This tech sheet outlines the end-to-end process for building an MVP to market solution with custom Verkada API integrations, focusing on scalable architecture, real-time monitoring, and rapid deployment. With this framework, businesses can manage security, analytics, and automated alerts more efficiently, leveraging Verkada’s powerful camera capabilities.
Key MVP Features:
1. Real-Time Video Integration:
• Verkada’s API is used to pull real-time camera feeds.
• Stream cameras directly in the dashboard with minimal latency.
2. License Plate Recognition (LPR):
• Fetch plate information every X seconds and compare it against the database.
• Alerts for unrecognized plates or flagged vehicles (e.g., unauthorized parking).
• Plate entries are time-stamped and stored for reporting.
3. Event-Triggered Notifications:
• Verkada camera events (e.g., motion detection, vehicle entry) trigger alerts via Twilio SMS or push notifications using Firebase.
• Admins can customize alerts by defining zones and schedules.
4. Custom API Integrations:
• Build custom APIs to sync Verkada data (video streams, plates, events) with other apps or business systems (e.g., CRMs, ERP).
• Webhooks support: Trigger real-time actions on detected events (e.g., automatic door lock, access control).
5. Admin Dashboard:
• View camera feeds, event logs, and recognized plates from a unified interface.
• Report Generation: Export reports on vehicle activity, event history, or camera usage by date.
6. Role-Based Access Control (RBAC):
• OAuth2 + JWT authentication ensures secure access.
• Admins can manage user roles and permissions to control who can view feeds or configure alerts.
MVP Development Process:
1. Requirements Gathering & Planning:
• Define business goals and identify essential camera features (e.g., LPR, live feeds, event alerts).
• Prepare API documentation from Verkada to understand the camera integration capabilities.
2. System Design & Architecture:
• Create flow diagrams to map user interactions (e.g., camera streams, LPR checks, alerts).
• Design microservices architecture to allow flexible scaling and independent updates of key modules (e.g., LPR processing, notifications).
3. Frontend Development:
• React.js / React Native for building the user-facing web and mobile interfaces.
• Integrate video streams and camera snapshots into dashboards.
• WebSocket integration for real-time camera updates.
4. Backend Development:
• Use Node.js + Express.js to build custom APIs that interface with Verkada’s API.
• Implement background tasks for continuous LPR data fetching and event logging (e.g., with Bull.js or Redis queues).
• Store plate data and event logs in PostgreSQL for easy querying and reporting.
5. Camera API Integration:
• API Authentication: Use Verkada’s OAuth-based API to securely connect cameras.
• Pull Video Feeds: Implement endpoints to stream and display live feeds.
• Fetch Plate Data: Automate LPR data fetching to keep plate logs up-to-date.
• Event Triggering: Use Verkada’s webhook support to trigger actions based on specific camera events.
6. Notifications & Alerts:
• Integrate Twilio for SMS alerts and Firebase for push notifications.
• Customize alerts based on predefined rules (e.g., vehicle detected at odd hours).
7. Testing & Quality Assurance:
• Unit Testing: Test each API endpoint and integration using Jest.
• Performance Testing: Ensure the system can handle concurrent camera feeds and API calls.
• End-to-End Testing: Validate the flow from video streaming to LPR alerts.
8. Deployment & CI/CD:
• Dockerize the application for easy deployment on AWS EC2.
• Use GitHub Actions to automate builds and deployments.
• Monitor deployments with AWS CloudWatch and receive alerts for errors or service disruptions.
