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

Xu, Yi‐Han; Sun, Qiu-Ya; Xiao, Yutong

doi:10.3390/fi10100102

Cited by 18 publications

(14 citation statements)

References 22 publications

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“…First, the literature review explored the importance of grasslands (Carlier et al, 2009;LandScope Colorado, 2020) and the destructive power of remote grassfires in SE Colorado (Grewe, 2020;Lynn & Campbell-Hicks, 2020;Markus, 2022). Second, the literature review showcased works highlighting WSN-based wildfire detection and the increase in destructive risk resulting from the delayed receipt of wildfire alerts by firefighters (Georgiades et al, 2019;Xu et al, 2018). The sparse and underdeveloped SE Colorado communication infrastructure between remote grassfire detective technology and fire stations exacerbates risk (Crosby & Vafa, 2013;DOLA, 2019;nPerf, 2021).…”

Section: Review Of the Literaturementioning

confidence: 99%

A Cybersecurity Study: Examining the Relationship between Converged-Network Architecture and Remote Grassfire Alert Transmission Delay in Southeast Colorado

P Wagoner,

Sambasivam

2022

InSITE Conference

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Aim/Purpose: The purpose of the present study was to examine the relationship between a converged wireless-sensor/cellular network architecture and cybersecurity, in terms of transmission delay, to deliver remote grassfire alerts to firefighters in Southeast (SE) Colorado. Background: Agriculture, rural communities, a thriving cattle industry, and a kaleidoscope of flora and fauna characterize the plains of SE Colorado. Unfortunately, the hot and dry climate of SE Colorado combines with the ever-expanding wildland-urban interface (WUI), presenting an enormous grassland fire risk. A review of the literature revealed a deficit of research that addressed the alerting mechanism between remote WSN-based fire detection and response forces. Methodology: The present research pursued a converged-network solution from two courses of action (COA) to address the wildfire risk. COA-A and COA-B coupled the ZigBee-Pro and ZigBee-IP WSN protocols, respectively, with the 4G-LTE infrastructure prevalent throughout SE Colorado to bolster alert information availability. Following construction of the simulation models, the Ostinato packet generator performed 194 end-to-end transmissions with each COA to ascertain the better-performing solution in terms of network transmission delay. Contribution: The study’s findings offer a starting point for subsequent research that will lead to a proposal for SE Coloradans – and beyond – to help bridge the gap between detective WSNs and the response forces that can subdue remote grassfires. To the extent the authors could surmise, the current research effort was the first to model and simulate a one-way, UDP-based wireless network that comprised a WSN node, two WSN-Cellular gateway designs, and several 4G-LTE infrastructure components. The simulated environment also measured and compared the end-to-end network transmission delay for two unique solutions, including the convergence process within the WSN-Cellular gateway. Findings: COA-B proved the superior solution with a 16.2% delay improvement over COA-A. An independent-samples t-test confirmed the statistical significance between the results’ means. Recommendations for Practitioners: COA-B offered a remote SE Colorado grassfire alerting solution that minimized network transmission delay and maximized alert payload to responding firefighters. However, the generalizability of the current research’s results indicates utility for firefighters providing overwatch to grasslands throughout the world – wherever valuable grasslands intersect with a 4G-LTE on-ramp. Within the United States and outside SE Colorado, 4G-LTE from multiple carriers exists throughout the Great Plains. U.S. industries, communities, and ecosystems that rely on the abundance of Great Plains grasslands abound and feature use cases ripe for benefit from the present research. Recommendations for Researchers: Additional studies could offer more depth and recommend solutions to bolsters the alert mechanism between fire detection and response capabilities. The literature is teeming with research that improves the efficacy of fire-detective WSNs. However, the dearth of practice-oriented research that delivers an alert to firefighters in SE Colorado and elsewhere warrants further work on top of the present study. Impact on Society: The study’s findings need not apply only to grassfires. Much research and residual challenges exist on the topic of forest and wildfire alerts throughout the world. Although the generation mechanisms may differ, propelling an alert over available infrastructure – 4G-LTE or other – offers a workable solution to ensure timely response to unsolicited fires. Future Research: The current research’s incremental construction of delay measurements for COA-A and COA-B encourages the creation of an end-to-end model in network simulators such as NS3 or OMNeT++. A network simulation framework like OMNeT++ would allow a more comprehensive representation of wireless channel effects on overall delay. The creation and testing of a physical COA-B prototype would provide a proof of concept for the current study. Future work could bridge the gap between any varietal of remote sensor network and the audience that consumes sensor data anywhere in the world.

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Section: Review Of the Literaturementioning

confidence: 99%

A Cybersecurity Study: Examining the Relationship between Converged-Network Architecture and Remote Grassfire Alert Transmission Delay in Southeast Colorado

P Wagoner,

Sambasivam

2022

InSITE Conference

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“…7 and Fig. 8, respectively [34]. Based on this, we recommended a 25 meters distance between nodes, giving us an average of 16 minutes of response time since the fire ignition.…”

Section: Prototype Developmentmentioning

confidence: 99%

LPWAN Based IoT Surveillance System for Outdoor Fire Detection

Roque

Padilla

2020

IEEE Access

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Many fire situations have represented the loss of lives and material costs due to the lack of early fire detection through smoke or gas sensing, which can become complex and critical. Meanwhile, engineers worldwide develop and test multiple systems for smoke and gas detection, commonly based on sensor networks, digital image processing, or computer vision. Furthermore, the detection system must work thoroughly with alarms and warnings that aware of a risk situation for prompt evacuation of the population in the surroundings based on a reliable data network topology with adequate device deployments that will let us know the moment a fire outbreak. This paper presents a low-cost Internet of Things (IoT) prototype for fire detection in outdoor environments based on sensors and Low Power Wide Area Network (LPWAN), focused on the accuracy in the temperature and gas measurement at the moment a fire starts. For its achievement, we integrated wireless components, development boards, and electronic devices, following the management of information updates through a database schema for the alarm settings based on the data gathered from the sensors. INDEX TERMS database systems, emergency services, gas detectors, sensor systems, temperature measurement.

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“…• Xu et al [28] proposed a formula for sensor distribution in a forest area, solving problems of optimal coverage by taking into account the topology of the covered area.…”

Section: Wireless Sensor Network Based Systemsmentioning

confidence: 99%

From Pillars to AI Technology-Based Forest Fire Protection Systems

Aspragathos¹,

Dogkas²,

Konstantinidis³

et al. 2020

Intelligent System and Computing

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The importance of forest environment in the perspective of the biodiversity as well as from the economic resources which forests enclose, is more than evident. Any threat posed to this critical component of the environment should be identified and attacked through the use of the most efficient available technological means. Early warning and immediate response to a fire event are critical in avoiding great environmental damages. Fire risk assessment, reliable detection and localization of fire as well as motion planning, constitute the most vital ingredients of a fire protection system. In this chapter, we review the evolution of the forest fire protection systems and emphasize on open issues and the improvements that can be achieved using artificial intelligence technology. We start our tour from the pillars which were for a long time period, the only possible method to oversee the forest fires. Then, we will proceed to the exploration of early AI systems and will end-up with nowadays systems that might receive multimodal data from satellites, optical and thermal sensors, smart phones and UAVs and use techniques that cover the spectrum from early signal processing algorithms to latest deep learning-based ones to achieving the ultimate goal.

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

Cited by 18 publications

References 22 publications

A Cybersecurity Study: Examining the Relationship between Converged-Network Architecture and Remote Grassfire Alert Transmission Delay in Southeast Colorado

A Cybersecurity Study: Examining the Relationship between Converged-Network Architecture and Remote Grassfire Alert Transmission Delay in Southeast Colorado

LPWAN Based IoT Surveillance System for Outdoor Fire Detection

From Pillars to AI Technology-Based Forest Fire Protection Systems

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