scholarly journals Navigation and Piloting System of Unmanned Aerial Vehicle for Forest Fire Monitoring

2020 ◽  
pp. 194-203
Author(s):  
O.V. Skudneva ◽  
◽  
S.V. Koptev ◽  
S.V. Ivantsov ◽  
◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Biological Diversity ◽  
Control Point ◽  
Effective Control ◽  
Ground Control ◽  
Control Panel ◽  
Forest Protection ◽  
Fire Monitoring ◽  
Starting Point

Forest fires are a common natural disaster all over the world. A great number of fires occur annually in the forest ecosystems of the European North of Russia for natural reasons and as a result of anthropogenic impacts. One of the urgent problems of forestry is the organization of effective control of forest fires. Herewith, it is important to quickly detect the source of fire, as well as to monitor the development of the fire, and to coordinate the actions of the staff of the ground forest protection services. Unmanned aerial vehicles (UAV) of different classes are increasingly used for these purposes. For forestry experience and, especially for forest fire monitoring, the most practical are helicopter-type UAV, which do not require special training of staff. Such devices can operate in the mode of “fire tower” and in the mode of monitoring the edge of the fire with an option to reset information pennants at certain points. The use of UAV is an effective means of monitoring the fire situation in addition to existing methods and technologies, and especially in cases of impossibility of using highresolution satellite images for operative tasks. For the effective operation of UAV in the area of active forest fires and, thus, strong smoke, navigation and piloting systems are necessary to perform safe flights outside the action of the ground control panel located at the starting point. The aim of this work is to develop a navigation and piloting system for UAV, which can be used in the area of limitation of ground control point. The use of such systems will allow monitoring of the fire situation in real time, which is especially important in the organization of protection and suppression of forest fires in large areas of nature reserves, where the priority is to preserve the biological diversity of natural ecosystems and unique landscapes. This article may be of interest to forestry specialists, developers of UAV and equipment, fire protection and the Ministry of Emergency Situations staff, as well as to engineering students to gain experience with UAV.

scholarly journals An Environmentally Aware Scheme of Wireless Sensor Networks for Forest Fire Monitoring and Detection

2018 ◽  
Vol 10 (10) ◽  
pp. 102 ◽  
Author(s):  
Yi-Han Xu ◽  
Qiu-Ya Sun ◽  
Yu-Tong Xiao
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Forest Fire ◽  
Forest Fires ◽  
Network Architecture ◽  
Resource Constraints ◽  
Wireless Sensor ◽  
Surveillance Systems ◽  
Fire Monitoring

Forest fires are a fatal threat to environmental degradation. Wireless sensor networks (WSNs) are regarded as a promising candidate for forest fire monitoring and detection since they enable real-time monitoring and early detection of fire threats in an efficient way. However, compared to conventional surveillance systems, WSNs operate under a set of unique resource constraints, including limitations with respect to transmission range, energy supply and computational capability. Considering that long transmission distance is inevitable in harsh geographical features such as woodland and shrubland, energy-efficient designs of WSNs are crucial for effective forest fire monitoring and detection systems. In this paper, we propose a novel framework that harnesses the benefits of WSNs for forest fire monitoring and detection. The framework employs random deployment, clustered hierarchy network architecture and environmentally aware protocols. The goal is to accurately detect a fire threat as early as possible while maintaining a reasonable energy consumption level. ns-2-based simulation validates that the proposed framework outperforms the conventional schemes in terms of detection delay and energy consumption.

scholarly journals Energy-Efficient Forest Fire Prediction Model based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol

2018 ◽  
Author(s):  
Jin-Gu Kang ◽  
Dong-Woo Lim ◽  
Jin-Woo Jung
Keyword(s):  
Prediction Model ◽  
Forest Fire ◽  
Duty Cycle ◽  
Forest Fires ◽  
Energy Efficient ◽  
Mac Protocol ◽  
Two Stage ◽  
Fire Monitoring ◽  
Environmental Status ◽  
Mountain Environment

In this paper, we propose an adaptive duty-cycled hybrid X-MAC (ADX-MAC) protocol for energy-efficient forest fire prediction. The X-MAC protocol acquires the additional environmental status collected by each forest fire monitoring sensor for a certain period. And, based on these values, the length of sleep interval of duty-cycle is changed to efficiently calculate the risk of occurrence of forest fire according to the mountain environment. The performance of the proposed ADX-MAC protocol was verified through experiments the proposed ADX-MAC protocol improves throughput by 19% and was more energy-efficient by 24% compared to X-MAC protocol. As the probability of forest fires increases, the length of the duty cycle is shortened, confirming that the forest fires are detected at a faster cycle.

scholarly journals Das Konzept «Waldbrand 2020» des Kantons Tessin

2019 ◽  
Vol 170 (5) ◽  
pp. 242-250
Author(s):  
Aron Ghiringhelli ◽  
Gianni Boris Pezzatti ◽  
Marco Conedera
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Forest Restoration ◽  
Fire Regime ◽  
Forest Service ◽  
Management Approach ◽  
Fire Control ◽  
Burnt Area ◽  
Forest Protection ◽  
Forest Fire Management

The “forest fire 2020” program of Canton Ticino The Canton of Ticino has a long-lasting experience in facing forest fires. As a result, a tradition in forest fire documentation and analysis exists and the forest fire management approach is continuously reviewed and improved with the aim to preserve the forest protection functions and to keep the mountain areas safe for the inhabitants. The fire regime has been reduced in Ticino since the seventies of last century thanks to improvement of the firefighting organization and fire control techniques (e.g. systematic use of helicopters for the aerial fire control) and the possibility of declaring a total fire ban in the open. However the demand in terms of protection of human lives and goods of the modern society is raising and as consequence of the climate change fire risk may increase in the future. For this reason two years ago the forest service of Canton Ticino developed the “forest fire 2020” program, in collaboration with the cantonal fire brigades association and the federal research Institute WSL. The program consists of four interdependent activity modules, which are 1) prevention, 2) organizational and technical measures, 3) firefighting and control, 4) burnt area restoration. The forest service is responsible for the fire-danger rating, the fire-ban release, the mentoring of local authorities in forest management questions and for planning pre-suppression facilities (e.g. water points for helicopters). It is also responsible for defining the mission rules for aerial firefighting, for collecting the data for the statistics, and for planning the post-fire forest restoration measures. The fire brigades are in charge of the firefighting tasks, by first intervening with the urban fire brigades and in case of need requiring the support of specialized forest-fire brigades. During the firefighting actions the forest service takes a consulting role. The first two years of implementation confirmed the suitability of the “forest fire 2020” program. Potential improvements have been however detected and are under implementation, such as the completion of the pre-suppression infrastructures, a better coordination between aerial and terrestrial firefighting and the strengthening of the specialized forest-fire brigades.

scholarly journals PENGENDALIAN KEBAKARAN HUTAN DI KPH MADIUN PERUM PERHUTANI UNIT II JAWA TIMUR Forest Fire Management in KPH Madiun Perum Perhutani Unit II East Java

2018 ◽  
Vol 8 (3) ◽  
pp. 183-190
Author(s):  
Bambang Hero Saharjo ◽  
Elga Tiara Putra
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Fire Management ◽  
Qualitative Description ◽  
Local People ◽  
Trigger Factors ◽  
Community Based ◽  
Fire Monitoring ◽  
Forest Fire Management ◽  
In Fire

Forest fires bring substantial losses in many aspects, especially for forest resources. Therefore, forest fire management should take into account at each of Indonesian forest area. KPH Madiun has suffered from a large forest fire in the recent 5 years, thus research to analyze the trigger factors and an effort to manage forest fire should be gone. This research used data triangular methods for data collecting and qualitative description analyse to analyze the data. Results of this research clearly shows that forest fire in KPH Madiun was mainly came from local people activities such as, burning the forest to clear the land (43%) and due to social conflict (15%). The forest fire prepetion emphasized on social approach in community based forest management (CBFM) by planting medicinal plant and establishing the forest Danger Index (FDI) board. The local people participated in fire extinction (49%), while the other not participate yet. There was no fire truck and fire monitoring tower found in the study area. Finding and arresting the suspect behind forest fire is the most difficult thing to do in post-fire management.Key words: forest fire, local people, fire management

scholarly journals Energy-Efficient Forest Fire Prediction Model Based on Two-Stage Adaptive Duty-Cycled Hybrid X-MAC Protocol

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2960 ◽  
Author(s):  
Jin-Gu Kang ◽  
Dong-Woo Lim ◽  
Jin-Woo Jung
Keyword(s):  
Prediction Model ◽  
Forest Fire ◽  
Duty Cycle ◽  
Forest Fires ◽  
Energy Efficient ◽  
Mac Protocol ◽  
Fire Occurrence ◽  
Fire Monitoring ◽  
Environmental Status ◽  
Environment Performance

This paper proposes an adaptive duty-cycled hybrid X-MAC (ADX-MAC) protocol for energy-efficient forest fire prediction. The Asynchronous sensor network protocol, X-MAC protocol, acquires additional environmental status details from each forest fire monitoring sensor for a given period, and then changes the duty-cycle sleep interval to efficiently calculate forest fire occurrence risk according to the environment. Performance was verified experimentally, and the proposed ADX-MAC protocol improved throughput by 19% and was 24% more energy efficient compared to the X-MAC protocol. The duty-cycle was shortened as forest fire probability increased, ensuring forest fires were detected at faster cycle rate.

A survey on technologies for automatic forest fire monitoring, detection, and fighting using unmanned aerial vehicles and remote sensing techniques

2015 ◽  
Vol 45 (7) ◽  
pp. 783-792 ◽  
Author(s):  
Chi Yuan ◽  
Youmin Zhang ◽  
Zhixiang Liu
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Forest Fire ◽  
Forest Fires ◽  
Cooperative Control ◽  
Fire Detection ◽  
Fire Monitoring ◽  
Diagnosis And Prognosis ◽  
Aerial Vehicles ◽  
Remote Sensing Techniques ◽  
Operational Range

Because of their rapid maneuverability, extended operational range, and improved personnel safety, unmanned aerial vehicles (UAVs) with vision-based systems have great potential for monitoring, detecting, and fighting forest fires. Over the last decade, UAV-based forest fire fighting technology has shown increasing promise. This paper presents a systematic overview of current progress in this field. First, a brief review of the development and system architecture of UAV systems for forest fire monitoring, detection, and fighting is provided. Next, technologies related to UAV forest fire monitoring, detection, and fighting are briefly reviewed, including those associated with fire detection, diagnosis, and prognosis, image vibration elimination, and cooperative control of UAVs. The final section outlines existing challenges and potential solutions in the application of UAVs to forest firefighting.

scholarly journals Forest Fire Intensity Monitoring Using the Himawari Weather Satellite―Taking Liaoning Forest Fires as Examples

2019 ◽  
Vol 131 ◽  
pp. 01088
Author(s):  
Jinwen Wu ◽  
Yushu Zhang ◽  
Longyu Sun ◽  
Ruipeng Ji ◽  
Wenying Yu ◽  
...  
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Blind Spot ◽  
Meteorological Conditions ◽  
Fire Intensity ◽  
Fire Monitoring ◽  
Almost All ◽  
Fire Accidents ◽  
In Fire ◽  
Fire Incidence

Almost all forest fires in Liaoning were caused by the act of men. Between 15:00-19:00, which is when the frequencies of human activities and the occurrence of fire peak, Liaoning is out of the path of the polar-orbiting satellites, making these 4 hours the blind spot domain in fire-incidence monitoring. At the same time, the trend of fire accidents changed quickly under the influence of local meteorological conditions, leading to the demand for a higher temporal resolution. Therefore, there is an urgent need to utilize the Himawari satellite in the forest fire intensity monitoring so as to compensate for the drawbacks of the polar-orbiting satellites. By improving the forest fire identification model of the Himawari-8 satellite, a forest fire monitoring done every ten minutes was realized , thereby enhancing the effectiveness of fire monitoring and rescue within a given period of time.

scholarly journals Forest Fires in the Ural Federal district and their impact on the environment

2020 ◽  
pp. 4-12
Author(s):  
В.К. Куплевацкий ◽  
Н.Ш. Шабалина
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Federal District ◽  
Economic Damage ◽  
Environmental Damage ◽  
Minimum Area ◽  
Forest Protection ◽  
Significant Damage ◽  
Fire Area ◽  
Chelyabinsk Region

На основе актов и книг учета лесных пожаров, а также статистической отчетности проанализированы показатели фактической горимости лесов за 2016–2020 гг. Установлено, что за 2020 г. на территории Уральского федерального округа зафиксировано 2182 лесных пожара. При этом пройденная огнем площадь составила 167,2 тыс. га. Указанные показатели несколько превышают значения количества и пройденной огнем площади по округу за последние 5 лет: 1961 случай и 124,6 тыс. га соответственно. Наибольшее количество лесных пожаров зафиксировано в 2020 г. в челябинской области – 587 случаев, а наименьшее – в Ямало-Ненецком автономном округе – 111 случаев. При этом максимальной пройден- ной огнем лесных пожаров площадью в 2020 г. характеризуется Ханты-Мансийский автономный округ – Югра – 144,7 тыс. га. Минимальная пройденная огнем площадь зафиксирована в Тюменской области – 1,6 тыс. га. Площадь среднего пожара за 2020 г. по округу составила 76,64 га, при этом в Ханты-Мансийском авто- номном округе – Югре она равнялась 308,0 га, а в Тюменской области – 6,98 га. Экономический ущерб от лесных пожаров составил по округу 4 109 793, 16 тыс. руб., при этом на тушение было затрачено 575 481,57 тыс. руб. Значительный размер ущерба от лесных пожаров, а также экологический ущерб вызывают необходи- мость дальнейшего совершенствования охраны лесов. On the bases and books of forest fire accounting, as well as statistical reporting the indicators of actual forest fire rates for 2016–2020 were and lyzed. It was established that in 2020 2182 forest fires were recorded in the Ural Federal Distict. While the area covered by fire was 167,2 th/ga. These indicators slightly exceed the value of the number and the area covered by fire over the past five years in the district. The latter account for 1961 cases and 124,6 thousands of ha respectively. The largest number of forest fires was recorded in 2020 in Chelyabinsk region – 587 cases, the least in the Yamalonenets autonomous okrug – 111 cases. At the same time the maximum area covered by forest fires in 2020 is charaiterized by the Khanty-Mansiysk autonomous okrug – Yugra – 144,7 thousands of has. The minimum area covered by the fire was recorded in the Tyumen region – 1,6 th. ha. The average fire area in 2020 around the Okrug was 76,64 ha, at the same time in the Khanty-Mansiysk autonomous okrug – Yugra, it is 308,0 ha, but in the Tyumen region – 6,98 ha. The economic damage from forest fires amounted to 4 109 793,16 th of roubes, at the same time 575 481,57 th of ronbes were spent fire suppressing significant damage from forest fires as well as environmental damage necessitates futher forest protection improvement.

scholarly journals Fuzzy logic in controlling the forest fire - level forecast warning signage

2020 ◽  
Vol 61 (4) ◽  
pp. 126-136
Author(s):  
Quyen Thi Vu ◽  
Minh Ngoc Pham ◽  
Chinh Manh Dang ◽  
Hoang Huy Vuong ◽  
Hung Duc Duong ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Forest Fire ◽  
Forest Fires ◽  
Text Message ◽  
Forest Protection ◽  
The World ◽  
Forecasting System ◽  
Great Harm

Forest fires are always a problem around the world because of its great harm. Especially in Vietnam, the prevention and detection of forest fires are mainly based on the patrolling forest rangers; the warning board is not automatically controlled. In this article, we will present the design of an automatic controller, which was applied fuzzy logic to control the forest fire - level forecast warning signage. The controller relies on regional meteorological information to control the signage on the spot, and to directly inform the manager about the forest fire forecasting situation via text message. The experienced results of some forest protection units in Thai Nguyen prove that the application of fuzzy logic has met the requirements of the forest protection sector in improving the forest fire forecasting system.

scholarly journals Forest Farm Fire Drone Monitoring System Based on Deep Learning and Unmanned Aerial Vehicle Imagery

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Shaoxiong Zheng ◽  
Weixing Wang ◽  
Zeqian Liu ◽  
Zepeng Wu
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Monitoring System ◽  
Forest Fire ◽  
Forest Fires ◽  
Operating Cost ◽  
Operating Efficiency ◽  
Rescue Operation ◽  
Fire Monitoring ◽  
Forest Farm

Forest fires represent one of the main problems threatening forest sustainability. Therefore, an early prevention system of forest fire is urgently needed. To address the problem of forest farm fire monitoring, this paper proposes a forest fire monitoring system based on drones and deep learning. The proposed system aims to solve the shortcomings of traditional forest fire monitoring systems, such as blind spots, poor real-time performance, expensive operational costs, and large resource consumption. The image processing techniques are used to determine whether the frame returned by a drone contains fire. This process is accomplished in real time, and the resultant information is used to decide whether a rescue operation is needed. The proposed method has simple operations, high operating efficiency, and low operating cost. The experimental results indicate that the relative accuracy of the proposed algorithm is 81.97%. In addition, the proposed technique provides a digital ability to monitor forest fires in real time effectively. Thus, it can assist in avoiding fire-related disasters and can significantly reduce the labor and other costs of forest fire disaster prevention and suppression.

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