Description

Seeed Studio SenseCAP A1102 is a rugged LoRaWAN Vision AI sensor built by Seeed Studio for low-power edge inference in remote and industrial deployments. Instead of sending raw video, SenseCAP A1102 runs TinyML models locally and transmits only inference results over LoRaWAN, which helps protect privacy and minimize bandwidth usage. If you need an edge AI camera for human detection, people counting, meter reading, or custom event monitoring, this Seeed Studio sensor gives you a practical path from no-code model deployment to long-range field-ready sensing.

Features

• Vision AI sensor with local TinyML inference for private low-bandwidth deployments.
• Pre-deployed AI tasks including human detection, people counting, and meter reading for fast field rollout.
• SenseCraft AI support for no-code access to 300+ pre-trained models and custom model workflows.
• Framework compatibility for TensorFlow Lite and PyTorch model deployment on a flexible edge AI camera platform.
• IP66-rated outdoor-ready design for harsh indoor and outdoor use.
• Built-in battery and LoRaWAN communication for long-range low-power edge AI camera sensing in the Seeed Studio ecosystem.

Specifications

Applications

• Edge AI camera deployments for human detection and occupancy awareness.
• People counting in entrances, public spaces, retail paths, and smart building workflows where people counting accuracy matters.
• Meter reading in utility, factory, and remote infrastructure scenarios.
• Industrial and agricultural monitoring where a Vision AI sensor must run in the field.
• Privacy-aware remote AI sensing where transmitting inference results is better than streaming raw video.

Product List

Note: Official example images may show the S2100 Data Logger in deployment diagrams, but that logger is not included with this product.

Other Content

SenseCAP A1102 is built around a split architecture: vision inference happens on the AI camera side, while LoRaWAN communication and integration happen through the network side. That design helps this Seeed Studio sensor keep power use low while remaining field-deployable.

The power options are also important. You can run SenseCAP A1102 with a built-in battery workflow or from external 12V DC depending on the installation plan and maintenance strategy.

For first deployment, the official onboarding flow shows app pairing, LoRaWAN parameter setup, and cloud visibility in a compact workflow. That is especially useful when bringing a Vision AI sensor and edge AI camera online in new projects.

Resources

• Seeed Studio SenseCAP A1102 Wiki
• SenseCraft AI Platform
• SenseCraft App Download
• SenseCAP Cloud Platform
• TensorFlow Lite
• PyTorch

FAQ

What makes SenseCAP A1102 different from a normal IP camera?
SenseCAP A1102 is a Seeed Studio AI sensor, not a streaming IP camera. It runs AI models locally and sends only inference results, which is better for low-power remote sensing and privacy-focused deployments.

Can SenseCAP A1102 do people counting out of the box?
Yes. Official documentation says SenseCAP A1102 includes pre-deployed models for human detection, people counting, and meter reading, which makes this edge AI camera practical from day one.

Can I deploy my own AI model?
Yes. This Seeed Studio edge AI camera supports model deployment through SenseCraft AI and also supports TensorFlow Lite and PyTorch workflows.

Is the S2100 Data Logger included?
No. Some official diagrams use the S2100 Data Logger to illustrate field deployment, but the product itself is the SenseCAP A1102 sensor.