NCAA Digital Transformation - Gate Inspection Module — Software Requirements Specification (SRS)
Table of Contents
- 1 Document Information
- 2 Project Overview
- 3 User Requirements
- 4 Technical Requirements
- 5 External Dependencies
- 6 Release Planning
- 7 Risks Assumptions
- 8 Market Specific Considerations
- 9 Sign Off
- 10 Detailed Feature Requirements
- 10.1 Ft Insp Detect Auto
- 10.2 Ft Insp Detect Classify
- 10.3 Ft Insp Detect Plate
- 10.4 Ft Insp Detect Trailer
- 10.5 Ft Insp Cam Adjustable
- 10.6 Ft Insp Cam Angles
- 10.7 Ft Insp Cam Quality
- 10.8 Ft Insp Cam Archive
- 10.9 Ft Insp Cred Permit
- 10.10 Ft Insp Cred Driver
- 10.11 Ft Insp Cred Commercial
- 10.12 Ft Insp Cred Blacklist
- 10.13 Ft Insp Int Logging
- 10.14 Ft Insp Int Permit
- 10.15 Ft Insp Int Capacity
- 10.16 Ft Insp Ui Dashboard
- 10.17 Ft Insp Ui Override
- 10.18 Ft Insp Ui Alert
- 10.19 Ft Insp Ui History
- 10.20 Ft Insp Manual Entry
- 10.21 Ft Insp Manual Photo
- 10.22 Ft Insp Report Daily
- 10.23 Ft Insp Report Audit
- 11 Additional Context
1 Document Information
| Field | Value |
|---|---|
| Project Name | NCAA Digital Transformation - Gate Inspection Module |
| Version | 1.0 |
| Date | 2025-11-06 |
| Project Manager | TBD |
| Tech Lead | TBD |
| Qa Lead | TBD |
| Platforms | ['Web', 'PWA', 'Desktop', 'Tablet'] |
| Document Status | Draft |
| Module Code | INSPECTION |
| Parent Project | NCAA Digital Transformation - Ngorongoro Gateway System |
2 Project Overview
2.1 What Are We Building
2.1.1 System Function
Automated vehicle inspection system using camera-based object detection to identify vehicles, verify credentials, and detect trailers. System integrates with gate operations to provide comprehensive vehicle tracking and credibility checks.
2.1.2 Users
- Gate Staff: Vehicle inspectors, Security personnel
- Management: Operations managers, Security managers
- System Operators: Technical staff monitoring camera systems
2.1.3 Problem Solved
Manual vehicle inspection is time-consuming and error-prone at gates handling 500+ cars/day (Seneto), lack of standardized inspection process, no automated vehicle detection, difficulty tracking vehicles with trailers, no vehicle credibility checks, narrow roads causing inspection bottlenecks
2.1.4 Key Success Metric
Automated vehicle detection in <5 seconds, 95% accuracy for vehicle type classification, trailer detection capability, vehicle credibility verification integrated with permit system, reduced inspection time from 2-3 minutes to <30 seconds per vehicle
2.2 Scope
2.2.1 In Scope
- Camera-based vehicle detection and classification
- License plate recognition (LPR)
- Vehicle type identification (car, jeep, bus, truck)
- Trailer detection using fine-tuned object detection models
- Adjustable camera system for varied vehicle heights
- Vehicle credibility verification against permit system
- Integration with vehicle logging module
- Image capture and archival for audit trail
- Real-time processing at gate locations
- Manual inspection fallback procedures
2.2.2 Out Of Scope
- Facial recognition for driver identification
- Automatic gate barrier control
- Weight measurement systems
- Cargo inspection systems
- Wildlife detection on vehicles
- Night vision capabilities (initial phase)
3 User Requirements
3.1 Vehicle Detection
| Feature Code | I Want To | So That I Can | Priority | Notes |
|---|---|---|---|---|
| FT-INSP-DETECT-AUTO | Automatically detect vehicles approaching the gate | Trigger inspection process without manual intervention | Must | Motion detection triggers camera. Processing <5 seconds. Works in daylight conditions. |
| FT-INSP-DETECT-CLASSIFY | Classify vehicle type automatically (car, jeep, bus, truck) | Verify vehicle matches permit and enforce appropriate regulations | Must | 95% accuracy target. Object detection model trained on safari vehicles. Manual override available. |
| FT-INSP-DETECT-PLATE | Recognize and extract license plate numbers | Automatically log vehicles and cross-reference with registration | Must | Tanzania plate format recognition. Fallback to manual entry if OCR fails. |
| FT-INSP-DETECT-TRAILER | Detect vehicles with trailers using fine-tuned object detection | Track additional equipment entering conservation area | Should | Model fine-tuning required per Nov 3 revision. Alert staff if trailer detected for additional verification. |
3.2 Camera System
| Feature Code | I Want To | So That I Can | Priority | Notes |
|---|---|---|---|---|
| FT-INSP-CAM-ADJUSTABLE | Use adjustable camera to capture vehicles of varied heights | Handle range from small cars to large safari buses | Must | Manual or automatic adjustment. Cover vehicle heights from 1.5m to 4m. Per Nov 3 revision feedback. |
| FT-INSP-CAM-ANGLES | Capture multiple angles of each vehicle (front, side) | Ensure complete vehicle documentation | Should | 2-3 camera setup at critical gates. Single camera minimum at remote gates. |
| FT-INSP-CAM-QUALITY | Ensure high-quality image capture in various lighting conditions | Maintain detection accuracy throughout the day | Must | HD resolution minimum (1080p). Auto-exposure adjustment. Weather-resistant housing. |
| FT-INSP-CAM-ARCHIVE | Archive vehicle images for audit and dispute resolution | Maintain complete visual record of all vehicles | Must | Stored on local NAS. 30-day retention minimum. Compressed storage to manage space. |
3.3 Credibility Verification
| Feature Code | I Want To | So That I Can | Priority | Notes |
|---|---|---|---|---|
| FT-INSP-CRED-PERMIT | Verify vehicle matches permit information | Detect permit fraud and unauthorized vehicles | Must | Cross-reference plate number with permit database. Alert if mismatch. Currently manual process at Seneto. |
| FT-INSP-CRED-DRIVER | Verify driver authorization for the vehicle | Ensure authorized operators only | Must | Driver license check. Safari guide license for commercial operators. Manual verification by staff. |
| FT-INSP-CRED-COMMERCIAL | Verify commercial operator licenses for safari vehicles | Enforce commercial operation regulations | Must | Operator license database. Expiry date checks. Alert if license expired or invalid. |
| FT-INSP-CRED-BLACKLIST | Check vehicle against blacklist of prohibited vehicles | Prevent entry of vehicles with violations history | Should | Blacklist management interface. Reason codes for blacklisting. Expiry dates for temporary bans. |
3.4 Integration
| Feature Code | I Want To | So That I Can | Priority | Notes |
|---|---|---|---|---|
| FT-INSP-INT-LOGGING | Automatically create vehicle log entry when inspection complete | Eliminate manual logging of 1000+ vehicles/day | Must | Integration with gate operations module. Timestamp, plate, type, image reference logged. |
| FT-INSP-INT-PERMIT | Link inspection results to permit verification system | Provide complete visitor-vehicle-permit validation | Must | Real-time lookup in permit database. Display permit status on inspection screen. |
| FT-INSP-INT-CAPACITY | Update capacity counts based on inspection results | Maintain accurate real-time capacity tracking | Must | Increment count on entry, decrement on exit. Vehicle type specific counts. |
3.5 Staff Interface
| Feature Code | I Want To | So That I Can | Priority | Notes |
|---|---|---|---|---|
| FT-INSP-UI-DASHBOARD | View real-time inspection dashboard showing camera feeds and detection results | Monitor inspection process and intervene when needed | Must | Live camera feed. Detection confidence scores. Manual override buttons. |
| FT-INSP-UI-OVERRIDE | Manually override automatic detection results | Correct errors and handle edge cases | Must | Edit vehicle type, plate number, trailer status. Reason required for override. Audit trail maintained. |
| FT-INSP-UI-ALERT | Receive visual and audio alerts for credibility issues | Take immediate action on vehicle violations | Must | Alert types: permit mismatch, blacklisted vehicle, expired license. Color-coded urgency levels. |
| FT-INSP-UI-HISTORY | View vehicle inspection history | Identify repeat visitors and track vehicle patterns | Should | Search by plate number or date range. Show all previous inspections with images. |
3.6 Manual Fallback
| Feature Code | I Want To | So That I Can | Priority | Notes |
|---|---|---|---|---|
| FT-INSP-MANUAL-ENTRY | Manually enter vehicle details when camera system unavailable | Maintain operations during technical issues | Must | Form-based entry interface. Same data fields as automated. Tablet-friendly for mobile inspection. |
| FT-INSP-MANUAL-PHOTO | Capture vehicle photos using tablet camera as backup | Maintain visual documentation even when fixed cameras fail | Should | Tablet camera integration. Manual photo upload. Sync to central archive when network available. |
3.7 Reporting
| Feature Code | I Want To | So That I Can | Priority | Notes |
|---|---|---|---|---|
| FT-INSP-REPORT-DAILY | Generate daily inspection reports with detection accuracy metrics | Monitor system performance and identify issues | Should | Total vehicles inspected, detection success rate, manual overrides, alerts triggered. |
| FT-INSP-REPORT-AUDIT | Generate audit reports showing all vehicle inspections with images | Support compliance and dispute resolution | Must | Filterable by date, gate, vehicle type. Export with images. PDF/Excel formats. |
4 Technical Requirements
4.1 Performance Standards
| Requirement | Target | How To Test |
|---|---|---|
| Vehicle detection time | < 5 seconds from trigger to result | Automated testing with 100 vehicle samples |
| License plate recognition accuracy | ≥ 90% accuracy | Test with 100 Tanzania plates in various conditions |
| Vehicle classification accuracy | ≥ 95% accuracy | Test with diverse vehicle types (cars, jeeps, buses, trucks) |
| Trailer detection accuracy | ≥ 85% accuracy | Test with vehicles with/without trailers after model fine-tuning |
| Camera feed latency | < 500ms | Network latency testing from camera to NUC |
4.2 Platform Requirements
| Platform | Minimum Version | Target Version | Notes |
|---|---|---|---|
| Object Detection Model | YOLOv5 / TensorFlow 2.8 | YOLOv8 / TensorFlow 2.13+ | GPU acceleration recommended but not required |
| Camera System | IP Camera 1080p, H.264 | IP Camera 4K, H.265, PoE | ONVIF compliant for compatibility |
| Processing | Intel NUC with Intel i5 | Intel NUC with Intel i7 or integrated GPU | Sufficient for real-time inference at gate volumes |
4.3 Security Privacy
| Requirement | Must Have | Implementation |
|---|---|---|
| Image encryption | True | AES-256 encryption for archived images on NAS |
| Access control for images | True | Role-based access. Audit log for image access. |
| Data retention policy | True | 30-day minimum retention, automatic archival to cold storage for longer retention |
5 External Dependencies
5.1 Third Party Services
| Service | What It Does | Criticality | Backup Plan |
|---|---|---|---|
| Object Detection Model (YOLO) | Vehicle and trailer detection | Critical | Manual inspection fallback |
| OCR Engine (Tesseract) | License plate text recognition | Critical | Manual plate entry |
5.2 Device Requirements
| Feature | Required | Optional | Notes |
|---|---|---|---|
| IP Camera (adjustable mount) | True | False | Weather-resistant, PoE powered, 1080p minimum, adjustable for vehicle heights per Nov 3 revision |
| Camera mounting hardware | True | False | Adjustable mount to cover varied vehicle heights (1.5m to 4m) |
| Network infrastructure | True | False | PoE switch for camera power, network cable to NUC |
6 Release Planning
6.1 Development Phases
| Phase | Features Included | Timeline | Success Criteria |
|---|---|---|---|
| Phase 1 (Model Training & Testing) | ['Train vehicle detection model on safari vehicles', 'Train trailer detection model', 'License plate OCR for Tanzania plates', 'Accuracy testing and fine-tuning'] | 8 weeks | ≥95% vehicle classification accuracy, ≥85% trailer detection accuracy, ≥90% plate recognition |
| Phase 2 (Pilot Deployment - 2 Gates) | ['Camera installation at Karatu and Seneto', 'Real-time detection integration', 'Staff interface', 'Manual fallback procedures'] | 6 weeks | System operational at 2 gates, <5 second detection time, staff trained and confident |
| Phase 3 (Full Deployment) | ['Camera installation at remaining critical gates', 'Integration with gate operations', 'Audit trail and reporting', 'Performance optimization'] | 8 weeks | All critical gates equipped, 90% of vehicles automatically inspected, staff workload reduced by 60% |
6.2 Release Checklist
- Vehicle detection model trained and tested (≥95% accuracy)
- Trailer detection fine-tuned per Nov 3 revision (≥85% accuracy)
- Camera hardware installed with adjustable mounts
- Integration with vehicle logging completed
- Staff training completed on inspection interface
- Manual fallback procedures documented and tested
- Image archival system operational with 30-day retention
- Performance benchmarks met (<5 second detection)
7 Risks Assumptions
7.1 Risks
| Risk | Probability | Impact | Mitigation |
|---|---|---|---|
| Model accuracy lower than expected in real-world conditions | Medium | High | Continuous model improvement, manual override capabilities, fallback to manual inspection |
| Camera visibility issues due to dust/weather in conservation area | High | Medium | Weather-resistant camera housing, regular cleaning schedule, manual fallback |
| Processing power insufficient for real-time detection | Low | High | Hardware specifications validated during pilot, GPU acceleration option, model optimization |
| Varied vehicle types not well represented in training data | Medium | Medium | Collect local vehicle images during pilot, continuous model retraining, manual corrections fed back to model |
7.2 Assumptions
- Vehicle detection models can achieve required accuracy with available training data
- Intel NUC processing power sufficient for real-time inference
- Camera placement locations available at all gates
- Network bandwidth sufficient for camera feeds
- Staff willing to trust and use automated system with manual oversight
- Adjustable camera mounts can cover full range of vehicle heights (per Nov 3 revision)
8 Market Specific Considerations
8.1 Primary Market
- Ngorongoro Conservation Area, Tanzania
8.2 Target Demographics
- Gate staff operating inspection systems
- Vehicle inspectors transitioning from manual to automated
8.3 Local Considerations
- Dusty environment requires rugged camera equipment
- High vehicle volumes during peak season (500+ cars/day at Seneto)
- Varied vehicle types from small cars to large safari buses
- Tanzania license plate formats and styles
- Safari vehicles often modified with roof hatches and racks
- Vehicles with trailers common for camping equipment (per Nov 3 revision)
8.4 Competition
- Manual inspection (current process)
9 Sign Off
9.1 Approval
| Role | Name | Signature | Date |
|---|---|---|---|
9.2 Document History
| Version | Date | Changes Made | Changed By |
|---|---|---|---|
| 1.0 | 2025-11-06 | Initial draft based on gate inspection architecture and Nov 3 revision feedback | Development Team |
10 Detailed Feature Requirements
10.1 Ft Insp Detect Auto
10.1.1 Priority
Must Have
10.1.2 User Story
As a gate inspector, I want vehicles to be automatically detected when approaching the gate so that the inspection process starts without manual intervention
10.1.3 Preconditions
Camera system operational; motion detection configured
10.1.4 Postconditions
Vehicle detected; inspection process triggered; detection time logged
10.1.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-DETECT-TC-001 | Detect approaching vehicle within 5 seconds | High |
| INSP-DETECT-TC-002 | Motion detection triggers camera capture | High |
| INSP-DETECT-TC-003 | Detection works in daylight conditions | High |
| INSP-DETECT-TC-004 | No false positives from pedestrians or animals | Medium |
10.2 Ft Insp Detect Classify
10.2.1 Priority
Must Have
10.2.2 User Story
As a gate inspector, I want vehicle type to be automatically classified so that I can verify it matches the permit
10.2.3 Preconditions
Vehicle detected; object detection model loaded
10.2.4 Postconditions
Vehicle type classified with confidence score; result displayed to staff
10.2.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-DETECT-TC-005 | Classify car with ≥95% accuracy | High |
| INSP-DETECT-TC-006 | Classify safari jeep with ≥95% accuracy | High |
| INSP-DETECT-TC-007 | Classify bus with ≥95% accuracy | High |
| INSP-DETECT-TC-008 | Classify truck with ≥95% accuracy | High |
| INSP-DETECT-TC-009 | Display confidence score to staff | Medium |
| INSP-DETECT-TC-010 | Allow manual override of classification | High |
10.3 Ft Insp Detect Plate
10.3.1 Priority
Must Have
10.3.2 User Story
As a gate inspector, I want license plate numbers to be automatically recognized so that vehicles are logged without manual entry
10.3.3 Preconditions
Vehicle image captured; OCR engine operational
10.3.4 Postconditions
Plate number extracted; cross-referenced with registration database
10.3.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-DETECT-TC-011 | Recognize Tanzania plate format | High |
| INSP-DETECT-TC-012 | Extract plate number with ≥90% accuracy | High |
| INSP-DETECT-TC-013 | Fallback to manual entry if OCR fails | High |
| INSP-DETECT-TC-014 | Cross-reference with vehicle registration | High |
10.4 Ft Insp Detect Trailer
10.4.1 Priority
Should Have
10.4.2 User Story
As a gate inspector, I want trailers to be automatically detected so that I can track additional equipment entering the area
10.4.3 Preconditions
Fine-tuned object detection model deployed; vehicle image captured
10.4.4 Postconditions
Trailer presence flagged; staff alerted for additional verification
10.4.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-DETECT-TC-015 | Detect trailer with ≥85% accuracy using fine-tuned model | Medium |
| INSP-DETECT-TC-016 | Alert staff when trailer detected | Medium |
| INSP-DETECT-TC-017 | Log trailer separately in vehicle record | Medium |
10.5 Ft Insp Cam Adjustable
10.5.1 Priority
Must Have
10.5.2 User Story
As a gate inspector, I want the camera to adjust for vehicles of varied heights so that all vehicles can be properly captured
10.5.3 Preconditions
Adjustable camera mount installed; height range 1.5m to 4m
10.5.4 Postconditions
Camera position adjusted; clear vehicle image captured
10.5.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-CAM-TC-001 | Capture small car (1.5m height) clearly | High |
| INSP-CAM-TC-002 | Capture safari bus (4m height) clearly | High |
| INSP-CAM-TC-003 | Manual camera adjustment option available | High |
| INSP-CAM-TC-004 | Auto-adjustment based on vehicle detection | Medium |
10.6 Ft Insp Cam Angles
10.6.1 Priority
Should Have
10.6.2 User Story
As a gate inspector, I want multiple camera angles of each vehicle so that complete documentation is captured
10.6.3 Preconditions
2-3 cameras installed at gate; cameras synchronized
10.6.4 Postconditions
Front and side images captured; all images archived
10.6.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-CAM-TC-005 | Capture front view of vehicle | Medium |
| INSP-CAM-TC-006 | Capture side view of vehicle | Medium |
| INSP-CAM-TC-007 | Synchronize capture across all cameras | Medium |
10.7 Ft Insp Cam Quality
10.7.1 Priority
Must Have
10.7.2 User Story
As a gate inspector, I want high-quality images in various lighting conditions so that detection accuracy is maintained
10.7.3 Preconditions
HD camera (1080p minimum); auto-exposure configured
10.7.4 Postconditions
Clear image captured; adequate for OCR and object detection
10.7.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-CAM-TC-008 | Capture 1080p HD images | High |
| INSP-CAM-TC-009 | Auto-exposure adjustment in bright sunlight | High |
| INSP-CAM-TC-010 | Maintain quality in cloudy conditions | Medium |
| INSP-CAM-TC-011 | Weather-resistant housing protects camera | High |
10.8 Ft Insp Cam Archive
10.8.1 Priority
Must Have
10.8.2 User Story
As a manager, I want vehicle images archived for audit and dispute resolution so that complete visual records are maintained
10.8.3 Preconditions
NAS storage operational; sufficient storage capacity
10.8.4 Postconditions
Images stored with compression; 30-day retention enforced
10.8.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-CAM-TC-012 | Archive image to local NAS | High |
| INSP-CAM-TC-013 | Compress images to manage storage space | High |
| INSP-CAM-TC-014 | Enforce 30-day minimum retention | High |
| INSP-CAM-TC-015 | Automatic cleanup of images older than retention period | Medium |
10.9 Ft Insp Cred Permit
10.9.1 Priority
Must Have
10.9.2 User Story
As a gate inspector, I want to verify the vehicle matches permit information so that I can detect fraud
10.9.3 Preconditions
Plate number extracted; permit database accessible
10.9.4 Postconditions
Permit verified; mismatch alerted to staff
10.9.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-CRED-TC-001 | Cross-reference plate with permit database | High |
| INSP-CRED-TC-002 | Alert if plate mismatch with permit | High |
| INSP-CRED-TC-003 | Display permit details on inspection screen | High |
| INSP-CRED-TC-004 | Work offline with locally synced permit data | High |
10.10 Ft Insp Cred Driver
10.10.1 Priority
Must Have
10.10.2 User Story
As a gate inspector, I want to verify driver authorization so that only authorized operators are allowed
10.10.3 Preconditions
Driver license presented; verification system accessible
10.10.4 Postconditions
Driver authorization confirmed or denied
10.10.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-CRED-TC-005 | Verify driver license validity | High |
| INSP-CRED-TC-006 | Verify safari guide license for commercial operators | High |
| INSP-CRED-TC-007 | Manual verification process by staff | High |
10.11 Ft Insp Cred Commercial
10.11.1 Priority
Must Have
10.11.2 User Story
As a gate inspector, I want to verify commercial operator licenses for safari vehicles so that regulations are enforced
10.11.3 Preconditions
Operator license database available; vehicle classified as commercial
10.11.4 Postconditions
Commercial license verified; alerts if expired or invalid
10.11.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-CRED-TC-008 | Check operator license in database | High |
| INSP-CRED-TC-009 | Verify license expiry date | High |
| INSP-CRED-TC-010 | Alert if license expired | High |
| INSP-CRED-TC-011 | Alert if license invalid or not found | High |
10.12 Ft Insp Cred Blacklist
10.12.1 Priority
Should Have
10.12.2 User Story
As a security manager, I want to check vehicles against a blacklist so that prohibited vehicles are prevented from entry
10.12.3 Preconditions
Blacklist database maintained; vehicle plate extracted
10.12.4 Postconditions
Blacklist status checked; entry denied if blacklisted
10.12.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-CRED-TC-012 | Check plate against blacklist database | Medium |
| INSP-CRED-TC-013 | Alert if vehicle blacklisted | High |
| INSP-CRED-TC-014 | Display blacklist reason to staff | Medium |
| INSP-CRED-TC-015 | Check expiry dates for temporary bans | Medium |
10.13 Ft Insp Int Logging
10.13.1 Priority
Must Have
10.13.2 User Story
As a gate staff member, I want inspection results to automatically create vehicle log entries so that manual logging is eliminated
10.13.3 Preconditions
Inspection complete; gate operations module accessible
10.13.4 Postconditions
Vehicle log entry created with timestamp, plate, type, and image reference
10.13.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-INT-TC-001 | Create log entry automatically after inspection | High |
| INSP-INT-TC-002 | Include timestamp, plate, type in log | High |
| INSP-INT-TC-003 | Include image reference in log entry | High |
| INSP-INT-TC-004 | Handle 1000+ log entries per day | High |
10.14 Ft Insp Int Permit
10.14.1 Priority
Must Have
10.14.2 User Story
As a gate inspector, I want inspection results linked to permit verification so that complete validation is provided
10.14.3 Preconditions
Inspection complete; permit database accessible
10.14.4 Postconditions
Permit status displayed; inspection result includes permit validity
10.14.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-INT-TC-005 | Real-time lookup in permit database | High |
| INSP-INT-TC-006 | Display permit status on inspection screen | High |
| INSP-INT-TC-007 | Link inspection record to permit record | High |
10.15 Ft Insp Int Capacity
10.15.1 Priority
Must Have
10.15.2 User Story
As a capacity manager, I want inspection results to update capacity counts so that real-time tracking is maintained
10.15.3 Preconditions
Inspection complete; capacity tracking system operational
10.15.4 Postconditions
Capacity incremented on entry; decremented on exit
10.15.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-INT-TC-008 | Increment capacity count on vehicle entry | High |
| INSP-INT-TC-009 | Decrement capacity count on vehicle exit | High |
| INSP-INT-TC-010 | Track capacity by vehicle type | Medium |
10.16 Ft Insp Ui Dashboard
10.16.1 Priority
Must Have
10.16.2 User Story
As a gate inspector, I want to view a real-time inspection dashboard so that I can monitor and intervene when needed
10.16.3 Preconditions
Inspection system operational; staff logged in
10.16.4 Postconditions
Dashboard displays live feed, detection results, and controls
10.16.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-UI-TC-001 | Display live camera feed | High |
| INSP-UI-TC-002 | Show detection confidence scores | High |
| INSP-UI-TC-003 | Provide manual override buttons | High |
| INSP-UI-TC-004 | Update dashboard in real-time (<500ms latency) | High |
10.17 Ft Insp Ui Override
10.17.1 Priority
Must Have
10.17.2 User Story
As a gate inspector, I want to manually override automatic detection results so that I can correct errors
10.17.3 Preconditions
Inspection result displayed; override access enabled for user role
10.17.4 Postconditions
Manual correction applied; reason documented; audit trail maintained
10.17.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-UI-TC-005 | Edit vehicle type manually | High |
| INSP-UI-TC-006 | Edit plate number manually | High |
| INSP-UI-TC-007 | Edit trailer status manually | Medium |
| INSP-UI-TC-008 | Require reason for manual override | High |
| INSP-UI-TC-009 | Maintain audit trail of all overrides | High |
10.18 Ft Insp Ui Alert
10.18.1 Priority
Must Have
10.18.2 User Story
As a gate inspector, I want to receive visual and audio alerts for credibility issues so that I can take immediate action
10.18.3 Preconditions
Credibility check complete; alert conditions configured
10.18.4 Postconditions
Alert displayed/sounded; staff acknowledged alert
10.18.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-UI-TC-010 | Visual alert for permit mismatch | High |
| INSP-UI-TC-011 | Visual alert for blacklisted vehicle | High |
| INSP-UI-TC-012 | Visual alert for expired license | High |
| INSP-UI-TC-013 | Audio alert for high-priority issues | Medium |
| INSP-UI-TC-014 | Color-coded urgency levels (red, yellow, green) | Medium |
10.19 Ft Insp Ui History
10.19.1 Priority
Should Have
10.19.2 User Story
As a gate inspector, I want to view vehicle inspection history so that I can identify repeat visitors
10.19.3 Preconditions
Historical inspection data available; search interface accessible
10.19.4 Postconditions
Inspection history displayed with images and details
10.19.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-UI-TC-015 | Search inspection history by plate number | Medium |
| INSP-UI-TC-016 | Search inspection history by date range | Medium |
| INSP-UI-TC-017 | Display all previous inspections with images | Medium |
10.20 Ft Insp Manual Entry
10.20.1 Priority
Must Have
10.20.2 User Story
As a gate inspector, I want to manually enter vehicle details when cameras fail so that operations continue
10.20.3 Preconditions
Camera system unavailable; manual entry form accessible
10.20.4 Postconditions
Vehicle details entered manually; marked as manual entry
10.20.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-MANUAL-TC-001 | Access manual entry form | High |
| INSP-MANUAL-TC-002 | Enter vehicle type, plate, and details manually | High |
| INSP-MANUAL-TC-003 | Tablet-friendly interface for mobile inspection | High |
| INSP-MANUAL-TC-004 | Flag entry as manual for audit purposes | Medium |
10.21 Ft Insp Manual Photo
10.21.1 Priority
Should Have
10.21.2 User Story
As a gate inspector, I want to capture vehicle photos using a tablet camera so that visual documentation is maintained when fixed cameras fail
10.21.3 Preconditions
Tablet with camera available; fixed camera system unavailable
10.21.4 Postconditions
Photo captured; uploaded to central archive when network available
10.21.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-MANUAL-TC-005 | Capture photo using tablet camera | Medium |
| INSP-MANUAL-TC-006 | Upload photo to central archive | Medium |
| INSP-MANUAL-TC-007 | Sync photos when network restored | Medium |
10.22 Ft Insp Report Daily
10.22.1 Priority
Should Have
10.22.2 User Story
As a manager, I want to generate daily inspection reports so that I can monitor system performance
10.22.3 Preconditions
Daily inspection data available; reporting module accessible
10.22.4 Postconditions
Report generated with performance metrics
10.22.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-REPORT-TC-001 | Generate report with total vehicles inspected | Medium |
| INSP-REPORT-TC-002 | Include detection success rate | Medium |
| INSP-REPORT-TC-003 | Include count of manual overrides | Medium |
| INSP-REPORT-TC-004 | Include count of alerts triggered | Medium |
10.23 Ft Insp Report Audit
10.23.1 Priority
Must Have
10.23.2 User Story
As an auditor, I want to generate audit reports with all vehicle inspections and images so that compliance is supported
10.23.3 Preconditions
Inspection data and images archived; audit reporting accessible
10.23.4 Postconditions
Comprehensive audit report generated with images
10.23.5 Test Cases
| Id | Description | Weight |
|---|---|---|
| INSP-REPORT-TC-005 | Filter audit report by date range | High |
| INSP-REPORT-TC-006 | Filter audit report by gate | High |
| INSP-REPORT-TC-007 | Filter audit report by vehicle type | Medium |
| INSP-REPORT-TC-008 | Include vehicle images in report | High |
| INSP-REPORT-TC-009 | Export report to PDF format | High |
| INSP-REPORT-TC-010 | Export report to Excel format | Medium |
11 Additional Context
11.1 Success Metrics
11.1.1 Inspection Time
< 30 seconds per vehicle (currently 2-3 minutes manual)
11.1.2 Detection Accuracy
≥ 95% vehicle classification, ≥ 85% trailer detection
11.1.3 Staff Workload Reduction
60% reduction in manual inspection tasks
11.1.4 Automation Rate
90% of vehicles automatically inspected with minimal manual intervention
11.1.5 Audit Trail Completeness
100% of vehicles have image documentation
11.2 Revision Notes
11.2.1 Nov 3 2025
Added adjustable camera requirement for varied vehicle heights, trailer detection with fine-tuned models