The wildfire is the most alarming threat to ecosystems,
whether human-made or natural. Unfortunately, fires destroy many hectares of
forest area each year due to late and ineffective fire detection. It is crucial
to detect forest fires early to prevent them from spreading widely and harming
the environment. Many research has been conducted in this field, but effective
fire detection and reduction remain a challenge. The proposed system aims to
address this challenge by developing a firefighting machine using advanced
Artificial Intelligence (AI) and Internet of Things (IoT) technology.
Currently, it is undergoing field trials. The primary objective of this machine
is to generate artificial rain through drones equipped with sodium bicarbonate.
This process aims to seed clouds and produce rain droplets to mitigate fire
outbreaks. Data collection is automated, with information being captured and
stored in a cloud-based system via the IoT. Images of both fire and normal
conditions are collected and used to train AI models for wildfire detection.
TensorFlow is utilized to support drone operations in this process. The IoT
cloud platform, Thing Speak, is chosen for its efficiency and reliability in
managing data modules. The stored data in the cloud is crucial for training AI
models effectively, enabling accurate wildfire detection and timely response.
The designed AI and IoT-enabled drones can accurately detect fires and deploy
artificial rain to suppress them immediately.
Author(s) Details
Anita Keshav Patil
Department of Electronics and Telecommunication, Dr.
Vithalrao Vikhe Patil College of Engineering MIDC, Vilad Ghat, Ahmednagar
-414111, Maharashtra, India.
Please see the link:- https://doi.org/10.9734/bpi/strufp/v8/1167
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