Forest Fire Detection using LoRa Wireless Mesh Topology

Adnan,; Salam, A. Ejah Umraeni; Arifin, Arham; Rizal, Muhammad

doi:10.1109/eiconcit.2018.8878488

Cited by 28 publications

(9 citation statements)

References 3 publications

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“…For example, the presence of compacted waste with limited oxygen supply can promote anaerobic conditions, leading to the production of flammable gases and an increased risk of fire.It is important to note that multiple factors can interact and contribute to landfill fires, making it crucial to implement preventive measures and early detection systems to minimise the risk and mitigate the potential consequences.In [1] -[4] are surveys and case studies on Ghazipur Landfill site of Delhi .in [5] a general method for fire control but not for its prevention. The following papers [6]- [11] are on Landfill fires and some of the projects on fire detection. The hazards to health and environment because of these fires are also addressed along with waste management systems for the dump yards.…”

Section: Problem Statementmentioning

confidence: 99%

An Intelligent IoT Based Landfill Fire Prediction And Prevention System

SAKYA,

Yadav,

Shukla

et al. 2023

Preprint

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This work focuses on India’s tallest heap of garbage at Ghazipur landfill site in New Delhi. About 2000 tonnes of garbage is being dumped at Ghazipur every day and it causes poisonous gases. Fire, sparked by methane gas coming from the garbage and takes days to extinguish. Methane belching from garbage can cause even more toxic gases. The dumping of garbage needs to be stopped for the betterment of people and the environment. The research helps detect the gases released from garbage and the importance of the project increasing due to the growth of solid waste. The detection of the risk of fire and the communication of this situation to the people could reduce the number of fires. The system also helps with automatic detection of fire in garbage-dumped areas and alerts to the authorities. This research work presents a low cost network based on Long Range(LoRa) network which is able to assess automatically the level of risk of catching fire in the solid waste. The system consists of several LoRa nodes with sensors to scale temperature, relative humidity and increase in methane level. The data coming from LoRa nodes is stored and processed in the server that is The Things Network and sends data finally to a website or an application for the analysis of the collected data using machine learning . This helps in reducing environmental pollution which results in health hazards for the people residing in the vicinity.The Simulation of the Lora Network is done in NS-3 first ,for finding the throughput and latency with different scenarios of lora nodes and gateways. The deployin stretegies are fixed after ns-3 simulation. The ns-3 simulation is done in ns-3.36.1 using lorawan module.Thereafter the prototype model is prepared using LoRA hardware and different sensors. The real time data is collected on the server for data analysis. The work have used machine learning algorithms to analyse real-time sensor data received on a network server through the LoRa Gateway to detect abnormal patterns indicative of a potential fire outbreak and to justify the ―intelligence‖ of our system. The wireless LoRa communication eliminates extensive wiring, while intelligent data analysis enhances accuracy and minimizes false alarms. Experimental evaluations demonstrate the system's effectiveness in timely fire detection and response, minimizing environmental impact and ensuring community safety. The proposed system presents a promising solution for efficient landfill fire early detection, prevention, and mitigation.

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Section: Problem Statementmentioning

confidence: 99%

An Intelligent IoT Based Landfill Fire Prediction And Prevention System

SAKYA,

Yadav,

Shukla

et al. 2023

Preprint

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“…Some works focus on specific use cases of the architectures discussed above, including forest fire detection [ 14 ], wild animals [ 15 ] and livestock [ 16 ] tracking, urban drainage [ 17 ] and monitoring of underground environments (e.g., medieval aqueducts) [ 18 ]. In all these cases, remote areas can be reached by multi-hop communication and/or mesh networking capabilities, and collected data are finally conveyed towards a gateway for further routing and processing.…”

Section: Related Workmentioning

confidence: 99%

A LoRa-Based Mesh Network for Peer-to-Peer Long-Range Communication

Berto

Napoletano

Savi

2021

Sensors

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LoRa is a long-range and low-power radio technology largely employed in Internet of Things (IoT) scenarios. It defines the lower physical layer while other protocols, such as LoRaWAN, define the upper layers of the network. A LoRaWAN network assumes a star topology where each of the nodes communicates with multiple gateways which, in turn, forward the collected data to a network server. The main LoRaWAN characteristic is the central role of the gateways; however, in some application scenarios, a much lighter protocol stack, relying only on node capabilities and without the presence of gateways, can be more suitable. In this paper, we present a preliminary study for realizing a LoRa-based mesh network, not relying on LoRaWAN, that implements a peer-to-peer communication between nodes, without the use of gateways, and extends node reachability through multi-hop communication. To validate our investigations, we present a hardware/software prototype based on low-power-consumption devices, and we preliminarily assess the proposed solution.

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“…orest fires are disasters that cause extensive damage to the entire world in economic, ecological, and environmental ways. 13 These fires can be caused by natural reasons, such as high temperatures that can create a spontaneous combustion of dry fuel 14 such as sawdust, leaves, lightning, etc., or by human activities, such as unextinguished campfires, arson, inappropriately burned 15 debris, etc. [1] According to research, 90% of the world's forest fire incidents have occurred as a result of the abovementioned human carelessness.…”

Section: Introductionmentioning

confidence: 99%

“…A mesh topology was chosen over a star topology because of its ability to self-organize, self-configure, and automatically establish among nodes in a network. [13]. As a smaller number of nodes involved for transmission results in minimum energy consumption, concepts based on cluster heads have been used [14].…”

Section: Introductionmentioning

confidence: 99%

“…When considering attributes such as transmission range and other relevant configurations, most papers have suggested using the LoRa module for transmission. [13] Most papers have suggested having threshold value-based fire detection on a sensor node, and if the exceeded threshold has remained the same, then a sink determines the location and will send an alarm to the fire department [11]. Because of the environmental parameter variations according to the place and time, threshold values are configured by the user considering geographic situations, climatic changes, seasonal changes, etc.…”

Section: Introductionmentioning

confidence: 99%

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Forest Fire Detection System using Wireless Sensor Networks and Machine Learning

Dampage

Bandaranayake

Wanasinghe

et al. 2021

Preprint

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Forest fires have become a major threat around the world, causing many negative impacts on human beings and forest ecosystems. Even though rapid climatic changes arising from high environmental pollution, greenhouse effects, etc. have caused this situation, a higher percentage of forest fires occur due to human activities. Therefore, to minimize the destruction caused by forest fires, the need to detect forest fires at their initial stage is needed. This paper proposes a model that can be used to detect forest fires at the initial stage using a wireless sensor network. Furthermore, to acquire more accurate fire detection, a machine learning regression model is proposed. Moreover, thorough attention is given to sensor node design and node placement in the forest to be fitted in the forest environment to minimize the damage and harmful effects caused by wild animals, weather conditions, etc. to the system.

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Forest Fire Detection using LoRa Wireless Mesh Topology

Cited by 28 publications

References 3 publications

An Intelligent IoT Based Landfill Fire Prediction And Prevention System

An Intelligent IoT Based Landfill Fire Prediction And Prevention System

A LoRa-Based Mesh Network for Peer-to-Peer Long-Range Communication

Forest Fire Detection System using Wireless Sensor Networks and Machine Learning

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