Conf42_IoT_Dec2024_Building IoT Applications With Open Source
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The document discusses building IoT applications using various Apache projects and technologies, such as Apache NiFi, Kafka, and Flink, alongside AI and machine learning tools. It highlights the capabilities of the Raspberry Pi 5 with AI kits for applications like human pose estimation and showcases various devices, their specifications, and associated code. Additionally, the document emphasizes the importance of real-time data integration and processing for actionable insights in IoT environments.
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Conf42_IoT_Dec2024_Building IoT Applications With Open Source
- 1. Building IoT Applicationswith Open Source Tim Spann, Senior Sales Engineer
- 2. This week inApache NiFi, Apache Polaris, Apache Flink, Apache Kafka, ML, AI, Streamlit, Jupyter, Apache Iceberg, Python, Java, LLM, GenAI, Vector DB and Open Source friends. https://bit.ly/32dAJft AI + Streaming Weekly by Tim Spann
- 3. Tim Spann Twitter: @PaasDev// Blog: datainmotion.dev Senior Sales Engineer, Snowflake NY/NJ/Philly - Cloud Data + AI Meetups ex-Zilliz, ex-Pivotal, ex-Cloudera, ex-StreamNative, ex-Hortonworks. https://medium.com/@tspann https://github.com/tspannhw
- 4. ● Introduction ● Devices ●Iot Apps ● Messaging ● Edge AI ● Demos
- 5. This week inApache NiFi, Apache Flink, Apache Kafka, ML, AI, Streamlit, Jupyter, Apache Iceberg, Python, Java, LLM, GenAI, Vector DB and Open Source friends. https://bit.ly/32dAJft AI + All Data Weekly by Tim Spann
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- 8. Raspberry Pi 5+ AI Kit Raspberry Pi 5 with 8GB of RAM The AI Kit adds a neural network inference accelerator capable of 13 tera-operations per second (TOPS), which is pretty good for $70 US. Attached to this M.2 Hat is the Hailo-8L M.2 Entry-Level Acceleration Module which will give us our AI powers.
- 9. What is it? https://paperswithcode.com/task/pose-estimation 1,431papers with code Human Pose Estimation is a computer vision technique that locates and estimates things like eyes, ears, shoulders, joints in motion. It looks pretty cool and has some interesting applications for medical purposes and robotics. For me, it was one of the cool examples that runs on the AI Kit.
- 10. Pose Estimation byHailo 8L Each person is identified and represented by 17 keypoints Examples nose, eyes, ears, shoulders, elbows, wrists, hips, knees, and ankles. We are tracking eyes and more (updated today) https://github.com/hailo-ai/hailo_model_zoo/blob/master/docs/public_models/HAILO8/HAILO8_pose_estimation.rst https://github.com/tensorboy/centerpose https://softwaremill.com/human-pose-estimation-2023-guide/
- 11. Pose Estimation onHailo 8L Pose Estimation COCO Yolov8s_pose Hailo-8L https://github.com/ultralytics/ultralytics
- 12. HAILO Raspberry Pi5 Example Apps https://github.com/hailo-ai/hailo-rpi5-examples New: CLIP Zero Shot Inference Application
- 13. ● Just ReleasedAI Kit+ with 26 Tops ● NVIDIA Jetson Series ● Smart Cameras like OAKD ● Specialized Devices Alternatives Edge Vector Olympics Gold - NVIDIA Jetson AGX Orin - 275 TOPS, 2048-core, 64 GB RAM Silver - NVIDIA Jetson Xavier NX, 21 TOPS, 384-core, 8 GB RAM Bronze - Raspberry Pi 5, 13 TOPS, 4-core, 8 GB RAM
- 14. ● Containers ● 64bit processors and operating systems ● 8-64 GB Modern RAM ● Fast WiFi / Bluetooth ● 300+ Core GPUs ● eMMC Fast Storage ● TBs of SSD ● Examples: NVIDIA JETSON XAVIER NX, NVIDIA JETSON ORIN AGX Edge Computing Power - Edge Server
- 15. streamnative.io Device 1 -AdaFruit Funhouse • https://github.com/tspannhw/pulsar-adafruit-funhouse (MQTT) Raw JSON: {"pressure": 1009.08, "button_sel": "off", "pir_sensor": "off", "humidity": 36.0422, "temperature": 80.9526, "button_down": "off", "captouch6": "off", "captouch7": "off", "button_up": "off", "captouch8": "off", "light": 6990} Processor 240MHz / RAM 2+4MB
- 16. streamnative.io Device 2 -Raspberry Pi • https://github.com/tspannhw/FLiP-Pi-DeltaLake-Thermal Pulsar Protocol Raw JSON: Processor 1.5 GHz, 64-bit quad-core / RAM 2-8 GB LPDDR4-3200 SDRAM {"uuid": "thrml_zda_20220715182748", "ipaddress": "192.168.1.204", "cputempf": 108, "runtime": 0, "host": "thermal", "hostname": "thermal", "macaddress": "e4:5f:01:7c:3f:34", "endtime": "1657909668.7279365", "te": "0.0007398128509521484", "cpu": 1.8, "diskusage": "105078.0 MB", "memory": 9.0, "rowid": "20220715182748_fc4cbbb1-79da-4c1a-8991-78bd23c9f221", "systemtime": "07/15/2022 14:27:53", "ts": 1657909673, "starttime": "07/15/2022 14:27:48", "datetimestamp": "2022-07-15 18:27:52.492469+00:00", " temperature": 28.238, "humidity": 29.61, "co2": 992.0}
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- 18. © 2024 SnowflakeInc. All Rights Reserved 18 IoT to Cloud Data Platform Source Data Aggregate Data Analyze Data Share Data UNIVERSAL DATA DISTRIBUTION (Ingest, Transform, Deliver) Ingest Processors Ingest Gateway Router, Filter & Transform Processors Destination Processors
- 19. • Guaranteed delivery •Data buffering - Backpressure - Pressure release • Prioritized queuing • Flow specific QoS - Latency vs. throughput - Loss tolerance • Data provenance • Supports push and pull models • Hundreds of processors • Visual command and control • Over a 200 sources • Flow templates • Pluggable/multi-role security • Designed for extension • Clustering • Version Control DataFlows for Data Ingest, Movement and Routing
- 20. • Moving Binary,Unstructured, Image and Tabular Data • Enrichment • Universal Visual Processor • Simple Event Processor • Routing • Feeding data to Central Messaging • Support for modern protocols • Kafka Protocol Source/Sink • Pulsar Protocol Source/Sink The Power of Apache NiFi
- 21. NIFI 2.0 FEATURES MajorUpdates: ● Python Integration ● ParameterIZATION ● JDK 21+ ● Provenance / Data Lineage ● Rules Engine for Development Assistance ● Additional Azure Processors ● Integration with Zendesk, Slack, ● Database Tables as Schemas ● Amazon Glue Schema Registry ● OpenTelemetry Support DataFlow is built for Real-Time Integration and AI
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- 23. 23 What is ApacheNiFi? Apache NiFi is a scalable, real-time streaming data platform that collects, curates, and analyzes data so customers gain key insights for immediate actionable intelligence.
- 24. Address To Lat/Long ●Python 3.10+ ● geopy Library ● Nominatim ● OpenStreetMaps (OSM) ● openstreetmap.org/copyright ● Returns as attributes and JSON file ● Works with partial addresses ● Categorizes location ● Bounding Box https://github.com/tspannhw/FLaNKAI-Boston
- 25. 25 Flink SQL ● StreamingAnalytics ● Continuous SQL ● Continuous ETL ● Complex Event Processing ● Standard SQL Powered by Apache Calcite
- 26. HuggingFaceTB/SmolLM2-1.7B-Instruct Small language models(SLMs) NVIDIA Edge AI / Physical AI Edge Models Raspberry Pi Edge AI Edge Models
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- 32. Code - PoseEstimation https://bit.ly/4ebEPUJ
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- 34. /tspannhw/AIM-BecomingAnAIEngineer: AIM - BecomingAn AI Engineer https://bit.ly/3BV4IKX
- 35. What’s in theAir Tonight Mr. Milvus? https://bit.ly/4fQhBog
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