This research develops an effective and precise collision detection (CD) algorithm for real-time simulation in virtual environments such as computer graphics, realistic and immersive virtual reality (VR), augmented reality (AR) and physical-based simulation within an enhanced algorithm for object collision detection in 3D geometry. We describe an improved algorithm through a comparison in the application of a central processing unit (CPU) and graphics processing units (GPU). Although leveraging CPU for computational speed improvements has gained significant recognition in recent years, this study distinguishes by tracking 3D geometry bounding volume hierarchy (BVH) constructed in a spatial decomposition structure with a focus on Octree-based Axis-Aligned Bounding Box (AABB) structure in 3D scene to compute collision detection to swiftly reject disjoint objects and minimize the number of triangle primitives that need to be processed and then the Möller method is utilized to compute precise triangle primitives, further enhancing the efficiency and precision of the collision detection process. This approach is also designed to implement computation with GPU which utilizes the high-level shader language (HLSL) programming language on the compute shader Unity3D. AABB is structured as the maximum and minimum hexahedron enclosing an object that is parallel to the coordinate axis. Otherwise, GPU computational technique is a crucial method for further enhancing the object’s performance. The proposed method utilizes Octree AABB-based GPU parallel processing to reduce the computational load of real-time collision detection simulations and to handle multiple computations simultaneously. Comparative performance evaluations demonstrate that our GPU-accelerated framework consistently reaches the fastest collision detection times from 1.01 to 45.62 times, respectively.