Technology peripherals
AI
Applications in Drone Technology: The Important Role of Computer Vision
Applications in Drone Technology: The Important Role of Computer Vision
Computer vision technology is widely used in drones
These use cases enable businesses to use drones for several purposes.
Over the past few years, drones have become increasingly popular in various fields including retail delivery, videography, real estate photography, and land surveying. According to a study, the commercial drone market is expected to grow further in the coming years. Therefore, the application fields of drones will only increase in the future. Computer vision is an integral part of drones, also known as unmanned aerial vehicles (UAV). Here are some important use cases for computer vision in drones that allow enterprises to use drones for a wide range of applications:
1. Real-time object and person recognition
Businesses can use drones to Personnel recognition is performed by humans and machines, thereby increasing safety. This computer vision application automatically simplifies security analysis and scanning of individuals as they enter a classified facility. In this way, drones can assist security personnel in large organizations where, at any given time, several people are entering or leaving the facility. Applications of computer vision-driven person recognition can also be used for crowd management in smart cities. Object recognition, on the other hand, allows smart city administrators or businesses to monitor vehicles. Therefore, traffic monitoring is simplified through computer vision in UAV systems.
In law enforcement, both object recognition and person recognition are widely used. This allows police agencies to track incidents such as stolen cars in desolate areas where there are no security cameras or when chasing fugitives. Generally speaking, CCTV cameras in smart cities have the function of identifying objects and people
2. Avoiding collisions
When drones fly in designated areas, they can easily collide with birds. Classes, cables, high-rise buildings or other drones collide. Such a conflict could cause serious damage to the drone and negatively impact its functionality. Dynamic object recognition on drones can detect rapidly approaching objects or determine if a collision with a stationary object is imminent. In this case, the drone can automatically change direction or altitude to avoid a collision. Computer vision is the main technology driving this detection and response mechanism of drones
3. Violence detection
Artificial intelligence and computer vision in drones can help by simplifying the captured video footage Real-time analysis to realize the automation of smart city security monitoring. A team of researchers in the UK and India have collaborated to develop a quadcopter that can capture and transmit video footage for law enforcement surveillance. Such a system could be configured to conduct behavioral analysis of crowds in smart cities. Machine learning algorithms can predict violent behavior by individuals or groups in smart city areas. Once such behavior is detected, drones can instruct nearby law enforcement to dispatch troops and control the situation. As with any type of surveillance, businesses and governments need to ensure that the way they use drones does not violate privacy.
Reworded: Now, one might think that smart cities already contain several CCTV cameras and sensors to capture visual data. Why is it necessary to use drones? First, drones are mobile, allowing them to silently enter areas beyond the reach of static cameras. Additionally, drones can cover areas with low network coverage or lack of cabling infrastructure. Therefore, drones offer more solutions to smart city authorities and businesses. As mentioned earlier, computer vision is at the core of all drone operations. Therefore, it is certain that computer vision applications in drones will further increase in the foreseeable future
The above is the detailed content of Applications in Drone Technology: The Important Role of Computer Vision. For more information, please follow other related articles on the PHP Chinese website!
Hot AI Tools
Undresser.AI Undress
AI-powered app for creating realistic nude photos
AI Clothes Remover
Online AI tool for removing clothes from photos.
Undress AI Tool
Undress images for free
Clothoff.io
AI clothes remover
Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!
Hot Article
Hot Tools
Notepad++7.3.1
Easy-to-use and free code editor
SublimeText3 Chinese version
Chinese version, very easy to use
Zend Studio 13.0.1
Powerful PHP integrated development environment
Dreamweaver CS6
Visual web development tools
SublimeText3 Mac version
God-level code editing software (SublimeText3)
Hot Topics
1386
52
2024 DJI drone rankings: Each model has sales of 50,000+, which one have you used?
Dec 16, 2023 pm 05:33 PM
Hello, hello! I am Yuan Haha, please pay attention, more exciting content is waiting for you. With the continuous advancement of drone technology, we can now buy one of the most important and reliable 4K cameras within a budget of several thousand yuan. This is how many times Unimaginable years ago. With the continuous efforts of DJI, Autel and other companies, this dream has become a reality. The overall drone of choice is DJI Mavic 3 Pro. This drone not only provides ultra-high definition recording, but also has excellent frame rates and long-lasting battery. life. In addition to my personal experience, I’ve compiled some other top drones for you to choose from based on positive reviews around the web. Now, let’s take a look at these exciting options. Best Drone Overall: DJIMavic 3Pr
Drone swarms: A game-changing technology for defense applications
Nov 14, 2023 pm 08:53 PM
Abstract: Swarming is a disruptive, game-changing technology that involves the collaborative deployment of multiple unmanned systems in multiple domains (land, sea, air, space). Developments in new microelectronics, guidance, navigation, sensors and artificial intelligence technologies enable low-cost micro-drones to perform challenging missions. When combined with novel decision-making processes, target tracking, communications technologies and algorithms, swarms can have a huge impact on the battlefield. It can also be used to provide continuous and undetectable surveillance capabilities as well as critical defense capabilities, such as intercepting cruise missiles. This article describes European research activities in the field of swarming and delves into the significant implications it may have for defence. Keywords: UAV, autonomous capability, target tracking,
The largest domestically produced unmanned transport aircraft successfully made its maiden flight: equipped with China Aviation Engineering Group's AEP100-A engine
Aug 23, 2024 am 07:32 AM
According to news from this website on August 22, China Aviation Engine Group Co., Ltd. issued an official announcement today. At 6:28 today, the 900-kilowatt turboprop engine AEP100-A, which was completely independently developed by China Aviation Industry Corporation, powered the SA750U large unmanned transport aircraft in Shaanxi. Successful first flight. According to reports, the AEP100-A turboprop engine was designed by the China Aerospace Engineering Research Institute and manufactured in the South. It has the ability to adapt to high temperatures and plateaus. It uses three-dimensional aerodynamic design and unit design technology to provide power for aircraft while improving fuel economy. Improve overall aircraft operating efficiency. The AEP100 turboprop engine series can be equipped with 2 to 6 ton general-purpose aircraft or 3 to 10 ton unmanned aerial vehicles, and its comprehensive performance has reached the international advanced level of the same level currently in service. This site reported earlier
The difference between single-stage and dual-stage target detection algorithms
Jan 23, 2024 pm 01:48 PM
Object detection is an important task in the field of computer vision, used to identify objects in images or videos and locate their locations. This task is usually divided into two categories of algorithms, single-stage and two-stage, which differ in terms of accuracy and robustness. Single-stage target detection algorithm The single-stage target detection algorithm converts target detection into a classification problem. Its advantage is that it is fast and can complete the detection in just one step. However, due to oversimplification, the accuracy is usually not as good as the two-stage object detection algorithm. Common single-stage target detection algorithms include YOLO, SSD and FasterR-CNN. These algorithms generally take the entire image as input and run a classifier to identify the target object. Unlike traditional two-stage target detection algorithms, they do not need to define areas in advance, but directly predict
Application of AI technology in image super-resolution reconstruction
Jan 23, 2024 am 08:06 AM
Super-resolution image reconstruction is the process of generating high-resolution images from low-resolution images using deep learning techniques, such as convolutional neural networks (CNN) and generative adversarial networks (GAN). The goal of this method is to improve the quality and detail of images by converting low-resolution images into high-resolution images. This technology has wide applications in many fields, such as medical imaging, surveillance cameras, satellite images, etc. Through super-resolution image reconstruction, we can obtain clearer and more detailed images, which helps to more accurately analyze and identify targets and features in images. Reconstruction methods Super-resolution image reconstruction methods can generally be divided into two categories: interpolation-based methods and deep learning-based methods. 1) Interpolation-based method Super-resolution image reconstruction based on interpolation
How to use AI technology to restore old photos (with examples and code analysis)
Jan 24, 2024 pm 09:57 PM
Old photo restoration is a method of using artificial intelligence technology to repair, enhance and improve old photos. Using computer vision and machine learning algorithms, the technology can automatically identify and repair damage and flaws in old photos, making them look clearer, more natural and more realistic. The technical principles of old photo restoration mainly include the following aspects: 1. Image denoising and enhancement. When restoring old photos, they need to be denoised and enhanced first. Image processing algorithms and filters, such as mean filtering, Gaussian filtering, bilateral filtering, etc., can be used to solve noise and color spots problems, thereby improving the quality of photos. 2. Image restoration and repair In old photos, there may be some defects and damage, such as scratches, cracks, fading, etc. These problems can be solved by image restoration and repair algorithms
Scale Invariant Features (SIFT) algorithm
Jan 22, 2024 pm 05:09 PM
The Scale Invariant Feature Transform (SIFT) algorithm is a feature extraction algorithm used in the fields of image processing and computer vision. This algorithm was proposed in 1999 to improve object recognition and matching performance in computer vision systems. The SIFT algorithm is robust and accurate and is widely used in image recognition, three-dimensional reconstruction, target detection, video tracking and other fields. It achieves scale invariance by detecting key points in multiple scale spaces and extracting local feature descriptors around the key points. The main steps of the SIFT algorithm include scale space construction, key point detection, key point positioning, direction assignment and feature descriptor generation. Through these steps, the SIFT algorithm can extract robust and unique features, thereby achieving efficient image processing.
An introduction to image annotation methods and common application scenarios
Jan 22, 2024 pm 07:57 PM
In the fields of machine learning and computer vision, image annotation is the process of applying human annotations to image data sets. Image annotation methods can be mainly divided into two categories: manual annotation and automatic annotation. Manual annotation means that human annotators annotate images through manual operations. This method requires human annotators to have professional knowledge and experience and be able to accurately identify and annotate target objects, scenes, or features in images. The advantage of manual annotation is that the annotation results are reliable and accurate, but the disadvantage is that it is time-consuming and costly. Automatic annotation refers to the method of using computer programs to automatically annotate images. This method uses machine learning and computer vision technology to achieve automatic annotation by training models. The advantages of automatic labeling are fast speed and low cost, but the disadvantage is that the labeling results may not be accurate.
