Seeed Studio Studio SenseCAP K1100 Sensor Prototype Kit w/ LoRaWAN & AI Vision

The Wio Terminal is programmable via the Arduino IDE or PlatformIO. Install the Seeed Studio Studio board package, connect via USB-C, and select the 'Seeed Studio SAMD Boards' target. For AI model deployment, use the Edge Impulse Studio to train your model, then export it as an Arduino library or use the EON compiler for the vision module. The Grove sensors communicate via I2C or analog pins, with libraries available in the Arduino Library Manager.

The included Grove Wio-E5 module supports LoRaWAN communication with a typical urban range of 2-5 km and up to 10 km in ideal line-of-sight conditions. To connect, you must register the device's DevEUI, AppEUI, and AppKey with a LoRaWAN network server like The Things Network (TTN) or ChirpStack. Use AT commands over a serial interface from the Wio Terminal to join the network and send uplink data packets. Ensure your region's frequency plan (EU868, US915, AS923) is correctly configured.

Yes, the Grove Vision AI Module supports custom models trained through Edge Impulse or other TensorFlow Lite frameworks. You can train a model using your own image dataset in Edge Impulse, then deploy it via the provided firmware examples. For advanced users, models can be converted to a compatible format and flashed onto the vision module's internal memory using a serial connection. The Wio Terminal acts as the host, processing the vision module's output over a UART or I2C interface.

The kit is primarily powered via the 5V USB Type-C port on the Wio Terminal. For field deployment, you can supply 5V to this port from a battery bank or a regulated LiPo battery with a USB output. The STM32WLE5JC MCU and sensors support low-power sleep modes to conserve energy. To maximize battery life, implement deep sleep cycles in your firmware and wake periodically for sensor readings and LoRa transmissions, which are the most power-intensive operations.