Intelligent Video Analytics for Public Safety

Key Challenges in Smart City Projects

Building AI-powered smart city solutions requires integrating complex technologies across large-scale, dynamic environments. System integrators must address several key challenges before deploying reliable and scalable edge AI infrastructure.

• Integrating diverse systems without compromising performance.
• Deploying hardware that withstands harsh environments.
• Scaling solutions to keep up with evolving city demands.
• Managing and maintaining devices efficiently across a distributed network.

6 Critical Factors for Selecting the Right AI Edge Computing Solution

1. AI Performance

Assess computing needs—does your application require lots of TOPS of 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

Does the ideal computing solution need to support DIN-Rail, VESA or wall mounting for secure and space-efficient installation?

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?