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@article{179646,
        author = {R. Elavarasi and S. Arjun and P. Karthik and B. Manjunath and N. Naveen Reddy},
        title = {Forest Fire and Animal Detection Using Drone},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {7382-7386},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=179646},
        abstract = {The design and development of an 
autonomous drone aim to detect and alert forest fires 
and identify animals within forest areas, particularly 
when they encroach upon human settlements, thereby 
notifying the appropriate authorities. The drone is built 
using a plastic structure designed in a hexagonal shape 
for aerodynamic efficiency. Its control system is divided 
into two main components: the flight controller and the 
intruder detection camera control unit. The flight 
controller integrates a telemetry module, a receiver 
module, and an ESC (Electronic Speed Controller) 
module, all of which are managed through the Mission 
Planner control software. For image-based detection of 
forest fires and animals, the camera system operates on 
a Python platform. The drone is capable of autonomous 
operation using Auto mode, navigating via waypoints 
to perform fire and animal detection tasks. During 
testing, both manual and automatic flight modes were 
evaluated. In manual mode, the drone successfully 
identified fire and animals within the surveillance zone, 
provided the speed and camera range were suitably 
configured for effective detection. In autonomous 
mode, particularly at very low altitudes, the system 
demonstrated its highest accuracy in detecting and 
alerting potential threats. The effectiveness of the 
detection depends on factors such as the active range of 
the camera and maintaining an appropriate flight 
speed during manual operation.},
        keywords = {Compact Drone, Camera, GPS, RF  Communication,  Python,  OpenCV,  YOLO,  TensorFlow, GSM, Convolutional Neural Network  (CNN) Model, Object Detection, Fire Detection, Real time Monitoring.},
        month = {May},
        }