Pat Tshibang's repositories
YOLOv8-Fall-detection
Training YOLOv8 on Falling Dataset to Enable Real-Time Fall Detection
AI-Based-Marine-Vessel-Firefighter-Safety-System
his project aims to enhance firefighter safety during marine vessel fire accidents. The system utilizes a neural network (NN) to detect distressed firefighters within the vessel. When a firefighter’s condition deteriorates, the AI triggers evacuation protocols, guiding them to safety zones
CNN-Grimace-detection
This repository enables grimace expression detection in images and videos using a trained Convolutional Neural Network (CNN) model. It includes a pre-trained model and code for seamless integration.
DC-Motor-Control-with-Relays
This repository contains code and circuit diagrams for controlling a 5V DC motor using two SRD-05 relays with an Arduino board. Achieve clockwise and counterclockwise rotation with ease using this simple yet effective setup
Smart-Ultrasonic-Water-Level-Monitoring-System
This project implements a smart water level monitoring system using an ultrasonic sensor. It accurately measures the water level in a tank and displays the information on an LCD screen. The system is powered by an Arduino microcontroller and is designed for easy installation and operation.
STEPPER-MOTOR-RUNNING-BY-BLUETOOTH
This project involves controlling a stepper motor wirelessly via Bluetooth communication. By utilizing Bluetooth technology, users can remotely operate the stepper motor, enabling various applications such as robotics, automation, and remote-controlled devices
YOLOv8-Available-storage
This repository contains code for object detection using YOLOv8 to detect available storage space. It uses deep learning techniques to identify and localize areas where storage space is available in images or video streams. This can be useful for various applications such as inventory management, parking space detection, and more
YOLOv8-Fire-detection
This repository contains code and resources for detecting fires using the YOLOv8 object detection model. The model is trained on annotated fire images and can accurately detect fires in real-time video streams or images
YOLOv8-Object-detection
Object detection with YOLOv8