IoT with Apache MXNet and Apache NiFi and MiniFi
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1) The document discusses using Apache MXNet for industrial IoT applications. MiniFi ingests camera images and sensor data at the edge and runs Apache MXNet to recognize objects in images. The data is then stored in Hadoop. 2) It describes using Apache MXNet on edge devices like the Raspberry Pi and Nvidia Jetson TX1 to perform tasks like image recognition from cameras and sensors. 3) The document provides information on setting up Apache MXNet on various IoT devices and edge servers to enable machine learning and deep learning capabilities for industrial IoT applications.
IoT with Apache MXNet and Apache NiFi and MiniFi
- 1. 1 © Hortonworks Inc. 2011–2018. All rights reserved. © Hortonworks, Inc. 2011-2018. All rights reserved. | Hortonworks confidential and proprietary information. Apache MXNet For IIoT Timothy Spann, Solutions Engineer Hortonworks @PaaSDev
- 2. 2 © Hortonworks Inc. 2011–2018. All rights reserved. Disclaimer • This document may contain product features and technology directions that are under development, may be under development in the future or may ultimately not be developed. • Technical feasibility, market demand, user feedback, and the Apache Software Foundation community development process can all effect timing and final delivery. • This document’s description of these features and technology directions does not represent a contractual commitment, promise or obligation from Hortonworks to deliver these features in any generally available product. • Product features and technology directions are subject to change, and must not be included in contracts, purchase orders, or sales agreements of any kind. • Since this document contains an outline of general product development plans, customers should not rely upon it when making a purchase decision.
- 3. 3 © Hortonworks Inc. 2011–2018. All rights reserved. What do we want to do? • MiniFi ingests camera images and sensor data • MiniFi executes Apache MXNet at the edge • Run Apache MXNet Inception to recognize objects in image • Apache NiFi stores images, metadata and enriched data in Hadoop
- 4. 4 © Hortonworks Inc. 2011–2018. All rights reserved. Aggregate all data from sensors, drones, logs, geo-location devices, images, machines and social feeds. Collect: Bring Together Mediate point-to-point and bi-directional data flows, delivering data reliably to Apache HBase, Apache Hive, HDFS, Slack and Email. Conduct: Mediate the Data Flow Parse, filter, join, transform, fork, query, sort, dissect; enrich with weather, location, image recognition and object detection with Apache MXNet. Curate: Gain Insights
- 5. 5 © Hortonworks Inc. 2011–2018. All rights reserved. IIoT Multiple devices, protocols, frameworks, languages, data types, sensors and networks Protocols • MQTT • HTTPS / SSL (REST/JSON) • OPC UA • CoAP • AMQP • JSON • XML • CSV • Raw Text • Images (JPEG, PNG) • Raw Data Streams Data Types Sensors • Cameras • Temperature/Humidity • IR • Proximity • Motion Sensors • GPS Protocols • NVidia Jetson TX1 • Raspberry Pi • Arduino • TS-7800 V2 • ESP8266 • DragonBoard 410c • BeagleBone Black
- 6. 6 © Hortonworks Inc. 2011–2018. All rights reserved. HDF Data-In-Motion Platform – with HDF 3.1 GA Release
- 7. 7 © Hortonworks Inc. 2011–2018. All rights reserved. Apache MiNiFi • NiFi lives in the data center. Give it an enterprise server or a cluster of them. • MiNiFi lives as close to where data is born and is a guest on that device or system “Let me get the key parts of NiFi close to where data begins and provide bidirectional data transfer"
- 8. 8 © Hortonworks Inc. 2011–2018. All rights reserved. Edge Intelligence with Apache MiNiFi Guaranteed delivery Data buffering ‒ Backpressure ‒ Pressure release Prioritized queuing Flow specific QoS ‒ Latency vs. throughput ‒ Loss tolerance Data provenance Recovery / recording a rolling log of fine-grained history Designed for extension Different from Apache NiFi Design and Deploy Warm re-deploys Key Features
- 9. 9 © Hortonworks Inc. 2011 – 2017. All Rights Reserved Java Agent C++ Agent Multi Cloud HDP Clusters HBase Druid YARN HDFS Hive Weather Location Sensors
- 10. 10 © Hortonworks Inc. 2011 – 2017. All Rights Reserved http://mxnet.incubator.apache.org/ • Cloud ready • Experienced team (XGBoost) • AWS, Microsoft, NVIDIA, Baidu, Intel backing • Apache Incubator Project • Run distributed on YARN • In my early tests, faster than TensorFlow. • Runs on Raspberry PI, NVidia Jetson TX1 and other constrained devices • Great documentation • Gluon • Great Python Interaction • Model Server Available • ONNX Support • Now in Version 1.1! • Great Model Zoo https://mxnet.incubator.apache.org/how_to/cloud.html https://github.com/apache/incubator-mxnet/tree/1.1.0/example
- 11. 11 © Hortonworks Inc. 2011 – 2017. All Rights Reserved Apache MXNet Pre-Built Models • CaffeNet • SqueezeNet v1.1 • Inception v3 • Single Shot Detection (SSD) • VGG19 • ResidualNet 152 • LSTM http://mxnet.incubator.apache.org/model_zoo/index.html https://github.com/dmlc/mxnet-model-gallery
- 12. 12 © Hortonworks Inc. 2011 – 2017. All Rights Reserved Apache MXNet Pre-Built Models • CaffeNet • SqueezeNet v1.1 • Inception v3 • Single Shot Detection (SSD) • VGG19 • ResidualNet 152 • LSTM http://mxnet.incubator.apache.org/model_zoo/index.html https://github.com/dmlc/mxnet-model-gallery
- 13. 13 © Hortonworks Inc. 2011 – 2017. All Rights Reserved Apache MXNet Raspberry Pi Setup pip install --upgrade pip pip install scikit-image git clone https://github.com/tspannhw/mxnet_rpi.git sudo apt-get update -y sudo apt-get install python-pip python-opencv python-scipy python-picamera -y sudo apt-get -y install git cmake build-essential g++-4.8 c++-4.8 liblapack* libblas* libopencv* git clone --recursive https://github.com/apache/incubator-mxnet.git mxnet --branch 1.1.0 cd incubator-mxnet export USE_OPENCV = 0 make pip install mxnet==1.1.0 https://mxnet.incubator.apache.org/tutorials/embedded/wine_detector.html
- 14. 14 © Hortonworks Inc. 2011 – 2017. All Rights Reserved Apache MXNet Raspberry Pi Setup curl --header 'Host: data.mxnet.io' --header 'User-Agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10.11; rv:45.0) Gecko/20100101 Firefox/45.0' --header 'Accept: text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8' --header 'Accept-Language: en- US,en;q=0.5' --header 'Referer: http://data.mxnet.io/models/imagenet/' --header 'Connection: keep- alive' 'http://data.mxnet.io/models/imagenet/inception-bn.tar.gz' -o 'inception-bn.tar.gz' -L tar -xvzf inception-bn.tar.gz cp Inception-BN-0126.params Inception-BN-0000.params
- 15. 15 © Hortonworks Inc. 2011–2018. All rights reserved. Apache MXNet Running on IoT Devices https://community.hortonworks.com/articles/83100/deep-learning-iot-workflows-with-raspberry-pi-mqtt.html https://github.com/tspannhw/mxnet_rpi https://community.hortonworks.com/articles/146704/edge-analytics-with-nvidia-jetson-tx1- running-apac.html
- 16. 16 © Hortonworks Inc. 2011–2018. All rights reserved. GPU Powered Nodes with NVidia Jetson TX1 Running Apache MXNet https://community.hortonworks.com/articles/146704/edge-analytics-with-nvidia-jetson-tx1-running-apac.html
- 17. 17 © Hortonworks Inc. 2011–2018. All rights reserved. Using Apache MXNet on Devices with Sensors and Intel Movidius https://community.hortonworks.com/articles/176932/apache-deep-learning-101-using-apache-mxnet-on- the.html
- 18. 18 © Hortonworks Inc. 2011–2018. All rights reserved. IIoT Processing Data Acquisition Edge Processing Real Time Stream Analytics Rapid Application Development IoT ANALYTICS CLOUD Acquire Move Routing & Filtering Deliver Parse Analysis Aggregation Modeling
- 19. 19 © Hortonworks Inc. 2011–2018. All rights reserved. Run everywhere Orchestration Queueing Simple Event Processing Deep Learning Framework Enabling Record Processing Schema Management Open Source Components Edge Ingest Data Buffering Device Integration
- 20. 20 © Hortonworks Inc. 2011–2018. All rights reserved. Questions?
- 21. 21 © Hortonworks Inc. 2011–2018. All rights reserved. Contact https://github.com/tspannhw/ApacheDeepLearning101 https://community.hortonworks.com/users/9304/tspann.html https://dzone.com/users/297029/bunkertor.html https://www.meetup.com/futureofdata-princeton/ https://twitter.com/PaaSDev https://community.hortonworks.com/articles/155435/using-the-new-mxnet-model-server.html @PaasDev
- 22. 22 © Hortonworks Inc. 2011–2018. All rights reserved. Hortonworks Community Connection Read access for everyone, join to participate and be recognized • Full Q&A Platform (like StackOverflow) • Knowledge Base Articles • Code Samples and Repositories
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Editor's Notes
- #7: Flow Management – the key is edge to anywhere with intelligence. This means the crux of it is being able to connect anything with anything else, from anywhere. This is a guiding principle for the roadmap on this aspect of data in motion. Stream Processing – the key is time to insight. This means the crux of this is to be able to extract actionable information as quickly and easily as possible. This is the guiding principle for this aspect of data in motion. Enterprise services – goes without saying, this has to all work together, efficiently, reliable, effectively.
- #9: TALK TRACK Apache MiNiFI is a sub project of Apache NiFi. It is designed to solve the difficulties of managing and transmitting data feeds to and from the source of origin, enabling edge intelligence to adjust dataflow behavior with bi-directional communication, out to the last mile of digital signal. It has a very small and lightweight footprint*, and generate the same level of data provenance as NiFi that is vital to edge analytics and IoAT (Internet of Any Thing) It’s a little bit diferent from NiF in that is is not a real-time command and control interface – in fact – the agent, unlike NiFi doesn’t have a built in UI at all. MiNiFi is designed for design and deploy situations and for “warm re-deploys”. HDF 2.0 supports the java version of the MiNiFi agent, and a C++ version is coming soon as well.
- #11: Adam Gibson DL4J/Skymind has spoken at my meetup Deep Learning A Practitioner’s Approach – I consulted with them on the Spark/Hadoop chapter.
- #22: Data Science Cheat Sheet - https://hortonworks.app.box.com/file/234426455072 White Paper - https://hortonworks.app.box.com/file/151460926459 Videos - https://www.youtube.com/user/Hortonworks/feed?activity_view=1