Artificial Intelligence Radio - Transceiver (AIR-T)

by Deepwave Digital

A high-performance SDR seamlessly integrated with state-of-the-art deep learning hardware

View all updates Apr 06, 2020

Webinar: Detecting and Labeling Training Data for Signal Classification

by John F

Deep Learning Series Part 1 of 2

Deepwave Digital will be hosting their next webinar on April 14, 2020 at 1 PM EST. In this webinar, we will demonstrate how to detect and label training data for signal classification, using the cuSignal signal processing techniques learned in our previous webinar. Specifically, you will learn how to leverage GPU signal processing and the AIR-T to detect, label, and record training data from various key FOBs over-the-air. cuSignal is part of the NVIDIA RAPIDS development environment and is an effort to GPU accelerate all of the signal processing functions in the SciPy Signal Library.

When: April 14th, 2020 at 1 PM EST

Register Here

Space is limited so make sure to register in advance. Read below for more information about the webinar and we hope you will join us!

Deepwave Digital, Inc.


Webinar Agenda

Introduction to Deepwave Digital

We will introduce you to the Deepwave Digital team and provide an overview of what our startup does. We will also discuss the way we see deep learning being applied to systems and signals.

AirStack Programming API for the AIR-T

We will provide a detailed review of AirStack, the application programming interface (API) for the AIR-T. The figure below outlines the CPU, GPU, and deep learning interfaces supported.

Demonstrations

Key FOB Signals for Labeling

We will create a training data set using an assortment of different key FOBs. These data will be added to our AirPack software package in an upcoming release.

Designing a Real-time Power Detector with cuSignal for the AIR-T

In this section, we will walk the attendees through the real-time python code to:

  1. Compute the instantaneous power of the signal stream
  2. Filter and down-sample the power to a lower data rate
  3. Reshape the down-sampled data into detection segments
  4. Perform detection on each segment of the down-sampled data
  5. Display the detected data (if desired)
  6. Record the data to disk for deep learning training

Real-time Signal Detection and Labeling

Here we will demonstrate how to first execute the software to detect, label, and record the signal from the key FOBs, then over-the-air capture these data. An example of this is shown in this video clip with recorded sections in blue/aqua. See a screenshot from the video below:


When: April 14th, 2020 at 1 PM EST

Register Here for the Webinar

About the Author

John F

boonedoggle  ·   Philadelphia, PA


$193,414 raised

of $20,000 goal

967% Funded! Order Below

Product Choices

$5,500

AIR-T

The AIR-T is the first platform that enables out-of-the-box machine learning wireless systems. Simply port current GNURadio or code directly in Python to access the radio frequency spectrum. Includes, AIR-T board, four MCX-to-SMA cables, getting started tutorial, and power supply.


$5,899

Air-T With Enclosure

The AIR-T is the first platform that enables out-of-the-box machine learning wireless systems. Simply port current GNURadio or code directly in Python to access the radio frequency spectrum. Includes, AIR-T board, four MCX-to-SMA cables, getting started tutorial, and power supply. The Air-T enclosure is expertly constructed from aluminum to produce a polished, elegant, and sleek metallic silver finish. It measures 192 x 182 x 79 mm (7.5 x 7.2 3.1 inches) and the power button illuminates blue when they system is on. All RF ports are brought to the front of the enclosure for ease of use and all computer peripherals connections are brought to the rear.

Credits

Deepwave Digital

We are a dedicated team of radio frequency and wireless industry experts with over fifty years of combined experience providing digital signal processing solutions to the commercial and defense industries. We understand both the technical capabilities as well as the limitations of these technologies, leading us to develop novel hardware and software solutions to combine the fields of artificial intelligence and signal processing.


John Ferguson

Steven Kline

Peter Witkowski

Subscribe to the Crowd Supply newsletter, highlighting the latest creators and projects: