Edge AI
The integration of artificial intelligence (AI) and machine learning algorithms directly into hardware enables devices to process data locally and make decisions real-time.
By choosing proper SoM or microcontroller with AI capabilities, the device is able to perform given tasks on the edge, without the need of cloud processing and data transfer consumption. Here is the list of the most common use cases:
Predictive maintenance & anomaly detection (vibration, ultrasounds)
Sounds recognition (cry, siren, dog barking)
Distinguish music from the background noise
People counting using thermal or RGB cameras
Crash detection on wearables
Automated quality control
Objects detection and recognition on video stream
Utilizing Nvidia Jetson which is one of the most powerful Edge AI modules on the market. Perfect for heavier tasks like real-time video processing, objects tracking, behavior recognition and others.
ESP is well-known for its quality of microcontrollers and now it offers also running AI and ML models on the device. Cost and size-optimized, perfect for tasks like sounds recognition or predictive maintenance.
Small size, low-power and quite powerful. Perfect for sounds recognition, predictive maintenance and many other tasks.
Improved Data Security
Edge AI leverages the cloud only during initial setup, ensuring your data remains within a secure, closed system.
Real-Time Decision Making
Make decisions instantly without the need for cloud connectivity or external systems.
Customization and Flexibility
Our solutions are fully customized to meet the unique needs of your business.
Case Prototype
We provide custom device cases through manufacturing or 3D printing services.
Energy Efficiency
Edge AI is designed for optimal performance with minimal power consumption, extending device lifespan.
EU Certification
Our projects comply with all relevant EU standards and regulations.
Help in Securing a Patent
Your innovations are safe with us, as we assist you in obtaining a patent.
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