Walter isn’t just a product; it’s your new best friend. An ESP32-S3 board equipped with NB-IoT, LTE-M, and GPS, it’s designed for low power consumption and high efficiency. Whether prototyping or in full production, Walter is your open-source solution for seamless IoT integration. 

In this next episode of our “Let’s Talk IoT Devices” series, delve into Walter’s technology through exciting use cases and understand how its features make it ideal for IoT applications:

 Whether you’re a business looking to expand into the IoT realm or a developer eager to build your next connected device, Walter is your key to a world of possibilities. Don’t miss this opportunity to learn, engage, and innovate with the experts!

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Smart buttons are among the simplest IoT devices, and yet their limitless potential for customization means they can pack quite a punch.

With the push of a button, end users can order products and services, start or stop a task, generate an alert, provide feedback, and so much more.

During the webinar, Soracom IoT Device Product Manager Dora Terjek will be discussing the power and potential of smart buttons, including our latest product, the Soracom LTE-M Button. This smart button boasts built-in connectivity to make custom automation quick and easy, right out of the box.

Key talking points include:

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Smart advertising screens are becoming the new standard for modern smart cities. Equipped with cameras and sensors, advertisers can customize and refresh content on the fly, while engaging and targeting audiences like never before.

Join Soracom, Edge Impulse, and Seeed Studio to learn how to build privacy-friendly advertising panels including:

✅ Training a machine learning model to detect faces in real-time.

✅ Running web applications locally on the Seeed reComputer, powered by NVIDIA’s Jetson platform.

✅ Enabling AIoT by connecting any device to the cloud over cellular with Soracom’s Onyx LTE modem.

✅ Counting people and measuring the time of exposure.

✅ Automatically refreshing the displays while deploying “on-device anonymization” techniques using edge machine learning.

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