STMicroelectronics
STM32F4 Edge AI Guides
192 KB SRAM with FPU and DSP instructions supports small ML models. CMSIS-NN optimized for Cortex-M4.
Hardware Specs
| Processor | ARM Cortex-M4F @ 168 MHz |
| Cores | 1 |
| Clock | 168 MHz |
| SRAM | 192 KB |
| Flash | 1 MB |
| FPU | single |
| Connectivity | USB OTG FS |
| Key Features | Single-precision FPU, DSP instructions, Widely available ecosystem |
| Price | $3–$10 (chip), $10–$30 (dev board) |
105 dev boards available across PlatformIO registries.
Hardware Guides
STM32F4 Anomaly Detection with Edge Impulse
For anomaly detection, the STM32F4 with Edge Impulse scores Excellent. Its 192 KB internal SRAM (6.0x the required 32 KB) and 168 MHz clock …
STM32F4 Anomaly Detection with TFLite Micro
The STM32F4 runs autoencoder-based anomaly detection with TFLite Micro using under 20 KB of its 192 KB SRAM. The Cortex-M4F's DSP instructio…
STM32F4 Fall Detection with Edge Impulse
The STM32F4 is an excellent match for fall detection with Edge Impulse. 192 KB SRAM delivers 3.0x the 64 KB minimum while 168 MHz processes …
STM32F4 Fall Detection with TFLite Micro
STMicroelectronics's STM32F4 excels at fall detection via TFLite Micro. The 1-core cortex-m4f at 168 MHz with 192 KB SRAM handles 20 KB quan…
STM32F4 Gesture Recognition with Edge Impulse
The STM32F4 classifies IMU gestures with Edge Impulse's optimized inference pipeline. The Cortex-M4F's DSP instructions handle spectral feat…
STM32F4 Gesture Recognition with TFLite Micro
Running gesture recognition on the STM32F4 with TFLite Micro is practical. 192 KB SRAM meets the 64 KB minimum with 3.0x headroom. The 168 M…
STM32F4 Image Classification with Edge Impulse
The STM32F4 handles image classification effectively with Edge Impulse. 192 KB SRAM at 168 MHz provides 1.5x headroom over the 128 KB requir…
STM32F4 Image Classification with TFLite Micro
The STM32F4 handles image classification effectively with TFLite Micro. 192 KB SRAM at 168 MHz provides 1.5x headroom over the 128 KB requir…
STM32F4 Predictive Maintenance with Edge Impulse
Running predictive maintenance on the STM32F4 with Edge Impulse is practical. 192 KB SRAM meets the 64 KB minimum with 3.0x headroom. The 16…
STM32F4 Predictive Maintenance with TFLite Micro
The STM32F4 is a widely used Cortex-M4 for vibration-based predictive maintenance. With 192 KB SRAM, 168 MHz clock, and DSP instructions, it…
STM32F4 Sound Classification with Edge Impulse
The STM32F4 is an excellent match for sound classification with Edge Impulse. 192 KB SRAM delivers 3.0x the 64 KB minimum while 168 MHz proc…
STM32F4 Sound Classification with TFLite Micro
STMicroelectronics's STM32F4 excels at sound classification via TFLite Micro. The 1-core cortex-m4f at 168 MHz with 192 KB SRAM handles 40 K…
STM32F4 Voice Recognition with Edge Impulse
STMicroelectronics's STM32F4 is a solid choice for voice recognition using Edge Impulse. The cortex-m4f core at 168 MHz with 192 KB SRAM acc…
STM32F4 Voice Recognition with TFLite Micro
The STM32F4 handles voice recognition effectively with TFLite Micro. 192 KB SRAM at 168 MHz provides 1.5x headroom over the 128 KB requireme…
STM32F4 Wildlife Monitoring with Edge Impulse
The STM32F4 handles wildlife monitoring effectively with Edge Impulse. 192 KB SRAM at 168 MHz provides 1.5x headroom over the 128 KB require…
STM32F4 Wildlife Monitoring with TFLite Micro
Running wildlife monitoring on the STM32F4 with TFLite Micro is practical. 192 KB SRAM meets the 128 KB minimum with 1.5x headroom. The 168 …
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Orchestrate STM32F4 Edge AI with ForestHub
The STM32F4 runs inference on-device. ForestHub on your Linux edge gateway ingests its results over MQTT, orchestrates the sense-reason-act loop as a deterministic, auditable graph, and acts on the line.
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