The document provides information about a Node-RED workshop that will teach participants how to use Node-RED to interact with a Ciseco Slice of Radio device connected to a Raspberry Pi. Node-RED is a visual tool for wiring the Internet of Things that allows non-programmers to create IoT workflows by connecting pre-defined nodes without complex coding. The workshop will have participants use Node-RED to receive sensor data from the Slice of Radio and send it to online IoT platforms, as well as control wireless actuators. Background is provided on the software and hardware setup already installed on the Raspberry Pis to be used. Step-by-step exercises are outlined to start Node-RED and create a simple flow
This document provides an overview of prototyping with Node-RED, including setting up a boilerplate Node-RED application on Bluemix, editing code locally, deploying the application, adding new nodes, calling APIs to get weather data from the Weather Company and storing it in Cloudant, and then displaying the data in a Google chart. Key steps include downloading starter code, adding node packages to package.json, pushing the application to Bluemix, making API calls to get data, parsing the response to JSON, trimming the data, storing it in a Cloudant database, and retrieving the data to display in a chart.
The document discusses the need for an open horizontal platform to enable interoperability in the Internet of Things (IoT). It describes some of the current challenges with separate vertical application stacks that use different protocols and APIs, trapping devices, code, user experiences, and data in isolated "silos". The proposed solution is an open platform that enables any application to connect to any connected thing via any M2M protocol, using common data models, semantic models, and a model-driven architecture to achieve interoperability. Key aspects of this open platform approach include breaking down silos, enabling "network effect" applications, and achieving "write once, run anywhere" software interoperability.
Here are some ideas for IoT projects you could build using Node-RED and MQTT:
- Home automation system to control lights, appliances, locks etc. using sensors and switches.
- Smart garden with soil moisture sensors, temperature/humidity sensors to automate watering and send alerts.
- Weather station to collect data from sensors like temperature, pressure, rainfall and display on a dashboard.
- Smart pet feeder that dispenses food only when pet is detected by a motion sensor.
- Smart parking system with ultrasonic sensors to detect available spots and guide drivers.
- Smart trash can that sends alerts when full to schedule emptying.
- Smart home security with door/window sensors,
Building the Internet of Things with Thingsquare and Contiki - day 1, part 3Adam Dunkels
This document provides information on building IoT hardware prototypes and discusses typical IoT hardware components and properties. It covers topics like rapid prototyping vs production hardware, microcontrollers, memory sizes, I/O, radio hardware options, power sources, operating systems vs custom firmware, software challenges, and wireless connectivity issues. The document also introduces Contiki, an open-source operating system designed for IoT devices, and discusses some of its features.
Building the Internet of Things with Thingsquare and Contiki - day 1, part 1Adam Dunkels
How to build the Internet of Things - what is an Internet of things device and how do we connect it? This is the first Thingsquare IoT workshop slide deck.
Building the Internet of Things with Thingsquare and Contiki - day 1, part 2Adam Dunkels
How to build the Internet of Things - what is an Internet of things device and how do we connect it? This is the second Thingsquare IoT workshop slide deck.
Using IO Visor to Secure Microservices Running on CloudFoundry [OpenStack Sum...IO Visor Project
As microservices grow, traditional firewall rules based on network ACLs are no longer scalable and fall short of providing fine-grained enforcement. Group Based Policy (GBP) is a flexible policy language that allows users to specify policy enforcement based on intent, independent of network infrastructure and IP addressing. Using micro-segmented virtual domains, administrators can define policies at a centralized location and use IO Visor technology for distributed enforcement. This provides infrastructure independent rules, template-based policy definitions, and scale-out policy enforcement for a solution that secures and scales with microservices. This session will be presented by members of the IO Visor community and will cover how IO Visor technology can be used to define and enforce GBP. The discussion will also cover using GBP for cloud foundry application spaces where microservices are deployed and need scalable, efficient security policies.
Sensor networks are a fundamental building block of Internet of Things (IoT) applications, as they provide the interface to the physical world. In fact, many techniques used for resource-constrained IoT devices originated in the research area of Wireless Sensor Networks (WSNs). This talk will present the transition from research prototypes to standardized Internet protocols, give an overview how sensor networks are connected today (with a practical hands-on), and discuss a few challenges that need to be addressed in the future.
The document discusses Mininet, an open source network emulator used for testing SDN ideas. It provides an overview of Mininet 1.0 and its functional fidelity before describing plans for Mininet 2.0 to improve performance fidelity through techniques like resource isolation, network invariants, and reproducible experiments. The document uses the example of DCTCP traffic to demonstrate how network invariants can validate emulator results.
Banog meetup August 30th, network device property as codeDamien Garros
Managing Network Device Properties as Code:
Device configuration templates have simplified a lot of things for the network industry but most people are still managing their device properties (aka variables) manually which is very tedious and error prone. This talk will present a new approach to generate and manage network device properties easily using infrastructure as code principles.
Californium: Scalable Cloud Services for the Internet of Things with CoAPMatthias Kovatsch
The Internet of Things (IoT) is expected to interconnect a myriad of devices. Emerging networking and backend support technology not only has to anticipate this dramatic increase in connected nodes, but also a change in traffic patterns. Instead of bulk data such as file sharing or multimedia streaming, IoT devices will primarily exchange real-time sensory and control data in small but numerous messages. Often cloud services will handle these data from a huge number of devices, and hence need to be extremely scalable to support conceivable large-scale IoT applications. To this end, we present a system architecture for IoT cloud services based on the Constrained Application Protocol (CoAP), which is primarily designed for systems of tiny, low-cost, resource-constrained IoT devices. Along with our system architecture, we systematically evaluate the performance of the new Web protocol in cloud environments. Our Californium (Cf) CoAP framework shows 33 to 64 times higher throughput than high-performance HTTP Web servers, which are the state of the art for classic cloud services. The results substantiate that the low overhead of CoAP does not only enable Web technology for low-cost IoT devices, but also significantly improves backend service scalability for vast numbers of connected devices.
IPSN 2009 tutorial: http://ipsn.acm.org/2009/tutorials.htm
Title: IP-based Sensor Networks: a Hands-on Tutorial (uIP)
Speakers: Adam Dunkels, Fredrik Osterlind, Nicolas Tsiftes (SICS)
Time: April 16,2009 Thursday 3:00PM~5:00PM
IP-based sensor networks are a rapidly emerging hot topic in both academia and the industry.
The open source uIP stack from the Contiki operating system, first released in 2001, is used in IP-enabled products and systems from hundreds of companies, ranging from pico-satellites, airplanes, and car engines, to worldwide freighter container tracking systems, ship control systems, and oil boring and pipeline monitoring systems. In October 2008 Cisco Systems released uIPv6, the world's smallest fully compliant IPv6 stack, for Contiki.
During this tutorial, participants will get started with building IP-based sensor networks with Contiki and uIP, and get hands-on experience with developing, compiling, and running IP-based software on sensornet hardware, setting up IP networking to the sensor network, and getting performance metrics (power, throughput, latency) from a running network.
We use a combination of Tmote Sky and Sentilla JCreate motes as the hardware platform. We provide Tmote Skys and JCreates for participants to borrow during the tutorial.
To avoid installation of compilers and tools, participants will use the Instant Contiki development environment, a complete development environment in a single-file download consisting of a VMWare virtual machine with all Contiki software development tools installed: http://www.sics.se/contiki/instant-contiki.html
About the authors: Jerome Tollet is Distinguished Engineer working in the Cisco Chief Technical and Architecture Office (CTAO) with a specific focus on Datacenter / Container Networking, Policy and Security. Jerome is an active member of FD.io. He is leading networking-vpp project as well as other VPP related projects.
Ed Warnicke is a Distinguished Consulting Engineer in the Chief Technology and Architecture Office (CTAO) office at Cisco Systems. He has been working for over a decade in many areas of networking and Open Source. He has been a member of the OpenDaylight TSC since its inception and currently serves as a committer elected member of the OpenDaylight TSC. He is a founding TSC member at ONAP.
This document discusses Network Address Translation (NAT) and how it allows private IP networks to connect to the Internet. It covers the problems of IP address exhaustion and depletion of IPv4 addresses. NAT enables private networks using unregistered IP addresses to connect to the public network by translating private IP addresses to public IP addresses. The document defines key NAT terms and describes how NAT is implemented on a router with inside and outside interfaces to translate packet headers. It also covers the types and advantages of NAT, including connecting multiple computers to the Internet using a single public IP address, as well as some disadvantages like added delay.
Network Address Translation (NAT) allows devices on a private network to use public IP addresses to access the Internet. NAT translates private IP addresses to public IP addresses to conserve the limited number of public addresses. There are three main types of NAT: static NAT assigns a public IP to a device; dynamic NAT uses a pool of public IPs; and port address translation uses ports of a single public IP for multiple private devices. NAT provides advantages like acting as a firewall and allowing unlimited private devices to share a single public IP. However, it also causes some applications to work less effectively and complicates troubleshooting when IP addresses change.
This document summarizes a presentation about achieving container networking without overlays by routing container IP addresses directly in the datacenter network. The presentation argues this approach reduces complexity, increases reliability, and avoids vendor lock-in. It then demonstrates routing containers in a spine-leaf fabric topology using Docker, Quagga routing on servers, and dynamic routing protocols. Container IPs are distributed as host routes throughout the network, providing connectivity, isolation, capacity scaling and high availability.
As computer network grow larger and more complex, there is a need for a new simple kind of approach to configure them. SDN has emerged as promising network architecture. It takes the control plane away from the individual nodes and centralize the network control by utilizing a flow based traffic management. Mininet is a cost effective and an efficient way to emulate and study SDN.This paper presents a study of programmable networks with basics of Mininet.
This document discusses using Kubernetes to build a domestic 5G NFV platform in Taiwan. It begins with an introduction of the speaker and overview of NFV and its impact. It then covers the advantages and challenges of deploying VNFs on Kubernetes, including networking and compute/management issues. It introduces some telco Kubernetes solutions from Nokia, SK Telecom, and Huawei. It also presents Taiwan's MOEA 5G project NFVI platform based on the open source X-K8S solution from ITRI, addressing networking and compute/management challenges. Finally, it shares an example of an end-to-end EPC system integration on the platform.
Workflows are a key component of server side of IoT solution along with Analytics, Rule Engine and IoT device management. IoT focused Workflow tools draw their inspiration of classical workflow tools that exist in market, but focus more on IoT use cases. For example they are able to connect with IoT devices using IoT specific protocols like CoAP or MQTT. Node-RED is a visual tool for wiring together hardware devices, APIs and online services in new and interesting ways. It’s build by IBM Emerging Technology team from group for IoT, though it’s not limited only to IoT.
Hands-on, Build an IoT app using IBM Bluemix, NodeRED and Simulated Sensor - ...WithTheBest
This document discusses building an Internet of Things (IoT) application using IBM Bluemix, NodeRED, and simulated sensors. It provides examples of IoT devices like BB8 Sphero and Intel Edison and how IoT is currently used in smart homes, connected automobiles, healthcare, smart waste management, intelligent traffic monitoring, and agriculture. It then demonstrates building an app that gets data from a simulated sensor and draws a graph to analyze the data. The conclusion discusses building an app combining IoT with visual recognition by analyzing images from a Raspberry Pi camera.
This document provides an introduction and overview of exercises for a workshop on using Node-RED, a visual tool for wiring together hardware devices, APIs, and online services for Internet of Things (IoT) projects. The workshop will teach participants how to build a basic web server and chat application using Node-RED's flow-based programming. Key aspects covered include installing and starting Node-RED, creating simple flows to inject and output test data, setting up HTTP requests and responses to build a static website, using templates and functions to add dynamic and styled content, and handling form submissions to return user input to the Node-RED flow. The exercises build up skills for retaining state across flows, integrating input and output, and developing a
Mehr und schneller ist nicht automatisch besser - data2day, 06.10.16Boris Adryan
Das Gesetz der großen Zahlen gilt immer: Die statistische Sicherheit nimmt mit der Anzahl der Datenpunkte immer zu, sofern die Datennahme fair erfolgt. Leider kostet das Sammeln der Daten oftmals Geld, und so ist man vor allem im Bereich der Sensorik (Stichwort: Internet der Dinge) gezwungen, sinnvolle Kompromisse einzugehen. In diesem Vortrag fasse ich die Erkenntnisse eines Projekts zusammen, in dem die Datenanalytik zeigte, dass man zukünftig nur 60% der ausgebrachten Sensoren wirklich braucht. Auch muss es nicht immer Echtzeit-Analyse sein: Mit einer auf den Business-Case abgestimmten Datenstrategie lassen sich unnötige Ausgaben vermeiden.
02 Raspberry Pi GPIO Interface on Node-RED (Some correction)Mr.Nukoon Phimsen
The document discusses using the Raspberry Pi's GPIO pins to control hardware interfaces with Node-RED. It provides examples of creating Node-RED flows to:
1. Control an LED by setting a GPIO pin as a digital output and toggling it on and off.
2. Control LED brightness using PWM by setting a GPIO pin as a PWM output and changing the duty cycle.
3. Read input from a binary sensor by setting a GPIO pin as a digital input and reading its state.
4. Read temperature from a 1-Wire temperature sensor connected to the Raspberry Pi's 1-Wire bus using a Node-RED 1-Wire node.
Flow Base Programming with Node-RED and Functional Reactive Programming with ...Sven Beauprez
To overcome callback hell in node.js, the presentation gives an overview of the advantages of using Flow Based Programming with node-RED and Functional Reactive Programming with Bacon.js.
The presentation was made for IoTBE (Internet of Things Belgium) user group to prove that node.js can actually be used for the Internet of Things (IoT).
Node-RED and Minecraft - CamJam September 2015Boris Adryan
This workshop uses the Node-RED framework as development tool for JavaScript. Building on functionality available for generic programming challenges, we’re going to use the communication standard TCP (Transmission Control Protocol) to interact with the Minecraft API (Application Programming Interface). The material is aimed at people who have had first experience with the Minecraft API on a Raspberry Pi (say, using Python), who now want to understand what's going on behind the scenes and what TCP, API and all those other acronyms mean. It also introduces flow-based programming concepts.
PHYSICAL COMPUTING WITH RGB LED OR MATRIX
Today we enter a topic in programming called
embedded computing with the internet; we code a
RGB LED light on a Arduino board with a breadboard
on which we switch off or on the light by a browser
on an android device with our own web server and
their COM or socket protocols too.
Node red & IoT - IEDC Hardware Club, April 8th 2016Sebin Benjamin
Node-RED is a flow-based development tool for visual programming developed originally by IBM for wiring together hardware devices, APIs and online services as part of the Internet of Things. Node-RED provides a web browser-based flow editor, which can be used to create JavaScript functions.
RGB LED in Arduino with an Oscilloscope
• Generating QR Code
• 3D Printing
• Web Video Cam
• Digi Clock with Real Time Clock
• Android SeekBar to Arduino LED Matrix
There are three main topics in here. First technologies – simply put, this part is mainly for early adopters. It’s about coding, developing toys, plugging in kettles on the web (and we and many others actually did that!).
The second part is about new ideas, prototyping and new technologies that are in the lab. It’s about research papers, and software philosophy, and about researchers worldwide. Third part is about end-users and products.
This document provides instructions for installing and using the INET framework for OMNeT++ simulations. It describes how to automatically or manually install INET, explore example simulations, familiarize yourself with OMNeT++, and create a new project using INET components. A wireless networking tutorial is presented that demonstrates creating a simple wireless network simulation by defining a topology and configuration file. The document also provides guidance on running the simulation and analyzing results using sequence charts and output visualization tools in the OMNeT++ IDE.
1. The document discusses using an Arduino board to control an LED light via a web server and browser. It provides code to set up an HTTP server on the Arduino that can turn the LED on or off by sending GET requests from a browser to specific URLs.
2. The code creates an TIdCustomHTTPServer object to set up the web server on the Arduino. It configures the server port and IP address. GET requests to URLs like 127.0.0.1:8000/LED will turn the LED on, while 127.0.0.1:8000/DEL will turn it off.
3. The document provides background on topics like HTTP, TCP/IP, IP addresses
Lab Handson: Power your Creations with Intel Edison!Codemotion
by Francesco Baldassarri - Come along and play with Intel Edison, for the Internet of Things? Learn about the Developer Kit for IoT, chose your preferred environment and test it – or test all the possibilities? We will be providing information and hands on training for developers interested in testing our solutions in C/C++, Javascript, Arduino, Wyliodrin and Python. Just bring you laptop and we will help you to get started. We will also provide information about our Cloud Analytics platform, and test hardware samples with the Grove Starter Kit – Intel IoT Edition. Visit us anytime and start making! What will you make?
We code a RGB LED light on the Arduino board and a breadboard on which we switch off or on the light by a browser on an android device with our own web server and their COM protocols.
The Arduino is what is known as a Physical or Embedded Computing platform, which means that it is an interactive system that through the use of hardware, firmware and software can interact with its environment.
The document describes two experiments conducted using the OPNET simulation tool. Experiment 1 involves simulating a TCP network using different congestion control mechanisms and analyzing OSPF routing. Experiment 2 compares the bus and star network topologies by creating networks with each in OPNET and collecting statistics on traffic and delay. The objectives are to get familiar with OPNET, study TCP algorithms, simulate OSPF routing, and understand the pros and cons of different topologies. Tasks for each experiment are described in detail, including how to set up the simulations, configure nodes and links, select statistics, and run the simulations.
Build your own discovery index of scholary e-resourcesMartin Czygan
Providing discovery systems for eresourcesis essential for library services today.
Commercial search engine indices have been a widely used solution in recent years. In
contrast, running an own discovery service is undoubtedly a challenging task but promises
full control over data processing, enrichment, performance and quality. Building an own
aggregated index of eresourcesincludes gathering the right mix of data sources, clearing
licensing issues, and negotiating data availability. Technically, these threads are resumed by
data harvesters, filters and workflow orchestration tools.
The Raspberry Pi is a series of small single-board computers developed Raspberry Pi
Foundation to promote the teaching of basic computer science in schools and in developing
countries. A Raspberry pi is a mini computer with IO pins so we can interface devices to
develop an embedded board
This document provides instructions on how to get started with Node-RED for connecting Arduino to the internet. It explains that Node-RED is a visual tool for wiring hardware, APIs and online services. It then provides step-by-step instructions on installing Node-RED, adding serial and social media nodes to send sensor data to Twitter, ThingSpeak and IBM Watson. It also includes shortcodes for installing common Node-RED nodes like for Google Charts, MySQL and Alexa.
This document welcomes the reader to a Node-RED Twitter analysis workshop and provides an introduction and overview of Node-RED. It discusses that Node-RED provides a drag-and-drop interface for creating "flows" of events to build applications and connects IoT devices. It also provides some examples of basic Node-RED nodes like Inject and Debug nodes, and encourages the reader to open the workshop URL and build flows together. Finally, it lists additional Node-RED resources and the presenter's contact information.
Hardwear.io 2018 BLE Security Essentials workshopSlawomir Jasek
Bluetooth Low Energy (Smart, 4) is recently gaining more and more traction as one of the most common and rapidly growing IoT technologies. Unfortunatelly the prevalence of technology does not come with security. Alarming vulnerabilities in BLE smart locks, medical devices and banking tokens are revealed day by day. And yet, the knowledge on how to comprehensively assess them seems very uncommon.
In this workshop you will get familiar with the basics of BLE security. We will work on a dedicated, readily available BLE hardware nRF devkit device. You will learn how to program and flash it yourself, using special web interface and ready templates. Such approach allows to better understand how things work “under the hood”, experiment with different options, and then secure the hardware properly.
From attacker’s perspective, we will cover among others: sniffing, spoofing, MITM, replay and relay.
Having enough time, we will play with a collection of vulnerable smart locks, sex toys and other devices.
The document provides an introduction and overview of connecting Intel Edison devices to the DeviceHub IoT platform. It discusses:
1) Setting up a DeviceHub account and adding a project and device.
2) Installing necessary libraries on the Intel Edison like libmraa to control GPIO pins and connect to WiFi/MQTT.
3) Examples of sending sensor data from the Edison to DeviceHub including string, analog, and digital values and viewing the data in real-time graphs on the DeviceHub dashboard.
Serial Data from Arduino to Raspberry Pi to MySQL using CoAP ProtocolSanjay Kumar
This document discusses getting sensor data from an Arduino Uno and sending it to a Raspberry Pi via UART serial communication. It then explains how to run a CoAP server on the Raspberry Pi to make the sensor data available via a GET request. Finally, it describes saving the sensor values from the Arduino in a MySQL database on the Raspberry Pi and accessing the stored data through a web browser.
Linux Format was the UK's first Linux-specific magazine, and as of 2013 was the best-selling Linux title in the UK. It is also exported to many countries worldwide. It is published by Future plc.
Topic: Low cost computing using the Raspberry PI and other single board computing platforms. Overview of the growing low cost computing environment and demo of basic configuration of the Raspberry PI and Arduino for home and business projects.
Similar to Node-RED and getting started on the Internet of Things (20)
A brief lesson on what constitutes computational decision making, from simple regression via various classification methods to deep learning. No maths, only basic concepts to teach the lingo of machine learning to a lay audience.
Development and Deployment: The Human FactorBoris Adryan
Thingmonk 2017: End-to-end IoT solutions are often highly integrated. Even small changes to the UX of a product can have profound impact on hardware requirements, while physical constraints such as battery capacity can dictate software architecture. A holistic understanding of IoT is key to efficient implementation, the “T-shaped engineer” the star in every development team. Contrast this to intellectual silos and matrix organisation, and you may see why especially large companies fail to move quickly into IoT. Similar issues strike the application of IoT. Deploying a solution in the enterprise is just a cost factor if processes are not adjusted to leverage the connected device and its data. However, changes in process often affect companies across their entire organisational structure. This can require a change of mindsets, making the success of an IoT solution depending on the human factor.
IoT-Daten: Mehr und schneller ist nicht automatisch besser.
Über optimale Sampling-Strategien, wie man rechnen kann, ob IoT sich rechnet, und warum es nicht immer Deep Learning und Real-Time-Analytics sein muss. (Folien Deutsch/Englisch)
Industry of Things World - Berlin 19-09-16Boris Adryan
Dr. Boris Adryan gave a talk on the impact of IoT analytics on development budgets. He discussed that IoT data problems are often not as complex as perceived and do not necessarily require "big data" solutions or specialists. Basic data storage and processing can often be done cost-effectively using standard tools. True challenges lie in extracting useful insights, which may require specialized machine learning approaches. Not all analytics need to be real-time. The appropriate solution depends on the use case and desired insights.
Just because you can doesn't mean that you should - thingmonk 2016Boris Adryan
Big data! Fast data! Real-time analytics! These are buzzwords commonly associated with platform offerings around IoT.
Although the Law of large numbers always applies, just because you can deploy more sensors doesn't automatically mean that you should. After all, they cost money, bandwidth, and can be a pain to maintain. On the example of the Westminster Parking Trial, I'd like to show how analytics on preliminary survey data could have reduced the number of deployed sensors significantly.
A similar logic goes for fast and real-time analytics. While being advertised as killer features, many people new to IoT and analytics are not even aware that they might get away with batch processing. On the example of flying a drone, I'd like to discuss for which use cases I'd apply edge processing (on the drone), stream or micro-batch analytics (when data arrives at the platform) or work on batched data (stored in a database).
Plattformen für das Internet der Dinge, solutions.hamburg, 05.09.16Boris Adryan
Talk in German. Abstract: Prospective end users new to IoT are overwhelmed with the vast number of offerings around IoT data brokerage, storage and analysis. This talk exemplifies some of the challenges that have to be met in real-world deployments, and why there is no one-size-fits-all IoT solution. We conclude that IoT solution providers in many cases need to consider PaaS solutions with customer-specific modifications.
My talk about data and information models for IoT, how ontologies can establish the relationship between IoT devices, and how Eclipse Vorto could accommodate ontological information. Briefly features Eclipse Smarthome.
My keynote from the Location Intelligence session at Geo-IoT World in Brussels in May 2016. How location is one of many important context variables in the interpretation of sensor data.
My talk at Smart IoT London. About adding 'context' for data analytics in the consumer IoT, touching on machine learning, hidden variables, and UX/UI of communicating probabilities.
Eclipse IoT is the M2M/IoT ecosystem provided by the Eclipse Foundation. It offers open source software solutions for end devices, gateway systems and backends. Notable Eclipse IoT projects are Kura (a turn-key ready gateway e.g. for the Raspberry Pi), Eclipse SmartHome (integral part e.g. of openHAB) or the MQTT/CoAP suits Mosquitto, Paho, Californium, Wakama and Leshan. There are also solutions for process plants and manufacturing, as well as tools for large-scale device management.
This document discusses the relationship between probability, machine learning, and user experience in consumer IoT devices. It notes that individual apps are not enough and that intelligent devices need to have contextual awareness and conversational abilities based on things like schedule, location, and preferences. However, acquiring and applying knowledge through machine learning comes with challenges around explaining probabilistic concepts and predictions to users, and ensuring that conversational systems do not feel repetitive, disruptive, or intrusive. Quantitative thinking will become more important as life becomes more dependent on probabilities modeled through data and algorithms.
Presented at the Open Data Science meetup London (January 2016). To fully leverage the potential of the Internet of Things requires the exchange of information between devices. Unfortunately, most data remains in vendor silos. This talk explains how the life sciences have tackled similar issues, and why closed, vendor-specific systems may miss out.
Potentially creepy human-computer interactions in the future of the consumer IoT. Lots of raw data need to be analysed and are represented as result of machine learning exercises. However, consumers are likely scared of probabilities. How can UX address these issues?
EclipseCon France 2015 - Science TrackBoris Adryan
Software is increasingly playing a big part in scientific research, but in most cases the growth is organic. The life time of research software is often as short as the duration of a postdoctoral contract: Once the researcher moves on, custom-written niche code is frequently not well documented, components are not reusable, and the overall development effort is likely lost.
This is a case study in looking at the evolution of software for research in the field of genomics within my research group at the Department of Genetics at Cambridge University. While our research questions changed over the past decade, we moved from Perl code and regular expressions to R and statistical analysis, and from there to agent-based simulations in Java. Not only will I discuss the languages and tools used as well as the processes and how they have evolved over the years. It also covers the factors that influence the nature of the growth, such as funding, but also how 'open source' as a default has changed our development work. We also take a look into the future to see how we predict the software usage will grow.
Also, in presenting the problems and discussing possible solution, this talk will look at the role institutions play in helping address these issues. In particular the Software Sustainability Institute (SSI, http://software.ac.uk/) works in the UK to promote the development, maintenance and (re)use of research software.
The Eclipse Foundation, with the Science Working Group, works to facilitate software sharing and reuse. How can organisations like the SSI and Eclipse align their strategies and activities for maximum effect?
Data Science London - Meetup, 28/05/15Boris Adryan
Slides from my @ds_ldn talk about Ontologies in the Internet of Things. Note that this is a short version of a talk that I presented earlier this month on O'Reilly Webcasts, still viewable for a while at: http://www.oreilly.com/pub/e/3365
O'Reilly Webcast: Organizing the Internet of Things - Actionable Insight Thro...Boris Adryan
- A biologist is interested in large, unstructured IoT data to gain insights from connections between different data points, similar to how biologists study connections between biological entities.
- Currently the IoT lacks common data formats, ontologies to provide context to things, and data repositories, limiting analytical flexibility and insights that can be gained.
- Biologists overcame similar problems by developing standards like gene ontologies, metadata requirements, and public data repositories, enabling knowledge inference from large, diverse datasets.
- Key concepts from biology that could help the IoT include developing ontologies to define thing functions, processes, and localizations in order to organize knowledge and enable inferencing across the large, diverse data generated by the Io
What the IoT should learn from the life sciencesBoris Adryan
What the Internet of Things should learn from the life sciences. About the utility of open data, ontologies and public repositories as routinely used in the academic life science, but rarely in the IoT.
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Node-RED and getting started on the Internet of Things
1. CamJam! Workshop: Node-RED and getting started on the Internet of Things
- 1 -
http://nodered.org
Tinamous
.com
http://shop.ciseco.co.uk
! Node-RED
is
a
visual
tool
for
wiring
the
Internet
of
Things
(IoT).
Node-‐RED
is
platform-‐independent,
but
has
been
developed
with
small
computers
such
as
the
Raspberry
Pi
in
mind.
! Traditional
IoT
development
can
be
very
technical:
Access
to
the
GPIO
and
other
hardware
requires
skills
in
C
or
assembler,
output
of
data
to
web
services
or
sending
tweets
and
emails
requires
the
use
of
complex
APIs.
Node-RED
takes
care
of
the
technicalities
and
lets
you
concentrate
on
the
logic
of
your
workflow.
! While
most
programming
in
Node-‐RED
is
done
visually
using
pre-‐defined
functions
(“nodes”),
any
additional
functionality
can
be
added
in
JavaScript.
WORKSHOP
CONTENT:
In
this
workshop,
we’re
going
to
use
Node-‐RED
to
interact
with
a
Ciseco
Slice
of
Radio.
This
is
a
low-‐cost
radio
shield
that
enables
the
Raspberry
Pi
to
receive
messages
from
wireless
sensors
(such
as
temperature
or
light
level)
and
send
messages
to
change
wireless
actuators
(such
as
a
relay
or
light).
We
will
also
discuss
how
to
send
sensor
data
to
IoT
platforms
on
the
Internet.
2. CamJam! Workshop: Node-RED and getting started on the Internet of Things
- 2 -
Technical
background:
For
this
workshop,
you
will
find
a
Raspberry
Pi
with
a
Slice
of
Radio
and
Node-‐RED
already
installed.
While
the
installation
of
both
hardware
and
software
is
relatively
easy,
it
would
be
difficult
to
include
this
step
within
the
time
constraints
of
the
exercise.
For
completeness,
this
is
what’s
happened
to
a
fresh
and
up-‐to-‐date
Raspian
installation
on
your
SD
card:
1. Remove
any
system
I/O
through
the
serial
port
(/dev/ttyAMA0)
from
/etc/inittab
and
/boot/cmdline.txt.
See
e.g.
http://openmicros.org/index.php/articles/94-ciseco-product-documentation/raspberry-pi/283-setting-up-my-raspberry-pi
2. Install
node.js
and
npm
(e.g.
by
sudo
apt-get
install
nodejs
npm)
3. Clone
Node-‐RED
from
Github
and
install
as
described
here:
http://nodered.org/docs/getting-started/installation.html
4. Install
the
node
that
encapsulates
communication
with
the
serial
port
by
issuing:
sudo
npm
install
serialport
5. The
default
Midori
browser
has
its
quirks.
We’re
using
Chromium,
installed
by:
sudo
apt-get
install
chromium
Note:
To
leverage
the
power
of
Node-‐RED,
consider
installing
nodes
for
email
or
raw
GPIO
access
as
well.
The
latter
is
described
here:
http://nodered.org/docs/hardware/raspberrypi.html
1)
Exercise:
Starting
Node-RED
as
Raspberry
Pi
user
Node-‐RED
can
be
installed
as
a
service
on
the
Raspberry
Pi,
i.e.
as
a
program
that’s
always
executed
when
your
Pi
is
running.
However,
this
is
only
useful
if
you
want
to
commit
your
Pi
for
this
particular
use
as
it
can
consume
considerable
resources.
For
everyone
else,
it’s
recommended
to
start
Node-‐RED
only
when
needed:
1. Open
the
LXTerminal
to
see
a
console
that
allows
you
to
enter
Linux
commands.
2. Change
into
the
Node-‐RED
directory
by
issuing
“cd
node-‐red”.
3. Start
Node-‐RED
by
typing
“node
red.js”.
You
should
now
see
Node-‐RED
starting
up
–
that
may
take
a
few
seconds:
Congratulations.
You’re
now
ready
for
the
exercises.
3. CamJam! Workshop: Node-RED and getting started on the Internet of Things
- 3 -
Node-‐RED
represents
a
server
on
the
basis
of
node.js
and
interacts
with
the
user
through
a
graphical
user
interface.
It
can
be
reached
on
port
1880.
To
use
Node-RED,
open
a
web
browser
and
direct
it
to
http://localhost:1880
It’s
useful
to
remember
that
Node-‐RED
acts
as
a
server
in
your
entire
network.
That
is,
if
your
Raspberry
Pi’s
internal
IP
address
is
something
like
192.x.x.x,
every
computer
in
your
network
can
open
the
Node-‐RED
GUI
through
http://192.x.x.x:1880.
You
can
make
your
system
more
restricted/secure
by
following
the
configuration
advice
on
http://nodered.org/docs/configuration.html.
2)
Exercise:
Your
first
flow
The
best
way
to
explain
“a
flow”
is
by
creating
one.
In
this
mini
flow,
we’re
going
to
inject
a
value
into
our
debug
window
(refer
to
page
1
for
what
the
GUI
elements
are
called).
1. Open
the
Chromium
Web
Browser.
It
supports
JavaScript
better
than
the
default
Midori
browser.
2. In
the
address
line,
enter
localhost:1880.
You
will
then
see
the
Node-‐RED
GUI.
3. Drag
and
drop
an
“inject”
node
from
the
nodes
library
into
the
flow
editor
(once
you’ve
chosen
the
inject
node,
you
should
see
some
general
explanation
about
its
functionality
in
the
info
pane
–
no
need
to
read
that
now).
4. Drag
and
drop
a
“debug”
node
from
the
nodes
library
into
the
flow
editor.
5. Create
a
pipe
between
the
inject
and
debug
nodes
by
drawing
a
connection
between
their
small
grey
rounded
rectangles.
6. Change
from
the
info
pane
to
the
debug
pane
(upper
right).
7. Deploy
(=start)
your
flow.
8. Once
deployed,
press
the
left
blue
rectangle
that’s
attached
to
the
inject
node.
Check
what’s
happening
in
the
debug
pane.
3)
Exercise:
Topics
and
payloads
While
it
is
possible
to
push
complicated
data
structures
through
pipes
in
Node-‐RED,
the
default
is
a
(topic
/
payload)
tuple,
which
could
be
interpreted
as
subject
and
body
of
an
email.
1. Double-‐click
your
inject
node.
2. Change
the
properties
of
your
inject
node
so
that
it
sends
a
string
“the
message”
as
payload
and
“the
envelope”
as
topic.
3. Deploy
your
flow
and
check
for
the
outcome
in
the
debug
window.
4. CamJam! Workshop: Node-RED and getting started on the Internet of Things
- 4 -
4)
Exercise:
Receiving
data
from
the
serial
port
Triggering
a
flow
through
the
inject
node
is
obviously
of
limited
utility.
Let’s
interact
with
the
real
world!
The
Slice
of
Radio
is
a
small
module
that
enables
the
Raspberry
Pi
to
send
and
receive
radio
frequency
messages.
Once
connected
to
the
GPIO,
the
radio
communicates
with
the
serial
(tx,
rx)
pins.
In
our
workshop,
you
will
receive
wireless
radio
messages
from
a
temperature
sensor.
In
Node-‐RED,
the
“serial”
node
facilitates
serial
communication
with
the
sensor.
1. Drag
and
drop
a
serial
node
into
the
flow
editor.
You
can
call
it
“radio”.
2. Connect
the
serial
node
to
your
debug
node
you’ve
used
in
the
last
script.
3. Configure
the
serial
node
to
talk
to
serial
port
/dev/ttyAMA0
(the
standard
Linux
name
of
the
serial
port
on
the
Raspberry
Pi),
expect
9600
baud
8N1
communication
(“how
a
character
is
encoded”)
and
split
your
input
after
50
milliseconds.
4. Deploy
your
flow
and
wait
for
your
first
radio
message
(up
to
30
sec).
5)
Exercise:
Use
JavaScript
to
extract
what’s
useful
from
LLAP
messages
Take
a
deep
breath.
Now
you’re
going
learn
exciting
technical
stuff
and
JavaScript!
A
radio
has
no
notion
of
the
physical
beginning
or
end
of
a
transmission.
However,
we
know
that
our
Ciseco
temperature
sensor
speaks
LLAP,
or
Lightweight
Logical
Application
Protocol1.
Every
LLAP
sentence
is
12
characters
long.
That
means,
unless
there
is
a
lot
of
radio
chatter
about,
every
burst
of
12
characters
should
be
a
complete
LLAP
message.
An
exemplary
message
we’re
looking
out
for
is
following
the
convention
aT1TMPA23.5-,
meaning
the
message
has
started
(“a”),
it
comes
from
sensor
T1,
and
the
temperature
(“TMPA”)
is
23.5,
plus
a
spacer
(“-‐“):
12
bytes.
While
Ciseco
radios
can
send
any
length
of
information
(yes,
even
the
transcript
of
Miles’
recent
speech
at
the
IoT
14
Meeting),
for
their
own
sensor
line
they’ve
chosen
to
encode
the
output
in
LLAP.
1
http://shop.ciseco.co.uk/llap/
&
http://openmicros.org/index.php/articles/85-‐llap-‐
lightweight-‐local-‐automation-‐protocol/297
5. CamJam! Workshop: Node-RED and getting started on the Internet of Things
- 5 -
In
this
workshop,
we
are
going
to
store
our
most
recent
temperature
readings
to
a
platform
called
Tinamous
(https://tinamous.com).
There
are
also
other
platforms,
all
for
slightly
different
use
cases2.
A
common
format
for
sensor
data
transmission
to
these
platforms
is
MQTT,
which
follows
a
topic
/
payload
convention.
1. Drag
and
drop
a
“switch”
node
into
the
flow
editor.
Configure
it
in
a
way
that
only
messages
with
a
TMPA
statement
get
forwarded
and
other
messages
are
disregarded:
2. Drag
and
drop
a
“function”
node
into
the
flow
editor.
3. Connect
the
switch
node
to
your
radio,
and
the
function
node
to
the
switch
node
so
that
it
sits
in
between
the
switch
and
the
debug
node.
4. Open
the
function
node
and
write
some
JavaScript
code
that
separates
the
LLAP
message
into
the
sensor
name
(for
topic)
and
the
temperature
(as
payload).
(Note:
You
don’t
have
to
type
all
the
green
things.
These
are
just
comments
to
explain
a
little
bit
what’s
going
on
in
the
code.
Concentrate
on
the
things
that
are
not
green.)
5. Deploy
your
workflow
and
check
what’s
going
on
in
your
debug
pane.
2
See
http://logic.sysbiol.cam.ac.uk/?p=1473
for
a
review
for
some
working
with
Node-‐RED
6. CamJam! Workshop: Node-RED and getting started on the Internet of Things
- 6 -
Comments
and
further
experiments:
msg.payload
and
msg.topic
are
available
at
the
start
of
every
function
node!
You
may,
by
now,
have
realised
that
there
are
not
only
TMPA
messages,
but
also
AWAKE,
SLEEPING
and
BATT…
If
you’re
a
keen
JavaScript
programmer,
write
some
code
that
avoids
the
switch
node
and
does
all
the
filtering
in
the
function
node.
6)
Exercise:
Connect
to
Tinamous
through
MQTT
1. Drag
and
drop
a
“MQTT”
output
node
into
the
flow
editor.
2. Connect
the
MQTT
node
to
the
extract
function
node.
3. Configure
the
MQTT
node.
We
have
previously
set
up
a
camjam
account
on
Tinamous
and
defined
“PiXX”
devices
(where
XX
is
your
table
number;
here:
13).
These
are
the
details
you
will
need
to
enter
in
the
configuration
of
your
MQTT
broker:
(Our
very
creative
password
is
camjam2camjam,
username:
PiXX
“dot”
camjam).
In
the
MQTT
node
itself
you
specificy
as
topic
/Tinamous/V1/Measurements/0/Field1
(most
of
this
is
Tinamous
nomenclature
–
look
at
their
MQTT
online
help
for
details).
4. Deploy
your
workflow
and
visit
https://camjam.tinamous.com
in
your
web
browser.
Quick
Excursion:
Viewing
your
data
on
Tinamous
1. Point
your
browser
to
https://camjam.tinamous.com
(camjam
/
camjam2camjam).
2. Click
on
the
small
line
chart
icon
next
to
your
device
(e.g.
Pi13).
7. CamJam! Workshop: Node-RED and getting started on the Internet of Things
- 7 -
3. Click
on
the
Field1
that
we’ve
designated
as
temperature.
4. Voila!
7)
Exercise:
Control
stuff
through
Node-RED
In
the
next
step,
we’re
going
to
control
an
actuator.
That’s
the
smart
word
for
a
thing
that
does
something
in
response.
Actuators
are:
lights,
relays,
switches,
etc.
In
our
example,
every
Raspberry
Pi
in
the
workshop
is
going
to
have
a
number
assigned.
Your
number
translates
into
a
position
in
an
Adafruit
NeoPixel
Ring.
The
NeoPixel
Ring
is
connected
to
a
XinoRF
wireless
Arduino-‐clone
(it’s
the
same
microcontroller
that’s
part
of
the
Ciseco
RasWik
Wireless
Inventor
Kit),
which
runs
some
code
to
listen
to
your
radio
messages
and
trigger
a
response.
We’ve
set
up
the
XinoRF
so
that
it
responds
to
your
LLAP
messages
of
the
format
aRFttrrggbb-,
where
tt
is
your
table
number
(01..12),
and
rrggbb
is
the
hexadecimal
code
of
your
desired
colour.
So
FF0000
is
“red”,
00FF00
is
“green”
and
0000FF
is
“blue”.
1.
Drag
an
outgoing
“serial”
node
into
your
project
and
connect
it
to
an
inject
node.
2. Configure
the
inject
node
so
that
it
injects
a
payload
in
aRFttrrggbb-‐
format.
3. Deploy
your
workflow
and
try
to
identify
your
position
in
the
NeoPixel
Ring.
8. CamJam! Workshop: Node-RED and getting started on the Internet of Things
- 8 -
Would
it
not
be
wonderful
to
translate
the
temperature
into
a
colour
tone?
You
can
do
it!
1. Write
yourself
some
code
(or
use
a
switch
node!)
that
sends
a
different
colour
code
for
different
temperatures.
Note:
As
soon
as
many
groups
start
to
automate
this
step,
we’re
going
to
have
a
dozen
Raspberry
Pis
fire
a
radio
message
once
the
temperature
sensor
has
triggered
their
flow.
You
can
prevent
the
XinoRF
from
being
overrun
by
inserting
a
“delay”
node
with
a
random
delay
(say,
between
0
and
1000
milliseconds)
before
the
outgoing
radio
node.
8)
Additional
Exercises…
…in
your
own
time
Node-‐RED
is
an
incredibly
powerful
framework
that
allows
you
to
do
things
in
very
little
time.
The
official
directory
of
flows
donated
to
the
community
is
here
http://flows.nodered.org
and
they
can
easily
be
imported
by
copying
&
pasting
the
JSON-‐formatted
code.
A
few
suggestions
and
examples
that
I
have
described
over
the
past
months
are
here:
! Triggering
Node-RED
with
drawings:
The
Aestheticodes
project
uses
a
QR
code
like
method
to
encode
information
in
beautiful
drawings.
Draw
a
picture,
take
a
photograph
with
your
mobile
and
trigger
the
debug
node
doing
that:
http://logic.sysbiol.cam.ac.uk/?p=1514
! Control
Minecraft
with
Node-RED:
The
Minecraft
Pi
Edition
can
be
controlled
through
Python,
but
that
may
not
be
easily
accessible
for
everyone.
With
a
MQTT-‐to-‐Minecraft
bridge,
the
Node-‐RED
inject
nodes
can
be
used
to
control
Steve:
http://logic.sysbiol.cam.ac.uk/?p=1499
! Got
an
AirPi
shield?
Monitor
your
room
climate
with
AirPi
and
Node-RED:
http://logic.sysbiol.cam.ac.uk/?p=1423