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Paul L. created project IoT Analytics Gateway

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IoT Analytics Gateway

Creation of a scaleable and efficient Analytics Gateway to collect anonymous usage data was achieved leveraging a "Serverless" Architecture. The "Serverless" Framework allows the construction auto-scaling, event driven components deployable to many cloud platforms such as Amazon Web Services, Azure and Google Cloud Platform or as the business case requires, deploying as easily to your own private cloud (Intel Private Cloud). Currently servicing sensor and usage data to over 20,000 live connected IoT devices deployed across the U.S., we are able to collect real-time, anonymous statistics for only pennies per device over the service life of the device.

Extremely Low latency (<100ms) and minimal downtime from connectivity disruption is achieved from this service model.

Exploration of usage of Analytics data with leading Machine Learning platforms: Caffe2 (on AWS), Apache Spark BigDL, Cloud AI (Google) & Watson (IBM).

Topics explored: * Serverless - https://serverless.com/ * Caffe2 - https://caffe2.ai/ * Google Cloud AI - https://cloud.google.com/products/machine-learning/ * Apache Spark BigDL - https://software.intel.com/en-us/articles/bigdl-distributed-deep-learning-on-apache-spark * IBM Watson Machine Learning - https://datascience.ibm.com/features#machinelearning * Intel Private Cloud - https://www.intel.com/content/www/us/en/cloud-computing/private-cloud-solutions.html

Paul langdon

Paul L. added photos to project OnTheWall

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OnTheWall

The MagicMirror project was originally developed for RaspPi, it has taken off with community developed modules for many smart home and information services. The Intel Joule allows taking the project to the next level by integrating:

- RealSense Camera to do face recognition and context switching
(i.e. when I walk up to the mirror it recognizes me, presents my calendar and email vs. when another user walk up)
- Voice Recognition/Control - Integrating voice with Google CloudSpeech API
- Integrating Cloud AI with wit.ai for intent and conversational processing
- Integrating Local AI algorithms to take advantage of processing available onboard
- Integration with sensors using MQTT interface
API for sensor data to be presented/incorporated a smart home dashboard
- HDMI video output to mirror
- Possible Augmented Reality leveraging GPU

-------------------

Highlights:

Google Voice API integration with python (Cloud Speech) - https://cloud.google.com/speech/

Node.js for UI

Module framework

---------

Git:
https://github.com/plangdon/OnTheWall

Medium paul langdon

Paul L. created project OnTheWall

Medium ac297d1b 27a4 405b b3dd 9fcc4a92a4e0

OnTheWall

The MagicMirror project was originally developed for RaspPi, it has taken off with community developed modules for many smart home and information services. The Intel Joule allows taking the project to the next level by integrating:

- RealSense Camera to do face recognition and context switching
         (i.e. when I walk up to the mirror it recognizes me, presents my calendar and email vs. when another user walk up) 
-  Voice Recognition/Control  - Integrating voice with Google CloudSpeech API
-  Integrating Cloud AI with wit.ai for intent and conversational processing 
-  Integrating Local AI algorithms to take advantage of processing available onboard
-  Integration with sensors using MQTT interface 
        API for sensor data to be presented/incorporated a smart home dashboard
- HDMI video output to mirror 
- Possible Augmented Reality leveraging GPU

Highlights:

Google Voice API integration with python (Cloud Speech) - https://cloud.google.com/speech/

Node.js for UI

Module framework


Git: https://github.com/plangdon/OnTheWall

Medium paul langdon

Paul L. updated status

Medium paul langdon

Paul Langdon

MagicMirror+++ for Intel Joule

Adding Face Recognition/Voice Recognition/Voice Control using RealSense, Amazon Voice and wit.ai to make a full smart home AI experience that hides as a mirror until you call it into action.

Medium paul langdon

Paul L. created project Warehouse Scanner

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Warehouse Scanner

Developed in node.js, HTML5 on a GT utilizing a camera (including RealSense) to scan an intake line to inventory new items. The system gains accuracy as more and more items are scanned and the classification "learns" which items are part of your inventory.

Inventory system will increment quantity as items are a scanned/added.

IDF16

Paul langdon

Paul L. added photos to project Robotics Hive - Cloud Machine Learning

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Robotics Hive - Cloud Machine Learning

Using a hub (Intel Edison), individual robotic devices and machine learning in the cloud an intelligent virtual "hive" is created that can be used to increase validity of collected data, improve efficiency of action and act together as a collective.
The hub will have the ability to interact with the individual robots via BLE, WiFi, and RF allowing for interaction with a large number of robots/devices.

A prototype has been built using Sphero BB-8's that collect 2D mapping data, share it via BLE to the Edison hub and pass the data to AWS to build a real-time map. The bots work in concert validating each others mapping/coordinate data, being controlled autonomously by the "Hive" logic controller.

Future plans will include controlling drones and bots of all types via any interface by extending the hub.

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OnTheWall

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Created: 01/13/2017

MagicMirror+ for Intel Joule - Adding Face/Voice Recognition & Control using RealSense, Voice and...

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Keith Temple

DX Strategist at Intel

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Josh Bancroft (Intel)

Community Manager, Developer Relations. Geek. Husband. Father. Educator. Tinkerer. Studies the intersection of technology and humanity.

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Developer and Co-Owner of Chronosapien Interactive

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Tyler Lauretti

I am an undergraduate student at the University of Connecticut studying Management Information Systems and Computer Science.

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Space Between

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Created: 11/16/2015

Explore the ocean by controlling different sea creatures and machines as you discover what secret...

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Space Mines

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Created: 11/13/2015

Intel RealSense powered arcade game, controlled by using head and mouth

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Lilly Jones

My passion involves leveraging deep learning and machine learning for the geosciences.

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Felix Farley

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London, UK

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Working experience, as business analyst in banking with Capgemini, and as an embedded systems developer in the energy industry.

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Akash M

Hi,I'm Akash from Chennai pursuing B.E Computer Science (first year) in Sathyabama University

Chennai, Tamil Nadu, India

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Shadab Hussain

I Love to Learn to Grow

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Akash Chandran

I am a Student, very much passionate about Intel and Intel products. I like to code. I am a learner and also a developer.

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