Advancing of personal protective equipment detection on construction sites with yolo-based deep learning architectures / (Record no. 177158)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04793namaa22004331i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | EG-GICUC |
| 005 - أخر تعامل مع التسجيلة | |
| control field | 20251229141741.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 251229s2025 ua a|||frm||| 000 0 eng d |
| 040 ## - CATALOGING SOURCE | |
| Original cataloguing agency | EG-GICUC |
| Language of cataloging | eng |
| Transcribing agency | EG-GICUC |
| Modifying agency | EG-GICUC |
| Description conventions | rda |
| 041 0# - LANGUAGE CODE | |
| Language code of text/sound track or separate title | eng |
| Language code of summary or abstract | eng |
| -- | ara |
| 049 ## - Acquisition Source | |
| Acquisition Source | Deposit |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 624.17 |
| 092 ## - LOCALLY ASSIGNED DEWEY CALL NUMBER (OCLC) | |
| Classification number | 624.17 |
| Edition number | 21 |
| 097 ## - Degree | |
| Degree | M.Sc |
| 099 ## - LOCAL FREE-TEXT CALL NUMBER (OCLC) | |
| Local Call Number | Cai01.13.05.M.Sc.2025.Ab.C |
| 100 0# - MAIN ENTRY--PERSONAL NAME | |
| Authority record control number or standard number | Abdelrahman Mohamed Elessawy Elnaqieb, |
| Preparation | preparation. |
| 245 10 - TITLE STATEMENT | |
| Title | Advancing of personal protective equipment detection on construction sites with yolo-based deep learning architectures / |
| Statement of responsibility, etc. | by Abdelrahman Mohamed Elessawy Elnaqieb ; Supervisors Prof. Dr. Hesham Maged Osman, Prof. Dr. Omar Hossam Eldin El-Anwar. |
| 246 15 - VARYING FORM OF TITLE | |
| Title proper/short title | الكشف عن معدات الحمایة الشخصیة (PPE) في مواقع البناء بإستخدام هياكل التعلم العميق(YOLO) |
| 264 #0 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Date of production, publication, distribution, manufacture, or copyright notice | 2025. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 95 pages : |
| Other physical details | illustrations ; |
| Dimensions | 30 cm. + |
| Accompanying material | CD. |
| 336 ## - CONTENT TYPE | |
| Content type term | text |
| Source | rda content |
| 337 ## - MEDIA TYPE | |
| Media type term | Unmediated |
| Source | rdamedia |
| 338 ## - CARRIER TYPE | |
| Carrier type term | volume |
| Source | rdacarrier |
| 502 ## - DISSERTATION NOTE | |
| Dissertation note | Thesis (M.Sc)-Cairo University, 2025. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc. note | Bibliography: pages 86-95. |
| 520 #3 - SUMMARY, ETC. | |
| Summary, etc. | The construction industry remains one of the most hazardous globally, with high rates of accidents and fatalities, despite risk assessments. Personal protective equipment (PPE) is critical for mitigating workplace hazards, but ensuring compliance remains challenging on dynamic construction sites. Advances in computer vision and data analytics, particularly through deep learning, offer promising solutions to improve safety standards. This research introduces innovative models leveraging YOLO-v5 and YOLO-v8 architectures to enhance PPE compliance among construction workers. The models predict six critical categories: person, vest, and four helmet colors, validated using the CHV benchmark dataset and an original dataset from Egyptian construction sites. A comparative analysis of ten YOLO-v5 models and five YOLO-v8 models revealed that YOLO-v8m achieved the highest precision, with a mean average precision (mAP) of 92.30% and an F1 score of 0.89. These results represent a 6.64% improvement over the CHV dataset baseline. The integration of these models into a safety dashboard allows for real-time monitoring and enforcement of PPE compliance. This approach significantly enhances the ability to prevent accidents and improve safety outcomes in construction environments. |
| 520 #3 - SUMMARY, ETC. | |
| Summary, etc. | تركز هذه الدراسة على تعزيز سلامة مواقع البناء باستخدام تقنيات رؤية الكمبيوتر المتقدمة وخوارزميات التعلم العميق لمراقبة الامتثال لمعدات الحماية الشخصية (PPE). من خلال استخدام الشبكات العصبية الملتفة (CNNs) ومبادئ التعلم الانتقالي، تم تطوير نماذج تعتمد على معماريات YOLO-v5 وYOLO-v8 لاكتشاف ست فئات رئيسية: الشخص، السترة، وأربعة ألوان للخوذة. تم التحقق من هذه النماذج باستخدام مجموعة بيانات مرجعية عالية الجودة (CHV Dataset) لتقييم الأداء. أظهرت النتائج أن YOLO-v5x6 كان الأسرع في معالجة البيانات، بينما تميز YOLO-v8m في الدقة مع تحقيقه لدقة ملاحظة (mAP) بنسبة 92.30% ودرجة F1-Score بلغت 0.89. كما سجل النموذج YOLO-v8m تحسنًا بنسبة 6.64% في دقة الملاحظة مقارنة بالدراسات السابقة باستخدام نفس مجموعة البيانات. توفر النماذج المطورة إمكانية إنشاء لوحات معلومات للسلامة في مواقع البناء، مما يساهم في تقليل الحوادث والإصابات وتحسين ممارسات السلامة العام. |
| 530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE | |
| Issues CD | Issues also as CD. |
| 546 ## - LANGUAGE NOTE | |
| Text Language | Text in English and abstract in Arabic & English. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Structural Engineering |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | الهندسة الإنشائية |
| 653 #1 - INDEX TERM--UNCONTROLLED | |
| Uncontrolled term | Construction safety |
| -- | PPE detection |
| -- | deep learnin |
| -- | Computer vision |
| -- | mAP score |
| -- | You Only Look Once (YOLO) |
| -- | سلامة البناء |
| -- | الكشف عن معدات الوقاية الشخصية |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Hesham Maged Osman |
| Relator term | thesis advisor. |
| 700 0# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Omar Hossam Eldin El-Anwar |
| Relator term | thesis advisor. |
| 900 ## - Thesis Information | |
| Grant date | 01-01-2025 |
| Supervisory body | Hesham Maged Osman |
| -- | Omar Hossam Eldin El-Anwar |
| Discussion body | Mona Metwally Abouhamad |
| -- | Ahmed Hussien Elyamany |
| Universities | Cairo University |
| Faculties | Faculty of Engineering |
| Department | Department of Structural Engineering |
| 905 ## - Cataloger and Reviser Names | |
| Cataloger Name | Shimaa |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Thesis |
| Edition | 21 |
| Suppress in OPAC | No |
| Source of classification or shelving scheme | Home library | Current library | Date acquired | Inventory number | Full call number | Barcode | Date last seen | Effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | المكتبة المركزبة الجديدة - جامعة القاهرة | قاعة الرسائل الجامعية - الدور الاول | 29.12.2025 | 92975 | Cai01.13.05.M.Sc.2025.Ab.C | 010101100092975000 | 29.12.2025 | 29.12.2025 | Thesis |