Smart Terrain Recognition System with Yolov8 Model

Smart Terrain Recognition System with Yolov8 Model

Anmol Deshratna Saxena , Drishti Sinha , Ayush Thakre , Aditya Gode , Rashmi Phalnikar

SoCSE, Dr. Vishwanath Karad MIT World Peace University

Pune, Maharashtra, India

Abstract—
Intelligent Terrain Identification for Agricultural and Environmental Uses Accurate terrain description is essential for effective agricultural and environmental planning. This work explores the precise and efficient terrain type detection using state-of-the-art computer vision techniques such as You Only Look Once (YOLO). Our objective is to combine image data with terrain features, such as plains, forests, mountains, and deserts, to develop a dependable system for forecasting landscape characteristics. This approach is less expensive and time-consuming than traditional survey methods, yet it provides insightful information that may be used to enhance agricultural practices, irrigation systems, and infrastructure development. Combining data fusion and model optimization ensures effective terrain recognition, enabling informed decision-making in various agricultural and environmental contexts.

Keywords: computer vision, data fusion, model optimization, remote sensing, land use planning, YOLO, terrain analysis, agricultural development, environmental management, and smart terrain recognition.