Automated Gate Control with Rugged Edge Computing

Key Challenges in Access Control Systems

The system integrators plan to deploy an AI-driven automated gate system that integrates RFID, license plate recognition (LPR), and video surveillance analytics to automate entry and exit processes while maintaining a real-time security overview. However, they are facing several key challenges:

• Gate controllers need to operate under harsh environments 24/7 without frequent maintenance.
• Need edge AI capabilities to process security footage locally and ensure instant access verification.
• Complex system integration in space-limited access control cabinets.
• Troubleshooting and managing devices efficiently remotely.

6 Critical Factors for Selecting the Right Edge AI Computing Solution

1. AI Performance

Assess computing needs—does your application require much AI performance for real-time AI inference, or is lite performance enough?

2. Connectivity

Ensure reliable industrial networking—do you need multiple LAN ports to connect to sensors or cameras? Is remote management a necessity? What about wireless or 5G connectivity?

3. Power Input

Smart city environments require flexible power options. Does your system support a wide power input range to accommodate different infrastructure setups?

4. Environmental Requests

What operating temperature range is required, and can it remain functional outdoors 24/7? Can it resist shock & vibration, and is it dust-proof or waterproof?

5. Mounting & Installation

Every workspace has constraints. Is your workspace DIN-Rail mount friendly, or does it only allow wall mount?

6. Security & Compliances

What security or safety compliances are required in this application? Is TPM 2.0 required? And does the application need a UL certification or EMC compliance?