IoT and Image Processing based Forest Monitoring and Counteracting System

Pareek, Shivam; Shrivastava, Shreya; Jhala, Sonal; Siddiqui, Juned A.; Patidar, Savitanandan

doi:10.1109/icoei48184.2020.9142996

Cited by 9 publications

(4 citation statements)

References 5 publications

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“…Solar power is the ideal alternative because of its specific advantages and availability over other power supply systems. This paper discusses the various technologies that are used for wildfire detection [21][22][23]. It also analyses the advantages and disadvantages and compares the various methods based on their mode of operation.…”

Section: __________________________mentioning

confidence: 99%

A Detailed Investigation on Forest Monitoring System for Wildfire Using IoT

Wesly

Chaitanya

Kumar

et al. 2023

Advances in Transdisciplinary Engineering

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The world’s forests cover one-third of the planet’s land surface, and it is necessary to sustain life with this geography. There is enough food, water, and energy for us to live off of them. Forest fires have recently surpassed all other forms of environmental degradation as the leading cause of death and destruction on Earth. Wildfires in the Amazon rain forest charred hundreds of hectares of land in 2019. A well-structured forest-monitoring system has been put in place in order to keep an eye on it. Incorporating the Internet of Things (IoT) and image processing systems is a real game-changer. The wireless network has made use of both of these techniques in recent times. This paper discusses the various technologies that keep track of the forest’s environmental conditions in real time and identify wildfires. Based on the information, the alerts are passed to the authorities to take action and protect the forest from further damage.

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Section: __________________________mentioning

confidence: 99%

A Detailed Investigation on Forest Monitoring System for Wildfire Using IoT

Wesly

Chaitanya

Kumar

et al. 2023

Advances in Transdisciplinary Engineering

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“…Many studies on routing algorithms and protocols have been conducted in order to improve the performance of forest fire sensing networks, which is one approach to reducing the risk and damage caused by forest fires [4], [5]. Furthermore, numerous recent studies on the development of forest fire monitoring, detection, and warning systems using image processing, sensor networks, and IoT technology have been conducted [6]- [20]. Cloud-edge computing and unmanned aerial vehicle-Internet of Things (UAV-IoT) networks are also proposed as effective methods for detecting and forecasting wildfire behavior [20]- [22].…”

Section: Introductionmentioning

confidence: 99%

Design and implementation of a LoRa-based system for warning of forest fire

Truong,

Tran,

2023

TELKOMNIKA

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This paper presents the design and implementation of a forest fire monitoring and warning system based on long range (LoRa) technology, a novel ultra-low power consumption and long-range wireless communication technology for remote sensing applications. The proposed system includes a wireless sensor network that records environmental parameters such as temperature, humidity, wind speed, and carbon dioxide (CO2) concentration in the air, as well as taking infrared photos. The data collected at each sensor node will be transmitted to the gateway via LoRa wireless transmission. Data will be collected, processed, and uploaded to a cloud database at the gateway. An Android smartphone application that allows anyone to easily view the recorded data has been developed. When a fire is detected, the system will sound a siren and send a warning message to the responsible personnel, instructing them to take appropriate action. Experiments in Tram Chim Park, Vietnam, have been conducted to verify and evaluate the operation of the system.

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“…The result is overwhelming adversity, frightful detriment to the environmental factors and climate, and irreversible damage to biology [1]. Animals during bushfires are impacted numerously in a total count of around a unit of estimation semi-extremely durable decisive impacts like effects on local climate examples; warming, and extinction of uncommon types of greenery [2]. Quick and successful locations play a crucial role in the disaster.…”

Section: Introductionmentioning

confidence: 99%

Prior Bush Fire Identification Mechanism based on Machine Learning Algorithms

Atheeq¹,

Mohammad²,

Mohammed³

2022

IJAIA

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Besides causing awful fatalities resulting in deaths and significant resources like many acres of timberland and dwelling places, forest fires are a significant threat to sound enormous wilderness biologically and environmentally. Consistently, a considerable number of fires around the globe reason debacles to different habitats and layouts. The stated matter has been the investigation premium for a significant length of time; there is a considerable amount of good concentrated on arrangements available for testing or perhaps ready to be utilized to determine this disadvantage. Woods and actual flames have been severe issues for quite some time. Presently, there is a wide range of answers for distinguishing woods fires. Individuals are utilizing sensors to determine the fire. However, this case isn't workable for vast sections of land woods. This paper discusses another fire-recognition methodology with incremental advancements. Specifically, we put forward a stage-Artificial Intelligence. The PC innovation strategies for acknowledgment and whereabouts of smog and fires, in light of the inert photographs or the graphics captured by the cameras. AI for tracing down the fires. The accuracy relies on the calculations that use dataset values later divided in various test and train sets, respectively.

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IoT and Image Processing based Forest Monitoring and Counteracting System

Cited by 9 publications

References 5 publications

A Detailed Investigation on Forest Monitoring System for Wildfire Using IoT

A Detailed Investigation on Forest Monitoring System for Wildfire Using IoT

Design and implementation of a LoRa-based system for warning of forest fire

Prior Bush Fire Identification Mechanism based on Machine Learning Algorithms

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