NanoScan - Horizon & Object Detection + Tracking WITHOUT AI

In this video I demonstrate NanoScan's Horizon detection ability as well as its object detection and tracking capabilities. This software requires NO artificial intelligence for object detection (YOLO, EfficientDet, SSD, etc) and can run on a raspberry pi zero. NanoScan uses OpenCV. Video is of Israel Iron Dome.
OpenCV is an open-source library for computer vision and image processing, offering tools for tasks like image/video processing, object detection, and feature extraction. It's used in applications such as robotics, medical imaging, and security systems.
AI, a broader field, aims to create machines/systems capable of human-like tasks enabling the use of pretrained models or custom trained models for tasks such as image classification using methods like ML/DL. This requires significant more processing and often requires neural network acceleration devices to be practical, such as GPUs, nvidia jetson, or coral TPU.
While OpenCV supports AI by preprocessing data for algorithms, it is not AI technology itself, but a tool to facilitate AI applications. Traditional computer vision implemented in OpenCV, does not use machine learning or deep learning. It is a straightforward algorithmic approach that calculates the absolute difference between corresponding pixels in two images or consecutive frames of a video.
Source code will likely be released on GitHub in the future.