{"title":"Instant Counting & Vehicle Detection during Hajj Using Drones","authors":"Abdullah M. Algamdi, Hammam M. AlGhamdi","doi":"10.18178/joig.11.2.204-211","DOIUrl":null,"url":null,"abstract":"During the past decade, artificial intelligence technologies, especially Computer Vision (CV) technologies, have experienced significant breakthroughs due to the development of deep learning models, particularly Convolutional Neural Networks (CNNs). These networks have been utilized in various research applications, including astronomy, marine sciences, security, medicine, and pathology. In this paper, we build a framework utilizing CV technology to support decision-makers during the Hajj season. We collect and process real-time/instant images from multiple aircraft/drones, which follow the pilgrims while they move around the holy sites during Hajj. These images, taken by multiple drones, are processed in two stages. First, we purify the images collected from multiple drones and stitch them, producing one image that captures the whole holy site. Second, the stitched image is processed using a CNN to provide two pieces of information: (1) the number of buses and ambulances; and (2) the estimated count of pilgrims. This information could help decision-makers identify needs for further support during Hajj, such as logistics services, security personnel, and/or ambulances.","PeriodicalId":36336,"journal":{"name":"中国图象图形学报","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"中国图象图形学报","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.18178/joig.11.2.204-211","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0
Abstract
During the past decade, artificial intelligence technologies, especially Computer Vision (CV) technologies, have experienced significant breakthroughs due to the development of deep learning models, particularly Convolutional Neural Networks (CNNs). These networks have been utilized in various research applications, including astronomy, marine sciences, security, medicine, and pathology. In this paper, we build a framework utilizing CV technology to support decision-makers during the Hajj season. We collect and process real-time/instant images from multiple aircraft/drones, which follow the pilgrims while they move around the holy sites during Hajj. These images, taken by multiple drones, are processed in two stages. First, we purify the images collected from multiple drones and stitch them, producing one image that captures the whole holy site. Second, the stitched image is processed using a CNN to provide two pieces of information: (1) the number of buses and ambulances; and (2) the estimated count of pilgrims. This information could help decision-makers identify needs for further support during Hajj, such as logistics services, security personnel, and/or ambulances.
中国图象图形学报Computer Science-Computer Graphics and Computer-Aided Design
CiteScore
1.20
自引率
0.00%
发文量
6776
期刊介绍:
Journal of Image and Graphics (ISSN 1006-8961, CN 11-3758/TB, CODEN ZTTXFZ) is an authoritative academic journal supervised by the Chinese Academy of Sciences and co-sponsored by the Institute of Space and Astronautical Information Innovation of the Chinese Academy of Sciences (ISIAS), the Chinese Society of Image and Graphics (CSIG), and the Beijing Institute of Applied Physics and Computational Mathematics (BIAPM). The journal integrates high-tech theories, technical methods and industrialisation of applied research results in computer image graphics, and mainly publishes innovative and high-level scientific research papers on basic and applied research in image graphics science and its closely related fields. The form of papers includes reviews, technical reports, project progress, academic news, new technology reviews, new product introduction and industrialisation research. The content covers a wide range of fields such as image analysis and recognition, image understanding and computer vision, computer graphics, virtual reality and augmented reality, system simulation, animation, etc., and theme columns are opened according to the research hotspots and cutting-edge topics.
Journal of Image and Graphics reaches a wide range of readers, including scientific and technical personnel, enterprise supervisors, and postgraduates and college students of colleges and universities engaged in the fields of national defence, military, aviation, aerospace, communications, electronics, automotive, agriculture, meteorology, environmental protection, remote sensing, mapping, oil field, construction, transportation, finance, telecommunications, education, medical care, film and television, and art.
Journal of Image and Graphics is included in many important domestic and international scientific literature database systems, including EBSCO database in the United States, JST database in Japan, Scopus database in the Netherlands, China Science and Technology Thesis Statistics and Analysis (Annual Research Report), China Science Citation Database (CSCD), China Academic Journal Network Publishing Database (CAJD), and China Academic Journal Network Publishing Database (CAJD). China Science Citation Database (CSCD), China Academic Journals Network Publishing Database (CAJD), China Academic Journal Abstracts, Chinese Science Abstracts (Series A), China Electronic Science Abstracts, Chinese Core Journals Abstracts, Chinese Academic Journals on CD-ROM, and China Academic Journals Comprehensive Evaluation Database.