360View Management System
The 360View Management System is a centralized surveillance solution designed to optimize CCTV operations using Artificial Intelligence (AI). Its architecture improves operational efficiency through automated, accurate analysis, and user-friendly interfaces for real-time monitoring, event tracking, and system management.
Core System Workflow
01.
ACQUIRING
At this stage, collects raw video footage from a network of CCTV cameras (IoT and edge devices)
02.
ORGANIZING
- Processes and categorizes video data with integrated AI
- Performs detection, identification, and autonomous self-training to enhance analytical accuracy
- Reduces reliance on raw data, utilizing advanced edge processing for efficient transmission
03.
OUTPUT
- Provides refined, actionable data, not just raw feeds
- Features automated AI tools: object tracking, sorting, and justification, improving overall efficiency and decision-making
Architecture
- Centralized management for all camera feeds and analytics.
- Edge and IoT devices process data locally before sending relevant information to the Video Management System (VMS).
- AI training platform enhances object recognition/detection through continuous learning and annotation feedback
Data Flow Example
| Stage | Process | Output |
|---|---|---|
| Acquiring | Cameras capture and collect video | Raw footage |
| Organizing | AI on edge devices processes data, identifies objects, self-trains | Categorized, analyzed data |
| Output | Output to user application with automation features (tracking, sorting) | Actionable insights, analytics |
Key Features
The system boasts 10 main features to streamline operations and improve performance :
Viewing and Managing Stream
Dynamically add/remove streams, real-time monitoring
Device Monitoring and Management
Track CPU, memory, media/recorder status, interface speed, storage
Viewing Event Data
Timeline/event-based browsing, metadata filtering
Browse Through Events
Organized, categorized incident review
Training Process
AI model training with project selection and parameter adjustment
Annotation
Manual correction of detection errors for dataset improvement
Testing Model
Evaluates performance: loss, accuracy, confusion matrix, etc.
Analyze Model
Comprehensive training reports and visualization tools
Playback
Access and navigate past recordings via timestamps/events
Adding Camerato Training Platform
Configure for data collection/model training (labeling, cycle, etc.)
Feature Highlights
- Real-Time Data Visualization: Customizable charts (bar, pie, line), interactive exploration, time-based filtering.
- Flexible Surveillance Control: Easily manage active/inactive streams based on operational priorities.
- Advanced Object Detection: Utilizes AI for real-time and recorded analysis, tracking, classification (e.g., helmet detection).
- Annotation & Retraining: Users manually correct misclassifications to improve model accuracy and retrain systems, reducing future errors.
- Event Analysis: Event metrics by time, location, activity type, and object/entity identification for efficient incident response.
System and Device Monitoring
Real-time monitoring of system status:
- CPU/Memory Usage: Keep performance optimal.
- Media Server/Recorder Status: Ensures uninterrupted operation and data integrity.
- Storage Levels & Interface Speed: Prevents failures or bandwidth bottlenecks.
AI Model Management
Training & Testing
Projects can be initiated and tracked for progress (e.g., Loss/Accuracy, epoch information, best-performing model)
Performance Metrics
Includes accuracy, precision, recall, F1-score, confusion matrix, and visual tools like heatmaps and curves to understand strengths and weaknesses
Configuration
Cameras are easily added to the data-collection system with customizable inputs: label lists, image cycles, training ratios, accuracy targets, and initial models
Key Technical Terms Explained
Edge Devices
Hardware (like local servers close to cameras) that processes data before syncing with the central system—reduces latency and bandwidth use
AI Self-Training/Autonomous Training
AI dynamically improves its detection/classification by learning from new data and user corrections, reducing errors over time
Object Justification
The system automatically validates and sorts detected objects for analysis
Annotation
Manually labeling data (correcting errors) to create more accurate training sets for AI models
Confusion Matrix
Graphical tool for visualizing the performance of a classification algorithm (shows true/false positives/negatives for each class)
Tables: System Stages & Monitoring Parameters
| Stage | Description |
|---|---|
| Acquiring | Capturing raw video data |
| Organizing | AI-based categorization, on-edge filtering |
| Output | User-focused analytics & automation |
| Parameter | Monitoring Purpose |
|---|---|
| CPU Usage | Diagnose performance bottlenecks |
| Memory Usage | Prevent slowdowns |
| Media Server | Assure continuous streaming |
| Recorder Status | Guarantee event capture |
| Interface Speed | Detect network issues |
| Storage | Avoid data loss/system failure |
Conclusion
The 360View Management System presents a comprehensive, AI-powered solution for CCTV management—enabling automated, accurate, and actionable surveillance at scale. By integrating real-time analytics, advanced model training, and user-friendly interfaces, organizations can efficiently manage security, optimize resources, and support data-driven operational decisions
Ready to get started?
Contact us today, to learn more about our 360View Management System Solutions, and how we can help take your business to the next level. Let us handle your IT, so you can focus on what matters cost – driving your business forward
Related Articles
Background In the metal and steel industry, maintaining high-quality standards is non-negotiable. Product durability and compliance with strict regulations are paramount,...
