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Identifying AI Opportunities

Identifying Practical AI Use Cases

The ALC-4096-AIH board is designed to bring powerful edge AI capabilities directly into your product or system. With a built-in AI accelerator, support for Raspberry Pi CM5, and flexible I/O options, it can analyze data, detect patterns, and trigger actions in real-time, all without relying on the cloud. But the real question many engineers and product managers face is:

​"How do I identify the right use cases for this board?"

This guide offers a straightforward framework for identifying relevant AI applications. By focusing on real operational needs, from preventing product failures to enhancing workplace safety, you can identify opportunities to utilize the ALC-4096-AIH board to deliver tangible benefits.

Process Overview

  1. Identify High-Cost Areas / Pain Points
  2. Check for relevant data
  3. Determine AI's impact
  4. Quantify Potential ROI

shows the four structured steps for identifying AI opportunities


Step 1: Start with Real-World Problems

The most effective AI projects begin with a specific, real-world objective, not with AI itself. Ask questions like:

  • Where are errors or failures most damaging?
  • Which tasks are repetitive, slow, or prone to human error?
  • Where could early detection or prediction prevent a bigger problem?

Common areas include:

  • Product Reliability: Detecting defects or conditions that could cause failures.
  • Operational Efficiency: Predicting maintenance needs or optimizing resource use.
  • Safety & Compliance: Monitoring PPE use, restricted areas, or unsafe movements.

By starting with a clear operational goal, you ensure AI is being used for something that truly matters.


Step 2: Check for Available Data

The ALC-4096-AIH board shines when paired with meaningful data sources. Consider:

  • Visual Data: Images or video from cameras (ideal for inspection or safety monitoring)
  • Sensor Data: Temperature, vibration, or environmental readings
  • System Logs: Machine outputs or error events

If data is not yet available, ask whether it can be captured with cameras or sensors. AI can only find patterns in the data it receives.


Step 3: Match the Data to AI Capabilities

Once you know the problem and the data, consider what the ALC-4096-AIH can do:

  • Detection & Classification: Identify defects, unsafe actions, or specific objects.
  • Prediction: Anticipate failures or abnormal behavior before they cause damage.
  • Optimization & Automation: Reduce human intervention in repetitive or error-prone tasks.
  • Anomaly Detection: Spot unusual conditions in sensor or camera data.

Edge AI is especially powerful when real-time action is required, catching a defect, triggering an alert, or adjusting a process immediately.


Step 4: Estimate the Benefit

Even if your primary goal is operational (like preventing a failure), consider the downstream impact:

  • Reduced warranty claims and product returns
  • Lower maintenance and downtime costs
  • Safer workplaces and fewer compliance issues
  • Improved customer trust and satisfaction

You don’t need a complex ROI model to start, simply ensure that solving the problem brings meaningful value.

Example Use Cases

Here are two clear examples of how to identify and apply the ALC-4096-AIH board in real products:

1. Preventing Product Failures

  • Problem: Small defects in a component can lead to field failures.
  • Data: Camera images of components during production.
  • AI Solution: Use the ALC-4096-AIH to run a real-time visual inspection model that flags defects.
  • Result: Fewer failures, reduced rework, and happier customers.

2. Enhancing Workplace Safety

  • Problem: Workers occasionally enter restricted areas without PPE.
  • Data: Live video from security or industrial cameras.
  • AI Solution: AI on the ALC-4096-AIH detects missing PPE or unsafe actions and sends immediate alerts.
  • Result: Fewer incidents, better compliance, and safer operations.

Conclusion

Identifying use cases for the ALC-4096-AIH board starts with understanding the problems you want to solve. By following this simple framework, problem first, data second, AI capability third, you can confidently pinpoint applications where edge AI delivers real, immediate value.

Next Steps

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