TinyML: Artificial Intelligence Revolution at the Edge in Industrial Sensors

Amazeng Technical Team
6 min read
TinyMLEdge AIIndustrial SensorsArtificial IntelligenceEmbedded Systems

Introduction

When artificial intelligence is mentioned, massive servers and powerful graphics cards come to mind. However, such a big power source is not contained within a transmitter or vibration sensor in the industrial field. This is where TinyML (Tiny Machine Learning) comes in. TinyML is the art of running machine learning models on microcontrollers (MCUs) with only a few kilobytes of memory. This technology transforms industrial sensors into smart devices that "understand what they see" rather than just "looking."

What Does TinyML Change in Sensors?

Traditional sensors collect and transmit data. A smart sensor with TinyML:

  1. Local Decision Making: Analyzes the data on site without sending it to the cloud. This means response time in milliseconds (zero latency).
  2. Bandwidth Savings: Transmits data only when an abnormal situation (fault, leak, etc.) is detected. This reduces the energy and communication cost of IoT systems.
  3. Privacy and Security: Since critical data is processed without leaving the device, cyber security risks are minimized.

Industrial Application Examples

  • Anomaly Detection: From the vibration of a motor, it can notice a previously unseen fault mode in seconds.
  • Smart Filtering: It uses deep learning models instead of classic filters to distinguish noise from real data (for example, the difference between churning in the tank and real filling).
  • Sound Analysis: Sound-based analysis systems that understand which bearing needs lubrication from the sounds made by machines in the factory.

Amazeng and the Future with AI

At Amazeng, we are making our data acquisition devices "Edge AI" compatible.

  • High-resolution 24-bit data coming from our ZMA Data Acquisition devices provide the highest quality training material for TinyML models.
  • The modern MCU infrastructure we use in our embedded system architecture allows libraries such as TensorFlow Lite Micro and Edge Impulse to run on our devices.

Conclusion

TinyML is a quiet revolution that increases the "IQ" of industrial sensors. In the factories of the future, devices will not only be interconnected, but each will also have a small artificial intelligence in its own area of responsibility.

Contact our engineers to get more information about your artificial intelligence-supported sensor projects and our TinyML-based solutions.

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