§ Smart infrastructure
City sensing, privacy-first.
People counting, traffic flow, energy monitoring — AI at the sensor, never streams raw video.
§ Why edge AI
The case for running it on the asset.
Smart-city deployments live or die on privacy. Streaming raw video to a central server is a privacy violation, a bandwidth bill, and a single point of failure. The E1M-X V2N runs inference at the lamppost: people-count metadata leaves the camera, raw pixels never do. Compliant by design.
§ The constraint
GDPR Article 5(1)(c) — data minimisation. Pre-aggregated counts and anonymised metrics, not raw streams. AI at the sensor is the only compliant way to deploy at city scale.
Cloud round trip
sensor → uplink → inference → downlink → action
On-module
sensor → on-module inference → action
Sensor
Camera at the lamppost
On-module inference
E1M-AEN
Action
People-count metadata, no raw pixels
§ Recommended modules
Pick the AI compute that fits.
E1M-AEN
Always-on AI at sub-1 mW. Cortex-M55 + Ethos-U55 scaling from 250 GOPS (E3/E5/E7) up to 500 GOPS (E4/E6/E8) for wake-word, vibration anomaly, and ultra-low-power sensing.
View detail →
E1M-X V2N
Quad-core A55 with 4 TOPS DRP-AI3 in a 45×65 mm form factor.
View detail →
E1M-X V2N+M1
RZ/V2N paired with DeepX DX-M1 for 29 TOPS combined AI in 45×65 mm.
View detail →
Smart Eye Camera
Industrial Edge-AI Camera powered by the E1M-X V2N+M1 SoM. A lightweight, all-in-one smart vision device delivering high-performance, low-power AI processing for manufacturing, robotics, warehouse automation, and workplace safety — inside a compact, rugged IP67 housing. Configurable from 4 to 33 TOPS by swapping the underlying SoM (V2N / V2H / V2N+M1 / V2H+M1).
Coming soon
Learn more →
§ Reference examples from the Alp SDK
Code you can fork and ship.
Every example is real C/C++ in the open-source alp-sdk repo. Clone, change the SKU in board.yaml, build.
ai-object-detection-realtime
People + traffic counting
YOLOv8-tiny on the NPU — count, classify, anonymise, ship metadata only.
View on GitHub ↗
iot-connected-camera
Smart-city sensor pipeline
Camera → on-device inference → MQTT events to the city data platform.
View on GitHub ↗
iot-fleet-ota
Fleet OTA for thousands of nodes
Secure firmware updates across a city-scale sensor deployment.
View on GitHub ↗
§ Built for this vertical
Why E1M wins here.
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AI runs at the sensor — raw video never leaves the device
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IP67 + PoE-ready when paired with the Smart Eye Camera
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Mali-C55 ISP for low-light + HDR — actual streetlight conditions
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Long-term availability for 5–10 year municipal deployments