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

A Sybil attack detection scheme for a forest wildfire monitoring application

© 2016 Elsevier B.V. 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

Towards an ultra‐low‐power low‐cost wireless visual sensor node for fine‐grain detection of forest fires

Advances in electronics, sensor technologies, embedded hardware and software are boosting the application scenarios of wireless sensor networks. Specifically, the incorporation of visual capabilities into the nodes means a milestone, and a challenge, in terms of the amount of information sensed and processed by these networks. The scarcity of resources – power, processing and memory – imposes strong restrictions on the vision hardware and algorithms suitable for implementation at the nodes. Both, hardware and algorithms must be adapted to the particular characteristics of the targeted application. This permits to achieve the required performance at lower energy and computational cost. We have followed this approach when addressing the detection of forest fires by means of wireless visual sensor networks. From the development of a smoke detection algorithm down to the design of a low‐power smart imager, every step along the way has been influenced by the objective of reducing power consumption and computational resources as much as possible. Of course, reliability and robustness against false alarms have also been crucial requirements demanded by this specific application. All in all, we summarize in this paper our experience in this topic. In addition to a prototype vision system based on a full‐custom smart imager, we also report results from a vision system based on ultra‐low‐power low‐cost commercial imagers with a resolution of 30×30 pixels. Even for this small number of pixels, we have been able to detect smoke at around 100 meters away without false alarms. For such tiny images, smoke is simply a moving grey stain within a blurry scene, but it features a particular spatio‐temporal dynamics. As described in the manuscript, the key point to succeed with so low resolution thus falls on the adequate encoding of that dynamics at algorithm levelMinisterio de Economía y Competitividad TEC2012‐38921‐C02, IPT‐2011‐1625‐430000, IPC‐ 20111009 CDTIJunta de Andalucía TIC 2338‐201

Optimization of Sensor Network Topology in Deployed in Inhomogeneous Lossy Media

This paper presents optimization of wireless sensor network (WSN) topology for forest fire detection. The sensors for this purpose are deployed in forest, grassland and open space, which have different attenuation properties in electromagnetic waves. For this reason, routers which receive signals from sensors and send them to the base station must be deployed considering these differences. In this work, we develop an optimization method for WSN topology based on simulated annealing considering the differences in the attenuation property. The vegetation data are taken from Landsat data. Using the present method, the necessary number of routers for full connection of the sensors deployed in diverse, irregular environments can be estimated

IoT-inspired Framework for Real-time Prediction of Forest Fire

Wildfires are one of the most devastating catastrophes and can inflict tremendous losses to life and nature. Moreover, the loss of civilization is incomprehensible, potentially extending suddenly over vast land sectors. Global warming has contributed to increased forest fires, but it needs immediate attention from the organizations involved. This analysis aims to forecast forest fires to reduce losses and take decisive measures in the direction of protection. Specifically, this study suggests an energy-efficient IoT architecture for the early detection of wildfires backed by fog-cloud computing technologies. To evaluate the repeatable information obtained from IoT sensors in a time-sensitive manner, Jaccard similarity analysis is used. This data is assessed in the fog processing layer and reduces the single value of multidimensional data called the Forest Fire Index. Finally, based on Wildfire Triggering Criteria, the Artificial Neural Network (ANN) is used to simulate the susceptibility of the forest area. ANN are intelligent techniques for inferring future outputs as these can be made hybrid with fuzzy methods for decision-modeling. For productive visualization of the geographical location of wildfire vulnerability, the Self-Organized Mapping Technique is used. Simulation of the implementation is done over multiple datasets. For total efficiency assessment, outcomes are contrasted in comparison to other techniqueS

무선 센서 네트워크에서 에너지 절감을 위한 계층 토폴로지 제어

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2015. 8. 신현식.Simple wireless sensor networks (WSNs) usually have a flat topology and transmit data using a flooding scheme of which there are several variants. However, these can cause the broadcast storming problem, reducing the efficiency and reliability of the WSN. Due to these problems, most WSNs have a cluster or tree structurebut this causes an imbalance of residual energy between nodes, which gets worse over time as nodes become defunct and replacements are inserted. Moreover, a defunct cluster head leads to a sharp drop of network connectivity. Therefore, an efficient way to improve the energy imbalance and the network connectivity is needed. In this thesis, we propose a hierarchical topology control scheme, in which each node periodically selects its own layer accommodating itself with different levels of residual energy and the amount of data to transfer, in order to balance the energy level and to increase the network connectivity. Simulations show that this scheme can balance node energy levels, and thus extend network lifetime. We also introduce a hierarchical topology control scheme for WSNs, which contains both energy-harvesting nodes and battery-powered nodes, in order to extend the lifetime of battery-powered nodes and to increase the network connectivity. In such a WSN, the energy harvesting nodes are also arranged in layers like the battery-powered nodes depending on their expected level of residual energy. This scheme is shown to increase the lifetime of battery-powered nodes preferentially by locating energy-harvesting nodes on the higher layers.Abstract i Contents iii List of Figures vi List of Tables ix 1 Introduction 1 1.1 Motivation 1 1.2 Research Contributions 4 1.3 Organization of This Thesis 5 2 Background and Related Work 7 2.1 Wireless Sensor Networks 7 2.1.1 Characteristics of WSNs 8 2.1.2 WSN Applications 10 2.1.3 Topology Control for WSNs 18 2.1.4 WSN using multiple sink nodes 22 2.2 Energy-harvesting WSNs 22 2.2.1 Hierarchical Topology Control for WSNs with Energy-Harvesting Nodes 23 3 Multi-layer Topology Control for Long-term Wireless Sensor Networks 25 3.1 Layer-Based Topology Control 25 3.1.1 Proposed Scheme 25 3.1.2 The Layering Algorithm Design 26 3.2 Layer Determination 28 3.2.1 TCI message 30 3.2.2 How a node selects its layer 30 3.3 Experimental Results 32 3.3.1 Simulation Environment 33 3.3.2 Simulation Results 35 4 Energy-aware Hierarchical Topology Control for Wireless Sensor Networks with Energy-Harvesting Nodes 41 4.1 Layer-based Topology Control with Energy-harvesting Sensor Nodes 41 4.1.1 Review of Layer-based Topology Control for Long-term WSNs with Battery-powered Nodes 42 4.1.2 The Layer Determination Algorithm 43 4.1.3 Introducing Energy-Harvesting Nodes to a Layered Topology 56 4.2 Experimental Results 58 4.2.1 Simulation Environment 58 4.2.2 Simulation Results 59 5 Conclusion 73 5.1 Summary 73 5.2 Future Research Directions 75 요약 92Docto

PEMANTAUAN PERILAKU TUMBUHAN MIMOSA PUDICA TERHADAP EFEK GERHANA MATAHARI TOTAL BERBASIS WIRELESS SMART SENSOR

The phenomenon of a total solar eclipse (total solar eclipse) can only occur within a period of 100 years, until now, even the natural phenomena related research is very interesting to do mainly related to metabolic processes that occur in green plants or high level. In the study, the behavior of Mimosa pudica plant will be measured by using a sensor device. The sensor device with PISA algorithm will monitor environmental factors such as light intensity, temperature, humidity and atmospheric pressure at the time of a solar eclipse total. In this case, changes in the behavior of Mimosa pudica plant to sunlight will be validated by using a digital camera to obtain information leaf movement. The results of this study the sun upon the occurrence of a total eclipse, the temperature conditions around the plant Mimosa pudica average 26oC. The movement of the leaves of Mimosa pudica move to close when the temperature of 25° C at 07. 43 pm. Leaves of Mimosa pudica reopened at 7:52 pm when the temperature is more than 27oC. sunlight at 7:24 o'clock pm at the time of the total solar eclipse of 1800 Lux. From the results of the measurements, light intensity sensor node at 07:25 - 07.29 pm downhill until the condition is 0 Lux, which means the condition is very dark with no light around the plant. From the results of measurements made at 07:39 hours GMT where the changes in air temperature around the leaf on the value of 25.59°C and light intensity levels 1729.4 Lux, Mimosa pudica leaves start to close. By the time the sun began to shine the light level the surface of the leaves, and the air temperature increases, the leaves of Mimosa pudica made the decision to seal the surface of the leaf, after 3 minutes the leaves will open again because there is no stimulus temperature and light. This research also analyzed the data with modeling RGB on the surface of the leaves to get the data chlorophyll Before the solar eclipse average picture chlorophyll on the leaf surface is 0.68149. By the time the sun shone on the condition of 3% on average 0.15494 prior to the occurrence of a total solar eclipse. On the condition of the leaves cover the average - average 0.29555, and after a solar eclipse passing and riding conditions and uneven irradiation, the average value of chlorophyll on the leaf surface is 0.54612

Priority Based Routing for Forest Fire Monitoring in Wireless Sensor Network, Journal of Telecommunications and Information Technology, 2014, nr 3

Recently, forest fire monitoring system in wireless sensor networks has received much attention. The conventional scheme receives fire alert data quickly to inform about fire forest event. However, since two or more nodes may detect a fire, high priority fire detection data frequently collide. In this paper, a new forest fire monitoring system is proposed in order to reduce high priority fire detection data dropped rate, by specifying a high priority received data immediately after fire detection and just before the destruction by fire. Furthermore, the node only transmits high priority data to a node, which has a low possibility of destruction by fire for low end-to-end delay of high priority fire detection data. The simulation results show that proposed scheme can reduce high priority data dropped ratio and the end-to-end delay, and have less effect of wind direction compared with the conventional scheme

A review of forest fire surveillance technologies: Mobile ad-hoc network routing protocols perspective

Mobile Ad-Hoc Network (MANET) is a type of structure-less wireless mobile network, in which each node plays the role of the router and host at the same time. MANET has gained increased interest from researchers and developers for various applications such as forest fire detection. Forest fires require continuous monitoring and effective communication, technology, due to the big losses are brought about by this event. As such, disaster response and rescue applications are considered to be a key application of the MANET. This paper gives an extensive review of the modern techniques used in the forest fire detection based on recent MANET routing protocols such as reactive Location-Aided Routing (LAR), proactive Optimized Link State Routing (OLSR) and LAR-Based Reliable Routing Protocol (LARRR)