A Dynamic Architecture to Control Multi-Rotors Using Hand Gestures
Journal Title: International Journal of Innovations in Science and Technology - Year 2024, Vol 6, Issue 3
Abstract
Traditional methods for controlling multi-rotors typically involve joysticks, radio controllers, and mobile applications. However, these methods pose significant challenges, particularly for novice users like farmers, due to the extensive training and understanding required to effectively operate a copter. This paper introduces a highly adaptable architecture designed to offer an end-to-end solution for controlling a copter using hand gestures. The proposed system leverages a depth sensor and Convolutional Neural Network (CNN) to recognize hand gestures, utilizing a custom dataset collected from both indoor and outdoor environments. Through a series of simulations with novice users, the system has demonstrated successful operation in real-world scenarios. Currently, the architecture can accurately recognize six distinct gestures with an average accuracy of 90.5% across three different test environments with varying lighting conditions. Key features of this proposed solution include its adaptability, reliable performance, especially in low-light conditions, and its user-friendly design, making it particularly well-suited for farmers and other inexperienced users.
Authors and Affiliations
Nabeel Hussain, Hassan Yousuf, Syed Atif Mehdi, Kanwal Atif
Keywords
Related Articles
- EP ID EP760435
- DOI -
- Views 32
- Downloads 0
Optimizing UAV Wing Performance: A Computational Analysis with Computer-Based Algorithms for Composite Material Integration
Introduction/Importance of Study: The aircraft wing, a vital component, demands intricate design to balance lift generation, drag reduction, and weight minimization. In advanced UAVs (Unmanned Aerial Vehicles), priorit...
Enhancing Open-Source Projects: The Synergy Between Code Readability Metrics and User Experience
Introduction /Importance of Study: The open-source project is a key driver of innovation in the so-called open ecosystem. However, the readability of code is still a major obstacle in having users successfully engaged...
Codebook-Based Feature Engineering for Human Activity Recognition Using Multimodal Sensory Data
Recently, Human Activity Recognition (HAR) using sensory data from various devices has become increasingly vital in fields like healthcare, elderly care, and smart home systems. However, many existing HAR systems face...
Developing an Arabic-Urdu Ontology of Quranic Concepts: A Semantic Approach
An Arabic-Urdu ontology system dedicated to Quranic concepts represents a necessity for protecting the semantic value and making religious texts more accessible during Quranic study. Ontology-driven annotation tools sh...
Deep Learning Based Multi Crop Disease Detection System
This research explores the integration of deep learning, computer vision, and edge computing to revolutionize crop disease detection. In response to the pressing need for prompt and accurate disease identification, thi...