Forest Fire Detection System using Wireless Sensor Networks and Machine Learning

Dampage, Udaya; Bandaranayake, D. M. L. N.; Wanasinghe, W. M.R. S.; Kottahachchi, K. O.; Jayasanka, W. A. B.

doi:10.21203/rs.3.rs-722627/v1

Cited by 3 publications

(9 citation statements)

References 8 publications

(12 reference statements)

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“…According to Udaya Dampage et al [1], the authors proposed a forest fire detection system based on wireless SNs deployed in a cellular architecture to cover the entire area. The proposed mobile architecture is in situations where the forest fire detection system is not feasible.…”

Section: B Analysis Of Some Well-known Wsn Model For Monitoring Detec...mentioning

confidence: 99%

“…Also as suggested by [1], WSN is organized according to network architecture, and based on clusters, clusters are arranged according to mobile architecture. This is even more difficult to do because the closer the SNs are to the CH, the higher the energy consumption.…”

Section: B Analysis Of Some Well-known Wsn Model For Monitoring Detec...mentioning

confidence: 99%

“…Normally, the SN consists of a microcontroller (Memory Central Unit -MCU) that consumes 7.5 mW of power and that in standby mode consumes 1.8 mW, the sensor module consumes 0. 16 mW, the radio transceiver has the highest power consumption of 24 mW, and the power supply uses a Lithium battery with a capacity of 4,800 mAh [1], [11]. The SN is designed to be spherical to withstand external forces and has features that prevent damage from the harsh conditions common in tropical forests.…”

Section: Determination Of the Range Of Fmdwmentioning

confidence: 99%

“…The Arduino Nano board was chosen as a microcontroller device, which is small in size and flexible for a variety of applications. The nrf24L01 module is used as a transceiver on NSNs and ESNs to communicate with each other [1] and with the cluster head node T1CH. In the calculation of FMDW range determination, similar to [1], we assume that the maximum sensing range of an NSN called a sensor network cell is defined with a radius of the transceiver area of the NSN of RTxRx = 5 m. For ESNs, each ESN will be responsible for forwarding data to 2 neighboring NSNs, so the power supply for the ESN is determined to be doubled, meaning a capacity of 9,600 mAh and the same radius of the transceiver area.…”

Section: Determination Of the Range Of Fmdwmentioning

confidence: 99%

“…The nrf24L01 module is used as a transceiver on NSNs and ESNs to communicate with each other [1] and with the cluster head node T1CH. In the calculation of FMDW range determination, similar to [1], we assume that the maximum sensing range of an NSN called a sensor network cell is defined with a radius of the transceiver area of the NSN of RTxRx = 5 m. For ESNs, each ESN will be responsible for forwarding data to 2 neighboring NSNs, so the power supply for the ESN is determined to be doubled, meaning a capacity of 9,600 mAh and the same radius of the transceiver area. of the ESN is still 5 m. At the same time, the NSN/ESN button is mounted on the trunk of the tree 1m above the ground to effectively conduct the first-stage surface fire detection test [1].…”

Section: Determination Of the Range Of Fmdwmentioning

confidence: 99%

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Monitoring, Detecting and Early Warning of Forest Fires using Blockchain in Wireless Sensor Network

Huy¹,

Thien²,

Tran³

et al. 2022

IJCSMC

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Forest fires cause economic and material losses and destroy the environment, causing many negative impacts on human habitats and forest ecosystems. The unpredictable threat of wildfires leads to climate change and the greenhouse effect. It is worth noting that up to 90% of forest fires occur mainly due to human activities [1], even due to tampering, vandalism, and hostile actions. Therefore, to minimize the destruction caused by forest fires as well as accurately identify the area where forest fires occur and support government agencies, forest rangers, and search and disaster relief forces, ... it is necessary to monitor, detect and warn of forest fires right from the early stage (early warning). This paper proposes to use static sensor nodes combined with mobile in wireless sensor network (WSN) to Forest fire Monitoring, Detection, and Early Warning - FMDW. At the same time, integrating Blockchain technology (BC) in WSN solves the problem of secure routing, and distributed data storage, and prevents destructive and tampering attacks. This also suggests new research directions on monitoring, detecting, warning, and protecting forests in countries using Blockchain security technology in WSN.

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Section: B Analysis Of Some Well-known Wsn Model For Monitoring Detec...mentioning

confidence: 99%

Section: B Analysis Of Some Well-known Wsn Model For Monitoring Detec...mentioning

confidence: 99%

Section: Determination Of the Range Of Fmdwmentioning

confidence: 99%

Section: Determination Of the Range Of Fmdwmentioning

confidence: 99%

Section: Determination Of the Range Of Fmdwmentioning

confidence: 99%

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Monitoring, Detecting and Early Warning of Forest Fires using Blockchain in Wireless Sensor Network

Huy¹,

Thien²,

Tran³

et al. 2022

IJCSMC

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Weaving the Nodes: Actor Relations in Forest Fire Handling

Rahmah,

Khairi,

Anggraini

et al. 2024

KSS

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This study aims to identify and describe the actor-network on forest fire handling in South Sumatra in its all three stages. This study collects data through interviews and documents. R Studio is used to analyze and visualize the connection between actors. The results of this study show a formal division of activities among actors in forest fire handling based on Governor decree involving state and non-state actors. However, non-state actors were not involved in every operational activity, especially in the pre-disaster stage. Furthermore, the Head of the Forest and Land Fire Control Section plays an essential role in the pre-disaster stage, the Regional Disaster Management Agency in the emergency stage, while there is no actor interactions in the post-disaster stage. Such situation requires a better actor-network by weaving the nodes to ensure effective coordination considering the role, interaction, and intervention of the actors as well as the nature of inclusiveness through the involvement of all actors, especially that of non-state actors. The limitation of this study is dealing with its focus just on one perspective that is based on the legal framework. Future research is expected to broaden the perspective with empirical and factual research. Keywords: forest fire handling, network, social network analysis, south Sumatra

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Early Wildfire Detection Technologies in Practice—A Review

Mohapatra

Trinh

2022

Sustainability

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As fires grow in intensity and frequency each year, so has the resistance from their anthropic victims in the form of firefighting technology and research. Although it is impossible to completely prevent wildfires, the potential devastation can be minimized if fires are detected and precisely geolocated while still in their nascent phases. Furthermore, automated approaches without human involvement are comparatively more efficient, accurate and capable of monitoring extremely remote and vast areas. With this specific intention, many research groups have proposed numerous approaches in the last several years, which can be grouped broadly into these four distinct categories: sensor nodes, unmanned aerial vehicles, camera networks and satellite surveillance. This review paper discusses notable advancements and trends in these categories, with subsequent shortcomings and challenges. We also describe a technical overview of common prototypes and several analysis models used to diagnose a fire from the raw input data. By writing this paper, we hoped to create a synopsis of the current state of technology in this emergent research area and provide a reference for further developments to other interested researchers.

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Forest Fire Detection System using Wireless Sensor Networks and Machine Learning

Cited by 3 publications

References 8 publications

Monitoring, Detecting and Early Warning of Forest Fires using Blockchain in Wireless Sensor Network

Monitoring, Detecting and Early Warning of Forest Fires using Blockchain in Wireless Sensor Network

Weaving the Nodes: Actor Relations in Forest Fire Handling

Early Wildfire Detection Technologies in Practice—A Review

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