[Đồ án] Dự án nghiên cứu phát triển hệ thống quản lý bãi đỗ xe thông minh sử dụng thị giác máy tính và trí tuệ nhân tạo - TG.D. A. K. S. M.
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- 47
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- EN
- 年份
- 2025
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- Sri Lanka Institute of Information Technology
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- 文档名称
- [Đồ án] Dự án nghiên cứu phát triển hệ thống quản lý bãi đỗ xe thông minh sử dụng thị giác máy tính và trí tuệ nhân tạo - TG.D. A. K. S. M.
- 学校 / 课程
- Sri Lanka Institute of Information Technology · Artificial Intelligence
- 作者(文档中)
- D. A. K. S. M. DORANEGODA
- 内容
- Báo cáo này đề xuất một hệ thống quản lý bãi đỗ xe thông minh sử dụng AI và thị giác máy tính để tối ưu hóa việc sử dụng chỗ trống, quản lý vi phạm và áp dụng định giá động. Hệ thống nhằm giảm ùn tắc giao thông và tăng doanh thu.
- 目录
- Table of Contents DECLARATION
- ABSTRACT
- ACKNOWLEDGEMENT
- LIST OF FIGURES
- LIST OF TABLES
- LIST OF ABBREVIATION
- 1. INTRODUCTION
- 1.1 Background
- 1.2 Literature Survey
- 1.3 Research Gap
- 1.4 Research Problem
- 1.5 Research Objectives
- 2. METHODOLOGY
- 2.1. Materials and Methods
- 2.2 Component System Architecture (Solution Design)
- 2.3 Hardware Implementation
- 2.4 Number Plate Recognition and Data Management
- 2.5 Empty Parking Space Detection via Pixel-Based Analysis
- 2.6 Automated Gate Control
- 2.7 Implementation of Dynamic Pricing and Billing System
- 2.8 Development of Administrative Panel
- 2.9 System Validation and Testing
- 2.10 Commercialization Aspects of The Product
- 2.11 Implementation
- 2.12 Testing
- 2.13 Test Plan and Strategy
- 3. RESULTS AND DISCUSSION
- 3.1 Results
- 3.2 Product Development
- 3.3 Research Findings
- 3.4 Discussion
- 4. CONCLUSION
- 5. REFERENCES
- 6. APPENDICES
- 6. Figure 1: Vehicle sales
- Figure 2 : overall System Diagram
- Figure 3 : Component System Architecture (Solution Design)
- Figure 4 : Servo Motor
- Figure 5 : Esp 32 with Camera module
- Figure 6 : IR sensor
- Figure 7 : ANPR System
- Figure 8 : Number Plate Dataset
- Figure 9 : Frame Pre-processing and Image Enhancement
- Figure 10 : Occupancy Classification and Visual Feedback
- Figure 11 : Dashboard Page
- Figure 12 : ANPR Detection
- Figure 13 : Billing Dashboard
- Table 1:Characteristics of Existing Research Literature and the Proposed System
- Table 2 : Unit Testing
- Table 3 : Integration Testing
- Table 4 : Functional Testing
- Table 5 : Performance Testing
- Table 6: UAT Testing
- Table 7 : ANPR System Accuracy
- Table 8 : Gate control Performance
- Table 9 : Parking Slot Accuracy
- 页数
- 47 页
- 上传者
- Nguyen Le Giang
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描述
IT4010 Research Project 4th Year, 1st Semester Final Report Project ID: 24-25J-319 IT21187032 D. A. K. S. M. DORANEGODA B.Sc. (Hons) Degree in Information Technology Sri Lanka Institute of Information Technology April 2025 DECLARATION We declare that this is our own work, and this proposal does not incorporate without acknowledgement any material previously submitted for a degree or diploma in any other university or Institute of higher learning and to the best of our knowledge and belief it does not contain any material previously published or written by another person except where the acknowledgement is made in the text. Name Student ID D. A. K. S. M. DORANEGODA IT21187032 Signature The above candidate is carrying out research for the undergraduate Dissertation under our supervision. …………………………………….. Ms. Wishalya Tissera (Supervisor) 2 ABSTRACT Intensive urbanization has profoundly accentuated problems related to parking management in densely populated urban environments. Traffic congestion, wasteful use of parking places, unlawful or inconsiderate parking, and poor revenue realization have become urban mobility and economic efficiency issues critically in need of urgent resolution. This research project suggests developing an advanced, comprehensive parking management system based on state-of-the-art computer vision and artificial intelligence technologies. The system involves using state-of-the-art real-time image analysis to detect and track empty parking bays accurately, maximizing use of available space and reducing the idle time spent searching for parking. In addition, through constant monitoring of parking trends, the system anticipates recurring choke points and provides automatic alerts to respond to improper or unauthorized parking in real time. A new timing mechanism embedded in the system monitors parking times accurately, allowing for real-time demand-based pricing models influenced by occupancy, time of day, and peak hours. This new bi
[Đồ án] Dự án nghiên cứu phát triển hệ thống quản lý bãi đỗ xe thông minh sử dụng thị giác máy tính và trí tuệ nhân tạo - TG.D. A. K. S. M.
正在生成预览...
IT4010 Research Project 4th Year, 1st Semester Final Report Project ID: 24-25J-319 IT21187032 D. A. K. S. M. DORANEGODA B.Sc. (Hons) Degree in Information Technology Sri Lanka Institute of Information Technology April 2025 DECLARATION We declare that this is our own work, and this proposal does not incorporate without acknowledgement any material previously submitted for a degree or diploma in any other university or Institute of higher learning and to the best of our knowledge and belief it does not contain any material previously published or written by another person except where the acknowledgement is made in the text. Name Student ID D. A. K. S. M. DORANEGODA IT21187032 Signature The above candidate is carrying out research for the undergraduate Dissertation under our supervision. …………………………………….. Ms. Wishalya Tissera (Supervisor) 2 ABSTRACT Intensive urbanization has profoundly accentuated problems related to parking management in densely populated urban environments. Traffic congestion, wasteful use of parking places, unlawful or inconsiderate parking, and poor revenue realization have become urban mobility and economic efficiency issues critically in need of urgent resolution. This research project suggests developing an advanced, comprehensive parking management system based on state-of-the-art computer vision and artificial intelligence technologies. The system involves using state-of-the-art real-time image analysis to detect and track empty parking bays accurately, maximizing use of available space and reducing the idle time spent searching for parking. In addition, through constant monitoring of parking trends, the system anticipates recurring choke points and provides automatic alerts to respond to improper or unauthorized parking in real time. A new timing mechanism embedded in the system monitors parking times accurately, allowing for real-time demand-based pricing models influenced by occupancy, time of day, and peak hours. This new bi
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- 文档名称
- [Đồ án] Dự án nghiên cứu phát triển hệ thống quản lý bãi đỗ xe thông minh sử dụng thị giác máy tính và trí tuệ nhân tạo - TG.D. A. K. S. M.
- 学校 / 课程
- Sri Lanka Institute of Information Technology · Artificial Intelligence
- 作者(文档中)
- D. A. K. S. M. DORANEGODA
- 内容
- Báo cáo này đề xuất một hệ thống quản lý bãi đỗ xe thông minh sử dụng AI và thị giác máy tính để tối ưu hóa việc sử dụng chỗ trống, quản lý vi phạm và áp dụng định giá động. Hệ thống nhằm giảm ùn tắc giao thông và tăng doanh thu.
- 目录
- Table of Contents DECLARATION
- ABSTRACT
- ACKNOWLEDGEMENT
- LIST OF FIGURES
- LIST OF TABLES
- LIST OF ABBREVIATION
- 1. INTRODUCTION
- 1.1 Background
- 1.2 Literature Survey
- 1.3 Research Gap
- 1.4 Research Problem
- 1.5 Research Objectives
- 2. METHODOLOGY
- 2.1. Materials and Methods
- 2.2 Component System Architecture (Solution Design)
- 2.3 Hardware Implementation
- 2.4 Number Plate Recognition and Data Management
- 2.5 Empty Parking Space Detection via Pixel-Based Analysis
- 2.6 Automated Gate Control
- 2.7 Implementation of Dynamic Pricing and Billing System
- 2.8 Development of Administrative Panel
- 2.9 System Validation and Testing
- 2.10 Commercialization Aspects of The Product
- 2.11 Implementation
- 2.12 Testing
- 2.13 Test Plan and Strategy
- 3. RESULTS AND DISCUSSION
- 3.1 Results
- 3.2 Product Development
- 3.3 Research Findings
- 3.4 Discussion
- 4. CONCLUSION
- 5. REFERENCES
- 6. APPENDICES
- 6. Figure 1: Vehicle sales
- Figure 2 : overall System Diagram
- Figure 3 : Component System Architecture (Solution Design)
- Figure 4 : Servo Motor
- Figure 5 : Esp 32 with Camera module
- Figure 6 : IR sensor
- Figure 7 : ANPR System
- Figure 8 : Number Plate Dataset
- Figure 9 : Frame Pre-processing and Image Enhancement
- Figure 10 : Occupancy Classification and Visual Feedback
- Figure 11 : Dashboard Page
- Figure 12 : ANPR Detection
- Figure 13 : Billing Dashboard
- Table 1:Characteristics of Existing Research Literature and the Proposed System
- Table 2 : Unit Testing
- Table 3 : Integration Testing
- Table 4 : Functional Testing
- Table 5 : Performance Testing
- Table 6: UAT Testing
- Table 7 : ANPR System Accuracy
- Table 8 : Gate control Performance
- Table 9 : Parking Slot Accuracy
- 页数
- 47 页
- 上传者
- Nguyen Le Giang
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