All Projects → sparkfun → Sparkfun_edge

sparkfun / Sparkfun_edge

Licence: other
SparkFun's Edge Development Board is based around the newest edge technology and is perfect for getting your feet wet with voice and even gesture recognition without relying on 3rd party cloud services.

Projects that are alternatives of or similar to Sparkfun edge

peerjs-python
Python port of PeerJS client
Stars: ✭ 56 (+143.48%)
Mutual labels:  edge-computing
google-coral
Community gathering point for Google Coral dev board and dongle knowledge.
Stars: ✭ 81 (+252.17%)
Mutual labels:  edge-computing
Kubeedge
Kubernetes Native Edge Computing Framework (project under CNCF)
Stars: ✭ 4,582 (+19821.74%)
Mutual labels:  edge-computing
fog05
End-to-End Compute, Storage and Networking Virtualisation.
Stars: ✭ 50 (+117.39%)
Mutual labels:  edge-computing
Awesome-Federated-Machine-Learning
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Stars: ✭ 190 (+726.09%)
Mutual labels:  edge-computing
Fastmot
High-performance multiple object tracking based on YOLO, Deep SORT, and optical flow
Stars: ✭ 284 (+1134.78%)
Mutual labels:  edge-computing
nott
The New OTT Platform - an excuse to discuss and design a simple edge computing platform
Stars: ✭ 46 (+100%)
Mutual labels:  edge-computing
Ops
ops - build and run nanos unikernels
Stars: ✭ 552 (+2300%)
Mutual labels:  edge-computing
Train plus plus
Repo and code of the IEEE UIC paper: Train++: An Incremental ML Model Training Algorithm to Create Self-Learning IoT Devices
Stars: ✭ 17 (-26.09%)
Mutual labels:  edge-computing
Wasm3
🚀 The fastest WebAssembly interpreter, and the most universal runtime
Stars: ✭ 4,375 (+18921.74%)
Mutual labels:  edge-computing
Edge2Guard
Code for PerCom Workshop paper title 'Edge2Guard: Botnet Attacks Detecting Offline Models for Resource-Constrained IoT Devices'
Stars: ✭ 16 (-30.43%)
Mutual labels:  edge-computing
DeepThings
A Portable C Library for Distributed CNN Inference on IoT Edge Clusters
Stars: ✭ 49 (+113.04%)
Mutual labels:  edge-computing
Yomo
🦖 Streaming-Serverless Framework for Low-latency Edge Computing applications, running atop QUIC protocol, engaging 5G technology.
Stars: ✭ 279 (+1113.04%)
Mutual labels:  edge-computing
freeioe
FreeIOE is a framework for building IOE (Internet Of Everything) edge-computing gateway 开源的边缘计算网关框架. 讨论群: 291292378
Stars: ✭ 77 (+234.78%)
Mutual labels:  edge-computing
Objectbox Java
ObjectBox is a superfast lightweight database for objects
Stars: ✭ 3,950 (+17073.91%)
Mutual labels:  edge-computing
keras openvino
How to run Keras model inference x3 times faster with CPU and Intel OpenVINO
Stars: ✭ 32 (+39.13%)
Mutual labels:  edge-computing
homesecurity
Security camera with Raspberry pi and NVIDIA Jetson platforms
Stars: ✭ 141 (+513.04%)
Mutual labels:  edge-computing
Openyurt
OpenYurt - Extending your native Kubernetes to edge(project under CNCF)
Stars: ✭ 750 (+3160.87%)
Mutual labels:  edge-computing
Macchina.io
macchina.io IoT Edge Device SDK is a powerful C++ and JavaScript SDK for edge devices, IoT gateways and connected embedded systems.
Stars: ✭ 437 (+1800%)
Mutual labels:  edge-computing
Kuiper
A lightweight IoT edge analytics software
Stars: ✭ 327 (+1321.74%)
Mutual labels:  edge-computing

SparkFun Edge 2

SparkFun Edge 2

SparkFun Edge 2 (DEV-15420)

Edge computing is here! You've probably heard of this latest entry to the long lineage of tech buzzwords like "IoT," "LoRa," and "cloud" before it, but what is “the edge” and why does it matter? The cloud is impressively powerful but all-the-time connection requires power and connectivity that may not be available. Edge computing handles discrete tasks such as determining if someone said "yes" and responds accordingly. The audio analysis is done at the edge rather than on the web. This dramatically reduces costs and complexity while limiting potential data privacy leaks.

In collaboration with Google and Ambiq, SparkFun's Edge 2 Development Board is based around the newest edge technology and is perfect for getting your feet wet with voice and even gesture recognition without relying on the distant services of other companies. The truly special feature is in the utilization of SparkFun's open-source and FCC Certified Artemis module, whose ultra-efficient ARM Cortex-M4F 48MHz (with 96MHz burst mode) processor, is spec’d to run TensorFlow Lite using only 6uA/MHz. The SparkFun Edge 2 board currently measures [email protected] and 48MHz and can run solely on a CR2032 coin cell battery for up to 10 days. Artemis sports all the cutting edge features expected of modern microcontrollers including six configurable I2C/SPI masters, two UARTs, one I2C/SPI slave, a 15-channel 14-bit ADC, and a dedicated Bluetooth processor that supports BLE5. On top of all that the Artemis has 1MB of flash and 384KB of SRAM memory - plenty for the vast majority of applications.

On the Edge 2 you'll have built-in access to sensors, Bluetooth, I2C expansion, and GPIO inputs/outputs. To support edge computing cases like voice recognition the Edge 2 board features two MEMS microphones, an ST LIS2DH12 3-axis accelerometer on its own I2C bus, and a connector to interface to an OV7670 camera (sold separately & functionality coming soon). As TensorFlow updates their algorithms more and more features will open up for the SparkFun Edge 2. An onboard Bluetooth antenna gives the Edge 2 out-of-the-box connectivity. Also available on the board is a Qwiic connector to add I2C sensors/devices, four LEDs, and four GPIO pins. To boast the low-power capabilities of the board we've outfitted it with battery operation from the CR2032 coin cell holder. Programming the board is taken care of with an external USB-serial adapter like the Serial Basic Breakout via a serial bootloader, but for more advanced users we've also made available the JTAG programming and debugger port.

As a brave explorer of this new technology, you'll have to use some advanced concepts but don't worry. Between Ambiq Micro's Software Development Kit and our SDK Setup Guide you'll have access to plenty of examples to begin working with your hardware.

Now get out there and make something amazing with the latest machine learning technology at your very own fingertips!

Repository Contents

  • /Documentation - Data sheets, additional product information
  • /Firmware - Arduino test firmware sketch
  • /Hardware - Eagle design files (.brd, .sch)
  • /Production - Production panel files (.brd)

Documentation

Product Versions

Version History

  • v20 - Edge with the Artemis
  • v10 - Initial HW release

License Information

This product is open source!

Please review the LICENSE.md file for license information.

If you have any questions or concerns on licensing, please contact [email protected].

Distributed as-is; no warranty is given.

  • Your friends at SparkFun.

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].