From leading IoT Protocols to Python Dashboarding_final

Oct 3, 20220 likes87 views

First i like to give an overview on common IoT Protocols: #CoAP (Constrained Application Protocol -> Close to HTTP / REST ) #MQTT ( Message Queue Telemetry Transport -> Pub/Sub with Broker -> Well defined Quality of Service -> Newest addition Eclipse Amlem (formerly the core of IBM Watson IoT platform) -> Eclipse Sparkplug -> Standardization of the topics and payloads -> Interoperability!) , #DDS (Data Distribution Service -> Pub/Sub without Broker -> Drones / Robotics) #LwM2M (Lightweight M2M -> Runs on Top of CoAP or MQTT -> standard sets of payloads for sensors) #zenoh (https://zenoh.io/ Pub/Sub Protocol -> combines the advantages of #DDS and #MQTT) #eclipsefoundation #apache #opensource #lightweight (+ some comments that this is not complete and does not encompass Industrial and Building Automation) Then I would like to show the leading edge IoT protocol Zenoh. Saving Zenoh Payload to Apache IoTDB. After that I would like to dive into Panel and the awesome capabilities of Apache ECharts.

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From leading edge IoT
Protocols to Python
Dashboarding an
End2End Journey
Lukas Ott - ApacheCon North America 2022

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●
Part of the community
●
By Day: Domain (Enterprise) Architect
●
By Night: Open Source Enthusiast
●
Pythonista
●
Copenhagen & Frankfurt
●
I connect People, Processes, Data and Machines
Who am I
@ot_luk
otluk

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Orchestrators
Data Visualization
Message Broker IIoT connector
Operating
System
Database
Data
Processing
Apache Projects in context of IoT (extract)

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IoT Protocols
Connecting IoT devices – OSI Model
1. Physical (Bluetooth, Ethernet, LTE, NFC, RFID, Wi-Fi, Z-Wave, Zigbee)
2. Data link (IEEE 802.15.5, LPWAN)
3. Network (IP, 6LoWPAN)
4. Transport (Transmission Control Protocol (TCP), User Datagram Protocol (UDP))
5. Session
6. Presentation
7. Application
https://en.wikipedia.org/wiki/OSI_model

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IoT Protocols – Application Layer
●
Advanced Message Queuing Protocol (AMQP)
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Constrained Application Protocol (CoAP)
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Data Distribution Service (DDS)
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Message Queue Telemetry Transport (MQTT)
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Lightweight Machine to Machine (LwM2M)

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And many more...
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Checkout 8-)
– https://plc4x.apache.org/
The universal protocol adapter for Industrial IoT

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Zenoh
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Zenoh unifies data in motion, data at rest and computations.
It elegantly blends traditional pub/sub with geo distributed storage,
queries and computations, while retaining a level of time and space
efficiency that is well beyond any of the mainstream stacks.
– Zero Overhead Pub/sub, Store/Query and Compute.

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A high-level app and dashboarding solution for Python
– Use the PyData tools and plotting libraries that you know and love
– Develop in your favorite editor or notebook environment and
seamlessly deploy the resulting application
– Stream data large and small to the front end
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Integrates for instance Apache Echarts

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Apache IoTDB
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IoT native database with high performance for data
management and analysis
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Checkout Apache Con Asia for more details

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Data Visualization
ZIP / PIP Stack
Database
IoT Protocol

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Github Repo: https://github.com/ottlukas/ApacheCon_2022_IoT

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MachinePulse at the November Open Hardware Meetup, Mumbai 2014MachinePulse

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Peripheral Programming using Arduino and Python on MediaTek LinkIt Smart 7688...MediaTek Labs

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Presentation of the Mainflulux team held In Portland at Embedded Linux Conference & OpenIoT Summit North America March 14 2018. IoT middleware platforms have become necessary building blocks of every complex vertical IoT solution. Traditionally, the platforms have been built to run in the cloud; wide availability and rich capabilities have driven the first wave of IoT adoption. As the scale and complexity of IoT projects have grown, however, the need to provide solutions that move to process to the network edge has also grown. Down-scaling cloud capabilities is complex in part because of the more modest capabilities of edge computing in typical deployment models. As a result, there are few open solutions that address this need. We introduce Mainflux (https://github.com/Mainflux/mainflux) - a IoT Platform for cloud and edge that can simultaneously scale-out to hundreds of nodes in the cloud but can also scale down to a modest RaspberryPi computer without changing a single line of code. This scalability is achieved thanks to careful architecture, the effectiveness of the Go programming language, and technology choices used in the implementation. We will discuss the platform, its use and application, and our work to bring core concepts from it to various open source projects including EdgeX. Repository for Mainflux open source and royalty-free IoT platform published under Apache-2.0 license, free download https://github.com/mainflux/mainflux Mainflux company official website: https://www.mainflux.com/

Mainflux - Hyperscalable Unified IoT PlatformSasa Klopanovic

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This document provides information on an IoT platform called Mainflux. It introduces Drasko Draskovic and Janko Isidorovic, the co-founders of Mainflux. It then describes Mainflux as an open-source and patent-free IoT platform that can be deployed on-premises or in the cloud. Mainflux uses microservices and is highly scalable. The document also discusses EdgeX Foundry, an open-source IoT edge framework, and provides an outline and links for more information on IoT platforms, devices, edge computing, on-premises vs cloud deployment, and unified IoT architectures.

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This session will be a detailed recount of the design, implementation, and launch of the next-generation Shutterstock Data Platform, with strong emphasis on conveying clear, understandable learnings that can be transferred to your own organizations and projects. This platform was architected around the prevailing use of Kafka as a highly-scalable central data hub for shipping data across your organization in batch or streaming fashion. It also relies heavily on Avro as a serialization format and a global schema registry to provide structure that greatly improves quality and usability of our data sets, while also allowing the flexibility to evolve schemas and maintain backwards compatibility. As a company, Shutterstock has always focused heavily on leveraging open source technologies in developing its products and infrastructure, and open source has been a driving force in big data more so than almost any other software sub-sector. With this plethora of constantly evolving data technologies, it can be a daunting task to select the right tool for your problem. We will discuss our approach for choosing specific existing technologies and when we made decisions to invest time in home-grown components and solutions. We will cover advantages and the engineering process of developing language-agnostic APIs for publishing to and consuming from the data platform. These APIs can power some very interesting streaming analytics solutions that are easily accessible to teams across our engineering organization. We will also discuss some of the massive advantages a global schema for your data provides for downstream ETL and data analytics. ETL into Hadoop and creation and maintenance of Hive databases and tables becomes much more reliable and easily automated with historically compatible schemas. To complement this schema-based approach, we will cover results of performance testing various file formats and compression schemes in Hadoop and Hive, the massive performance benefits you can gain in analytical workloads by leveraging highly optimized columnar file formats such as ORC and Parquet, and how you can use good old fashioned Hive as a tool for easily and efficiently converting exiting datasets into these formats. Finally, we will cover lessons learned in launching this platform across our organization, future improvements and further design, and the need for data engineers to understand and speak the languages of data scientists and web, infrastructure, and network engineers.

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This talk will explore how Raspberry Pi and Node-RED enable robust solutions for automation and control systems in both industrial and local applications. Leveraging open-source technology, these platforms can handle a wide range of tasks, from reading sensor data and managing actuators, to controlling devices through industrial communication protocols such as Modbus, RS485 ascii RTU etc. Node-RED’s message-driven architecture simplifies the creation of control logic, even for complex operations, while Raspberry Pi serves as a powerful and cost-effective alternative to traditional PLCs and IPCs. The integration of these tools allows for seamless data processing, remote communication, and the development of HMI interfaces both user-friendly or more traditiconal SCADA-like, making these technologies ideal for creating IIoT-native solutions. This presentation will focus on the technical capabilities, showing how these platforms can empower engineers and developers to build flexible and scalable automation solutions. https://www.sfscon.it/talks/raspberry-pi-and-node-red-open-source-tools-for-local-automation-and-industrial-iot-applications/

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Big data analysis has become much popular in the present day scenario and the manipulation of big data has gained the keen attention of researchers in the field of data analytics. Analysis of big data is currently considered as an integral part of many computational and statistical departments. As a result, novel approaches in data analysis are evolving on a daily basis. Thousands of transaction requests are handled and processed every day by different websites associated with e-commerce, e-banking, e-shopping carts etc. The network traffic and weblog analysis comes to play a crucial role in such situations where Hadoop can be suggested as an efficient solution for processing the Netflow data collected from switches as well as website access-logs during fixed intervals.

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Red Hat® Ceph Storage and Network Solutions for Software Defined InfrastructureIntel® Software

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This document discusses Intel's vision for software defined infrastructure (SDI) and provides examples of how their technology enables SDI. The key points are: 1. Intel's SDI vision is to provide dynamic, policy-driven management of compute, storage, and networking resources through abstraction, orchestration, and standards-based solutions. 2. Red Hat Ceph Storage is presented as an open source, scalable storage solution optimized for SDI through the use of commodity servers and SSDs. 3. Intel is contributing to open standards and growing an ecosystem of partners through their Network Builders program to accelerate the SDI transformation.

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Phoenix Data Conference - Big Data Analytics for IoT 11/4/17Mark Goldstein

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“Big Data for IoT: Analytics from Descriptive to Predictive to Prescriptive” was presented to the Phoenix Data Conference on 11/4/17 at Grand Canyon University. As the Internet of Things (IoT) floods data lakes and fills data oceans with sensor and real-world data, analytic tools and real-time responsiveness will require improved platforms and applications to deal with the data flow and move from descriptive to predictive to prescriptive analysis and outcomes.

Open NetworkingTal Lavian Ph.D.

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[OpenStack Day in Korea 2015] Keynote 2 - Leveraging OpenStack to Realize the...OpenStack Korea Community

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Drone data syncRubyCorporation, Inc

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This document discusses syncing drone log data from the drone's dataflash to cloud-based big data platforms using MQTT over WiFi or LTE. It proposes two architectures - one with an MQTT thread within the ArduPilot task, and one with a separate MQTT task. The goal is to accumulate drone log data in cloud platforms like AWS IoT to enable machine learning-based analysis of flight data and autopilot improvements.

Accelerating Apache Hadoop through High-Performance Networking and I/O Techno...DataWorks Summit/Hadoop Summit

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The document discusses accelerating Apache Hadoop through high-performance networking and I/O technologies. It describes how technologies like InfiniBand, RoCE, SSDs, and NVMe can benefit big data applications by alleviating bottlenecks. It outlines projects from the High-Performance Big Data project that implement RDMA for Hadoop, Spark, HBase and Memcached to improve performance. Evaluation results demonstrate significant acceleration of HDFS, MapReduce, and other workloads through the high-performance designs.

Internet of Things - protocols review (MeetUp Wireless & Networks, Poznań 21....Marcin Bielak

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- The document provides an overview of various Internet of Things (IoT) communication protocols including MQTT, HTTP/REST, and DDS. - It discusses the key aspects of MQTT including its publish-subscribe model, use of a message broker, lightweight design, and quality of service levels. HTTP/REST is described as using a client-server model with status codes and uniform interfaces. - The document also compares MQTT and HTTP/REST, noting MQTT is simpler, message-centric, and ideal for low-power IoT devices, while HTTP/REST is more complex, document-centric, and the standard web protocol.

Accelerate Big Data Processing with High-Performance Computing TechnologiesIntel® Software

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IPMI is dead, Long live RedfishBruno Cornec

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Redfish is an IPMI replacement standardized by the DMTF. It provides a RESTful API for server out of band management and a lightweight data model specification that is scalable, discoverable and extensible. (Cf: http://www.dmtf.org/standards/redfish). This presentation will start by detailing its role and the features it provides with examples. It will demonstrate the benefits it provides to system administrator by providing a standardized open interface for multiple servers, and also storage systems. We will then cover various tools such as the DMTF ones and the python-redfish library (Cf: https://github.com/openstack/python-redfish) offering Redfish abstractions.

Wearables and IoT StrategyAllSeen Alliance

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SDN, OpenFlow, NFV, and Virtual NetworkTim4PreStartup

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OPEN NETWORK OPERATING SYSTEM.PPTXAhmed59616

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ONOS is an open source SDN controller platform written in Java. It has a distributed core for high availability and scalability. ONOS uses northbound and southbound APIs to interface with applications and network devices. The presentation demonstrated ONOS' architecture and key features, and provided a live demo of interacting with ONOS through its GUI, CLI, and APIs. It also discussed how to develop applications for ONOS and get involved in the community.

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The document provides an agenda for understanding Hadoop which includes an introduction to big data, the core Hadoop components of HDFS and MapReduce, the Hadoop ecosystem, planning and installing Hadoop clusters, and writing simple streaming jobs. It discusses the evolution of big data and how Hadoop uses a scalable architecture of commodity hardware and open source software to process and store large datasets in a distributed manner. The core of Hadoop is HDFS for reliable data storage and MapReduce for parallel processing. Additional projects like Pig, Hive, HBase, Zookeeper, and Oozie extend the capabilities of Hadoop.

Community over Code EU 2024 - State of the Civet.pdfLukas Ott

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What is PLC4X? Overview of PLC4X’s journey from an idea to an Apache Top-Level Project. Past Development milestones including Java 11 support, S7 protocol completeness, and CAN improvements. Present Current capabilities and a demo of reading virtual Modbus using Python. Future Plans for EU CRA compliance, reproducible builds, and new user interfaces. Demo Showcasing current UI possibilities with Apache StreamPipes. Closing Q&A session. Key Highlights Development Journey: From initial concept to a stable release, involving community growth and protocol support. Technological Advancements: Java 11+, S7 protocol, CAN improvements, and Python integration. Future Plans: Focus on compliance, security, and enhancing user interfaces. Demos: Practical demonstrations of PLC4X’s capabilities and future UI developments.

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From leading IoT Protocols to Python Dashboarding_final

1. 1 From leading edge IoT Protocols to Python Dashboarding an End2End Journey Lukas Ott - ApacheCon North America 2022

2. 2 ● Part of the community ● By Day: Domain (Enterprise) Architect ● By Night: Open Source Enthusiast ● Pythonista ● Copenhagen & Frankfurt ● I connect People, Processes, Data and Machines Who am I @ot_luk otluk

3. 3 Orchestrators Data Visualization Message Broker IIoT connector Operating System Database Data Processing Apache Projects in context of IoT (extract)

4. 4 IoT Protocols Connecting IoT devices – OSI Model 1. Physical (Bluetooth, Ethernet, LTE, NFC, RFID, Wi-Fi, Z-Wave, Zigbee) 2. Data link (IEEE 802.15.5, LPWAN) 3. Network (IP, 6LoWPAN) 4. Transport (Transmission Control Protocol (TCP), User Datagram Protocol (UDP)) 5. Session 6. Presentation 7. Application https://en.wikipedia.org/wiki/OSI_model

5. 5 IoT Protocols – Application Layer ● Advanced Message Queuing Protocol (AMQP) ● Constrained Application Protocol (CoAP) ● Data Distribution Service (DDS) ● Message Queue Telemetry Transport (MQTT) ● Lightweight Machine to Machine (LwM2M)

6. 6 Advanced Message Queuing Protocol (AMQP) ● Popular Apache Frameworks: – https://activemq.apache.org/ – https://pulsar.apache.org/ – https://qpid.apache.org/index.html ● Properties – Brokered – Publish / Subscribe – Direct Exchange

7. 7 Message Queue Telemetry Transport (MQTT) ● Popular Apache Frameworks: – https://streampipes.apache.org/ – https://activemq.apache.org/ ● Properties – Tied to TCP – Publish / Subscribe – Brokered

8. 8 Data Distribution Service (DDS) ● Popular Apache Frameworks: – https://mynewt.apache.org/ – https://nuttx.apache.org/ ● Properties – Publish / Subscribe – Peer-to-Peer

9. 9 And many more... ● Checkout 8-) – https://plc4x.apache.org/ The universal protocol adapter for Industrial IoT

10. 10

11. 11 Zenoh ● Zenoh unifies data in motion, data at rest and computations. It elegantly blends traditional pub/sub with geo distributed storage, queries and computations, while retaining a level of time and space efficiency that is well beyond any of the mainstream stacks. – Zero Overhead Pub/sub, Store/Query and Compute.

12. 12 ● A high-level app and dashboarding solution for Python – Use the PyData tools and plotting libraries that you know and love – Develop in your favorite editor or notebook environment and seamlessly deploy the resulting application – Stream data large and small to the front end ● Integrates for instance Apache Echarts

13. 13 Apache IoTDB ● IoT native database with high performance for data management and analysis ● Checkout Apache Con Asia for more details

14. 14 Data Visualization ZIP / PIP Stack Database IoT Protocol

15. 15 Github Repo: https://github.com/ottlukas/ApacheCon_2022_IoT

16. 16

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From leading IoT Protocols to Python Dashboarding_final

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