network (WSN) can be maliciously compromised through several attacks, but anomaly detection algorithms may provide resilience by detecting inconsistencies in the data. Anomaly detection can identify severe threats to WSN applications, provided that there is a sufficient amount of genuine information. This article presents a novel method to calculate an assurance measure for the network by estimating the maximum number of malicious measurements that can be tolerated. In previous work, the resilience of anomaly detection to malicious measurements has been tested only against arbitrary attacks, which are not necessarily sophisticated. The novel method presented here is based on an optimization algorithm, which maximizes the attack’s chance of staying undetected while causing damage to the application, thus seeking the worst-case scenario for the anomaly detection algorithm. The algorithm is tested on a wildfire monitoring WSN to estimate the benefits of anomaly detection on the system’s resilience. The algorithm also returns the measurements that the attacker needs to synthesize, which are studied to highlight the weak spots of anomaly detection. Finally, this article presents a novel methodology that takes in input the degree of resilience required and automatically designs the deployment that satisfies such a requirement.

Quantifying wildfire growth rates using smoke plume observations derived from weather radar

Fast-moving wildfires can result in substantial losses of infrastructure, property and life. During such events, real-time intelligence is critical for managing firefighting activities and public safety. The ability of fixed-site weather radars to detect the plumes from fires has long been recognised; however, quantitative methods to link properties of radar observed plumes to fire behaviour are lacking. We investigated the potential for weather radars to provide real time estimates of the growth of large fires in south-eastern Australia. Specifically, we examined whether the rate of change in fire area could be approximated using the change in volume represented by radar returns. We evaluated a series of linear mixed-effects models predicting fire-area growth using radar data representing a range of dBZ thresholds and search volumes. Models were compared using an information–theoretic approach. Radar return volume was found to be a robust predictor of fire-area change. The best model had a minimum threshold of 10 dBZ and a search radius of 60 km (R2 = 0.64). Fire area and radar relationships did not vary significantly between radar stations, suggesting broad applicability beyond the dataset. Further development of the use of weather radars for wildfire monitoring could yield substantial benefits because of their high frequency of scan and broad coverage over many populated areas.

Real-time wildfire detection and tracking in Australia using geostationary satellite: Himawari-8

ABSTRACTReal-time information about the spatial extents of wildfires can assist both emergency responders and the general public to mitigate the impact of the wildfires. However, in a large spatial and temporal scale, timely and accurate information about the areas affected by ongoing wildfires is often in scarce supply. This paper investigates the feasibility of generating such real-time information in Australia using the recently launched geostationary Himawari-8 satellite. The Himawari-8 satellite offers extremely high-temporal-resolution (10 minutes) multispectral imagery, which is suitable for real-time wildfire monitoring in a large spatial and temporal scale. The potential of real-time wildfire monitoring using Himawari-8 is evaluated by a case-study of the recent 2015 Esperance, Western Australia wildfire. The results demonstrate that the detection is robust to smoke and moderate cloud obscuration and sensitive enough for early detection of wildfires. Further, fine-grained temporal changes in the rate and direction of fire spread can be monitored in real-time, which enables the potential for automated detection of abnormal fire behaviour.

A Study on Development of Reliability Assessment Method for Industrial Drone

In the past, drones have been developed for military use. Recently, however, the use of drones in industrial and civilian markets has been spreading rapidly because of their potential for various applications. The main application areas of industrial drones are aerial photography, logistics transportation, lifesaving, policing, wildfire monitoring and spraying agricultural pesticide. The reliability assessment and performance test methods of drones are not systematically established against such a rapidly growing market situation until these days. Therefore, in this study,we developed reliability assessment methods and test equipment that can evaluate reliability of drone by performance test, environmental test, safety test and life test method, which can be used to ensure safety of individual users and reliability of industrial drones. In the developmentof the reliability assessment method for industrial drones, we tried to verify drones’ reliability and to show the acceptable minimum limit required by manufacturer’s general specification. Furthermore, it is expected that we possibly obtain the degradation measure of the flight performance and the durability through the comprehensive performance and life test via applying the usage history and practical load in the laboratory. The developed methods were set up reflecting international standards, user requirements and field operating conditions. Since the field failure data of industrial drones has been reported rare in the manufacturing companies and research institutes until now. We think that it is necessary to obtain more than thousand's hours of the actual usage history and the failure data in order to correct or supplement the developed reliability assessment method in the future.

An integrated approach for tactical monitoring and data-driven spread forecasting of wildfires

In recent times there have been increasing efforts to integrate technology into wildfire management, especially in the fields of tactical monitoring and simulation. On the one hand, thermal infrared imaging (TIR) systems have been installed aboard surveillance aircraft including unmanned systems (UAS). On the other, there exists a variety of models and simulators able to forecast the fire spread. However, both fields currently present significant limitations. While relevant information is still extracted manually from aerial thermal imagery and is most times merely qualitative, simulators’ accuracy on fire spread prediction has proved insufficient. To solve these issues, this article presents a twofold methodology to couple meaningful automated wildfire monitoring with accurate fire spread forecasting. The main goals are to, firstly, automatically process aerial TIR imagery so that valuable information can be produced in real time during the event and, secondly, use this information to adjust a Rothermel-based simulator in order to improve its accuracy on-line. The fire perimeter location is tracked automatically through an unsupervised edge detector. Afterwards, an assimilation module uses the remotely sensed data to optimise the simulator's fuel and wind parameters, which are assumed to remain constant for a certain period of time. Subsequently, the optimum parameters’ values are used to issue a fire evolution forecast. All outputs are projected onto the corresponding Digital Terrain Model (DTM) and integrated into a Geographic Information System (GIS) for visualization. The global system was validated using two large-scale experiments. If these algorithms can be applied to a sufficiently rich and varied set of experimental data and further developed to cope with more complex scenarios, they could eventually be incorporated into a fire management decision support system.

Wildfire Monitoring and Detection System Using Wireless Sensor Network: A Case Study of Tanzania

This paper proposes a wildfire monitoring and detection system based on wireless sensor network. This system detects fire by monitoring surrounding temperature, humidity and smoke. Once fire is detected, a warning message containing probable location of that fire is immediately sent to the responsible authority over cellular network. In order for the system to be more effective, communities living near forests or national parks can send warning messages through the same system to the responsible authority using their mobile handsets once they witness wildfire or illegal activities. For the system to be fully functional, the only requirement is the availability of cellular network coverage in forests or national parks to enable short message services to take place. The system prototype is developed using Arduino microcontroller, several sensors to detect temperature, relative humidity and smoke as well as wireless network connection modules. At the control center Telerivet messaging platform is used to design the messaging service. The experimental results justify the capability of the proposed system in detecting wildfire in real time.

Cogent Confabulation based Expert System for Segmentation and Classification of Natural Landscape Images

Ever since there has been an increase in the number of automatic wildfire monitoring and surveillance systems in the last few years, natural landscape images have been of great importa ...

Application of the remote-sensing communication model to a time-sensitive wildfire remote-sensing system

ABSTRACTRemote sensing for hazard response requires a priori identification of sensor, transmission, processing, and distribution methods to permit the extraction of relevant information in timescales sufficient to allow managers to make a given time-sensitive decision. This study applies and demonstrates the utility of the Remote Sensing Communication Model (RSCM) to improve a tactical wildfire remote-sensing system to better meet the time-sensitive information requirements of emergency response managers in San Diego County, USA. A thermal infrared airborne remote-sensing system designed and operated by the United States Forest Service Pacific Southwest Research Station for active wildfire monitoring is documented and updated based on the RSCM. Analysis of the thermal infrared remote-sensing system in the context of the RSCM identified three configuration changes that can improve the effectiveness of the information produced when employed by wildfire incident commanders for suppression prioritization: (1) limit spectral sampling collection to a single waveband; (2) complete image processing steps on-board the aircraft; and (3) provide information on wildfire locations to incident commanders in the form of a static map.

A Sybil attack detection scheme for a forest wildfire monitoring application

Wireless Sensor Networks (WSNs) have experienced phenomenal growth over the past decade. They are typically deployed in human-inaccessible terrains to monitor and collect time-critical and delay-sensitive events. There have been several studies on the use of WSN in different applications. All such studies have mainly focused on Quality of Service (QoS) parameters such as delay, loss, jitter, etc. of the sensed data. Security provisioning is also an important and challenging task lacking in all previous studies. In this paper, we propose a Sybil attack detection scheme for a cluster-based hierarchical network mainly deployed to monitor forest wildfire. We propose a two-tier detection scheme. Initially, Sybil nodes and their forged identities are detected by high-energy nodes. However, if one or more identities of a Sybil node sneak through the detection process, they are ultimately detected by the two base stations. After Sybil attack detection, an optimal percentage of cluster heads are elected and each one is informed using nomination packets. Each nomination packet contains the identity of an elected cluster head and an end user’s specific query for data collection within a cluster. These queries are user-centric, on-demand and adaptive to an end user requirement. The undetected identities of Sybil nodes reside in one or more clusters. Their goal is to transmit high false-negative alerts to an end user for diverting attention to those geographical regions which are less vulnerable to a wildfire. Our proposed approach has better network lifetime due to efficient sleep–awake scheduling, higher detection rate and low false-negative rate.

Real-Time Wildfire Monitoring and Alert System Using GSM Technology

Environmental related issues and parameters are of utmost importance to man, and is essential to his existence and influence and thus he alwaysseeks for an improved system that would be able to capture and monitor the changes in environmental parameters irrespective of time and location so as to provide for measures that will forestall abnormalities and cater for emergencies.This paper presents research work on a system that is capable of providing real time remote wildfire monitoring and SMS alert. Thework aimed at the design and implementation of a low cost but efficient and flexible wildfire monitoring and alert system using GSM technology. It was designed in such a way that the Monitoring of wildfire would be achieved with the use of temperature and smoke sensorscoupled with a control unit and transmitter module all of which are battery powered. Fire and smoke are sensed and measured by the sensors which send the signals to the control unit for proper processing and determination of the smoke rate.This is displayed on an LCD screen, then an alert is sent to the mobile phone of the environmental personnel via SMS while simultaneously triggering an alarm in control room. Thus this system presents a continuous, real time, remote, safe and accurate monitoring of wildfires and smoke rate hence ensuring the conservation and preservation of wildlife, natural habitats and the ecosystem, and at the same time, helping tocurb high impact human, industrial and environmental damage

Real-time autonomous wildfire monitoring and georeferencing using rapidly deployable mobile units

Each year and only in Spain, more than 16,000 wildfires account for the devastation of over 200,000 ha of forest, causing the loss of human life and incurring costs of more than 620 million euros in the last 10 years [1]. This disaster also has a direct consequence in the reduction of the forest biomass, causing severe damage to the Earth’s forest ecosystem.

Real-time autonomous wildfire monitoring and georeferencing using rapidly deployable mobile units

This article deals with the design and prototyping of a rapidly deployable mobile unit (RDMU), which uses a thermographic camera to autonomously detect, track, and georeference a wildfire that falls within its detection range. The following sections present an analysis of the current situation, followed by the technological developments carried out to address the identified problems. Details about the prototype integration and functional tests are also provided.

Localization in terrestrial and underwater sensor‐based m2m communication networks: architecture,classification and challenges

SummaryLocalizing machine‐type communication (MTC) devices or sensors is becoming important because of the increasing popularity of machine‐to‐machine (M2M) communication networks for location‐based applications. These include such as health monitoring, rescue operations, vehicle tracking, and wildfire monitoring. Moreover, efficient localization approaches for sensor‐based MTC devices reduce the localization error and energy consumption of MTC devices. Because sensors are used as an integral part of M2M communication networks and have achieved popularity in underwater applications, research is being conducted on sensor localization in both underwater and terrestrial M2M networks. Major challenges in designing underwater localization techniques are the lack of good radio signal propagation in underwater, sensor mobility management, and ensuring network coverage in 3D underwater M2M networks. Similarly, predicting the mobility pattern of MTC devices, trading‐off energy consumption and location accuracy pose great design challenges for terrestrial localization techniques. This article presents a comprehensive survey on the current state‐of‐the‐art research on both terrestrial and underwater localization approaches for sensor‐based MTC devices. It also classifies localization approaches based on several factors, identifies their limitations with potential solutions, and compares them. Copyright © 2015 John Wiley & Sons, Ltd.

A data acquisition protocol for a reactive wireless sensor network monitoring application.

Limiting energy consumption is one of the primary aims for most real-world deployments of wireless sensor networks. Unfortunately, attempts to optimize energy efficiency are often in conflict with the demand for network reactiveness to transmit urgent messages. In this article, we propose SWIFTNET: a reactive data acquisition scheme. It is built on the synergies arising from a combination of the data reduction methods and energy-efficient data compression schemes. Particularly, it combines compressed sensing, data prediction and adaptive sampling strategies. We show how this approach dramatically reduces the amount of unnecessary data transmission in the deployment for environmental monitoring and surveillance networks. SWIFTNET targets any monitoring applications that require high reactiveness with aggressive data collection and transmission. To test the performance of this method, we present a real-world testbed for a wildfire monitoring as a use-case. The results from our in-house deployment testbed of 15 nodes have proven to be favorable. On average, over 50% communication reduction when compared with a default adaptive prediction method is achieved without any loss in accuracy. In addition, SWIFTNET is able to guarantee reactiveness by adjusting the sampling interval from 5 min up to 15 s in our application domain.

Real-time stream processing for active fire monitoring on Landsat 8 direct reception data

Abstract. Some remote sensing applications are relatively time insensitive, for others, near-real-time processing (results 30-180 minutes after data reception) offer a viable solution. There are, however, a few applications, such as active wildfire monitoring or ship and airplane detection, where real-time processing and image interpretation offers a distinct advantage. The objective of real-time processing is to provide notifications before the complete satellite pass has been received. This paper presents an automated system for real-time, stream–based processing of data acquired from direct broadcast push-broom sensors for applications that require a high degree of timeliness. Based on this system, a processing chain for active fire monitoring using Landsat 8 live data streams was implemented and evaluated. The real-time processing system, called the FarEarth Observer, is connected to a ground station’s demodulator and uses its live data stream as input. Processing is done on variable size image segments assembled from detector lines of the push broom sensor as they are streamed from the satellite, enabling detection of active fires and sending of notifications within seconds of the satellite passing over the affected area, long before the actual acquisition completes. This approach requires performance optimized techniques for radiometric and geometric correction of the sensor data. Throughput of the processing system is kept well above the 400Mbit/s downlink speed of Landsat 8. A latency of below 10 seconds from sensor line acquisition to anomaly detection and notification is achieved. Analyses of geometric and radiometric accuracy and comparisons in latency to traditional near-real-time systems are also presented.

Design and Field Test of a WSN Platform Prototype for Long-Term Environmental Monitoring.

Long-term wildfire monitoring using distributed in situ temperature sensors is an accurate, yet demanding environmental monitoring application, which requires long-life, low-maintenance, low-cost sensors and a simple, fast, error-proof deployment procedure. We present in this paper the most important design considerations and optimizations of all elements of a low-cost WSN platform prototype for long-term, low-maintenance pervasive wildfire monitoring, its preparation for a nearly three-month field test, the analysis of the causes of failure during the test and the lessons learned for platform improvement. The main components of the total cost of the platform (nodes, deployment and maintenance) are carefully analyzed and optimized for this application. The gateways are designed to operate with resources that are generally used for sensor nodes, while the requirements and cost of the sensor nodes are significantly lower. We define and test in simulation and in the field experiment a simple, but effective communication protocol for this application. It helps to lower the cost of the nodes and field deployment procedure, while extending the theoretical lifetime of the sensor nodes to over 16 years on a single 1 Ah lithium battery.

Towards an Integrated Cyberinfrastructure for Scalable Data-driven Monitoring, Dynamic Prediction and Resilience of Wildfires

Abstract Wildfires are critical for ecosystems in many geographical regions. However, our current urbanized existence in these environments is inducing the ecological balance to evolve into a different dynamic leading to the biggest fires in history. Wildfire wind speeds and directions change in an instant, and first responders can only be effective if they take action as quickly as the conditions change. What is lacking in disaster management today is a system integration of real-time sensor networks, satellite imagery, near-real time data management tools, wildfire simulation tools, and connectivity to emergency command centers before, during and after a wildfire. As a first time example of such an integrated system, the WIFIRE project is building an end-to-end cyberinfrastructure for real-time and data-driven simulation, prediction and visualization of wildfire behavior. This paper summarizes the approach and early results of the WIFIRE project to integrate networked observations, e.g., heterogeneous satellite data and real-time remote sensor data with computational techniques in signal processing, visualization, modeling and data assimilation to provide a scalable, technological, and educational solution to monitor weather patterns to predict a wildfire's Rate of Spread.

Wildfire Management in the Tain II Forest Reserve of Ghana: An Evaluation of Community Participation

Until 1983 uncontrolled wildfires were uncommon, especially in the forest zones of Ghana. Unfortunately early efforts at curbing wildfires did not place emphasis on stakeholder management. This weakness has constrained wildfire management as a result of weak coordination among stakeholders in the management of wildfire. But an essential element for the success of wildfire management is the active involvement of all stakeholders. This study was conducted to assess the role of stakeholders in wildfire management in the Tain II Forest Reserve in the Brong Ahafo Region of Ghana. The study relied on both qualitative and quantitative approaches using household questionnaires as its primary data collection instrument. The study reveals that stakeholders occasionally participated in wildfire management planning, implementation and monitoring activities at the community level. This assertion was confirmed by the index of participation indicating that stakeholders were occasionally involved in wildfire management regarding planning (0.59), implementation (0.60) and monitoring (0.56). Also, empirical results show that the absence of incentives and lack of insurance serve as disincentives for effective functioning of wildfire squad volunteers around the Tain II forest reserve. The study concludes that the success, or otherwise, of wildfire management interventions, to a large extent, depends on the degree of involvement of stakeholders and the support given to them.

위성자료를 이용한 한반도 산불정보 하이브리드 앱의 구현 및 활용

최근 항시적 광역 모니터링이 가능한 위성원격탐사 기술에 의해 산불감시의 효율성이 증대될 것으로 기대되고 있는 가운데, 미국의 Terra, Aqua, GOES (Geostationary Operational Environmental Satellite), 유럽연합의 Meteosat, 그리고 우리나라의천리안위성 및 후속위성도 산불정보의 실시간 제공을 목표로 하고 있다. 본 연구에서는 이러한 위성기반 산불정보를 대민서비스하기 위한 방법의 일환으로 스마트폰 앱을 구현하여, 북한지역을 포함한 한반도 전역의 위성자료로부터 추출한 산불발생여부, 산불탐지 신뢰도, 산불의 방사강도 등의 정보를 DBMS (Database Management System)에서 관리하고, 안드로이드와 iOS 스마트폰을통해 제공하는 서비스의 원형을 개발하였다. 공통적 핵심기능은 HTML5 (HyperText Markup Language 5) 웹페이지로 구성함으로써 상이한 OS (Operating System)의 네이티브 앱과 결합하는 하이브리드 방식을 통해 소스코드의 재사용성과 시스템 확장성을 추구하였으며, 일자별 산불조회, 최근 산불조회, 주변 산불조회 등의 기능을 포함하도록 하였다. 현재는 위성기반 산불탐지 자료가 실시간 제공되지 않아 산불발생의 이력정보를 서비스하도록 구성하였지만, 2010년대 후반 우리나라 기상위성의 산불탐지 자료가 실시간으로 제공될 것이므로, 정부 3.0의 정보공개 흐름과 함께 국민 모두에게 필요한 실시간 산불정보 조회가 가능해질 것으로 예상된다. 본 연구는 위성기반의 실시간 산불정보 앱 개발을 위한 출발점으로서 의의를 가지며, 향후 산불정보 앱은 SNS (SocialNetworking Service) 기반의 빅데이터 마이닝 기술과 연동하는 통합 솔루션으로 구성되어야 그 활용성이 보다 더 제고될 것이다.