Slides from my talk at NDC IoT day in Oslo 2014-11-06.
Code is available on GitHub at https://github.com/codeplanner/NDC-InternetOfThingsDay-2014-11-06
Developing io t applications in the fog a distributed dataflow approachNam Giang
In this paper we examine the development of IoT applications from the perspective of the Fog Computing paradigm, where computing infrastructure at the network edge in devices and gateways is leverage for efficiency and timeliness. Due to the intrinsic nature of the IoT: heterogeneous devices/resources, a tightly coupled perception-action cycle and widely distributed devices and processing, application development in the Fog can be challenging. To address these challenges, we propose a Distributed Dataflow (DDF) programming model for the IoT that utilises computing infrastructures across the Fog and the Cloud. We evaluate our proposal by implementing a DDF framework based on Node-RED (Distributed Node-RED or D-NR), a visual programming tool that uses a flow-based model for building IoT applications. Via demonstrations, we show that our approach eases the development process and can be used to build a variety of IoT applications that work efficiently in the Fog.
Fog computing extends cloud computing to the edge of a network, closer to IoT devices. It helps process data locally instead of sending everything to the cloud, reducing latency, bandwidth usage, and security risks. Fog computing can provide localized services for applications like healthcare and smart grids, improving response times, privacy, and insights while lowering costs compared to relying solely on cloud infrastructure. The main challenges involve authentication across gateways and devices, and protecting privacy while still obtaining useful aggregate data.
Improving Web Siste Performance Using Edge Services in Fog Computing Architec...Jiang Zhu
We consider web optimization within Fog Computing context. We apply existing methods for web optimization in a novel manner, such that these methods can be combined with unique knowledge that is only available at the edge (Fog) nodes. More dynamic adaptation to the user’s conditions (eg. network status and device’s computing load) can also be accomplished with network edge specific knowledge. As a result, a user’s webpage rendering performance is improved beyond that achieved by simply applying those methods at the webserver or CDNs.
XMPP a Unified Fabric for Internet Of ThingsRikard Strid
The document discusses Unified Communication for IoT provided by Clayster. It introduces the founders, Rikard Strid and Peter Waher, and their visions for normalizing technologies and enabling rapid application development for IoT. Clayster provides platforms and frameworks to unify data from different sources using XMPP as the core protocol, and provides analytics, provisioning, applications, and management capabilities. The document describes several use cases customers use Clayster's technology for, such as energy management, smart homes, and building automation.
The Fog Computing Meetup in May 2016 aimed to further Fog Computing development through education and networking. Fog Computing is defined as using end-user devices to handle storage, communication, and management near the edge of networks rather than in centralized cloud servers. Potential discussion topics included applications of Fog Computing in different industries and technologies, as well as comparisons to cloud computing. Key questions focused on the technical benefits and challenges of Fog Computing adoption and when the ecosystem would be ready to scale.
The document discusses future visions for the Internet of Things (IoT) including fog computing and cloud computing. It provides a brief history of IoT beginning in 1999 and describes the layers of an IoT system from things to gateways to middleware to applications. It then defines cloud computing models including Software as a Service, Platform as a Service, and Infrastructure as a Service. The document introduces fog computing as providing similar functionalities as cloud computing but being physically closer to IoT devices. It concludes by thanking the audience.
Presentation of ThingStudio for the course of PervasiveSystem 2017 Sapienza university of Rome
LinkedIn: https://www.linkedin.com/in/alessio-tirabasso-44a023140/
GitHub: https://github.com/alessiotirabasso
Developing io t applications in the fog a distributed dataflow approachNam Giang
In this paper we examine the development of IoT applications from the perspective of the Fog Computing paradigm, where computing infrastructure at the network edge in devices and gateways is leverage for efficiency and timeliness. Due to the intrinsic nature of the IoT: heterogeneous devices/resources, a tightly coupled perception-action cycle and widely distributed devices and processing, application development in the Fog can be challenging. To address these challenges, we propose a Distributed Dataflow (DDF) programming model for the IoT that utilises computing infrastructures across the Fog and the Cloud. We evaluate our proposal by implementing a DDF framework based on Node-RED (Distributed Node-RED or D-NR), a visual programming tool that uses a flow-based model for building IoT applications. Via demonstrations, we show that our approach eases the development process and can be used to build a variety of IoT applications that work efficiently in the Fog.
Fog computing extends cloud computing to the edge of a network, closer to IoT devices. It helps process data locally instead of sending everything to the cloud, reducing latency, bandwidth usage, and security risks. Fog computing can provide localized services for applications like healthcare and smart grids, improving response times, privacy, and insights while lowering costs compared to relying solely on cloud infrastructure. The main challenges involve authentication across gateways and devices, and protecting privacy while still obtaining useful aggregate data.
Improving Web Siste Performance Using Edge Services in Fog Computing Architec...Jiang Zhu
We consider web optimization within Fog Computing context. We apply existing methods for web optimization in a novel manner, such that these methods can be combined with unique knowledge that is only available at the edge (Fog) nodes. More dynamic adaptation to the user’s conditions (eg. network status and device’s computing load) can also be accomplished with network edge specific knowledge. As a result, a user’s webpage rendering performance is improved beyond that achieved by simply applying those methods at the webserver or CDNs.
XMPP a Unified Fabric for Internet Of ThingsRikard Strid
The document discusses Unified Communication for IoT provided by Clayster. It introduces the founders, Rikard Strid and Peter Waher, and their visions for normalizing technologies and enabling rapid application development for IoT. Clayster provides platforms and frameworks to unify data from different sources using XMPP as the core protocol, and provides analytics, provisioning, applications, and management capabilities. The document describes several use cases customers use Clayster's technology for, such as energy management, smart homes, and building automation.
The Fog Computing Meetup in May 2016 aimed to further Fog Computing development through education and networking. Fog Computing is defined as using end-user devices to handle storage, communication, and management near the edge of networks rather than in centralized cloud servers. Potential discussion topics included applications of Fog Computing in different industries and technologies, as well as comparisons to cloud computing. Key questions focused on the technical benefits and challenges of Fog Computing adoption and when the ecosystem would be ready to scale.
The document discusses future visions for the Internet of Things (IoT) including fog computing and cloud computing. It provides a brief history of IoT beginning in 1999 and describes the layers of an IoT system from things to gateways to middleware to applications. It then defines cloud computing models including Software as a Service, Platform as a Service, and Infrastructure as a Service. The document introduces fog computing as providing similar functionalities as cloud computing but being physically closer to IoT devices. It concludes by thanking the audience.
Presentation of ThingStudio for the course of PervasiveSystem 2017 Sapienza university of Rome
LinkedIn: https://www.linkedin.com/in/alessio-tirabasso-44a023140/
GitHub: https://github.com/alessiotirabasso
The document discusses how the growth of IoT devices and data is creating challenges around scaling, security, storage, and analytics. It predicts that there will be trillions of connected devices generating zettabytes of data by 2020. This massive amount of data will be costly and inefficient to store and process in the cloud alone. The document proposes that a "fog computing" model, which processes data at the edge using gateways and local device intelligence, will be needed to efficiently handle the scale of IoT data. Cooperation between organizations on standards, APIs, and education will be important to support fog computing architectures for IoT.
Fog computing is a model that processes and stores data near network edge devices rather than solely in cloud data centers. It extends cloud computing to the edge of the network to provide low latency services to end users. Key characteristics include proximity to users, dense geographical distribution, and support for mobility. Fog computing is well-suited for applications requiring real-time processing like industrial automation and IoT networks of sensors. It helps improve quality of service by bringing services closer to users and enabling real-time analytics on distributed data sources.
This document discusses the growth of the Internet of Things (IoT) and the rise of fog computing. It notes that:
- 50 billion devices are expected to be internet-connected by 2020, up from 12.5 billion in 2010, representing rapid growth.
- Most of the world's data is now being generated by IoT devices like sensors and smart objects, creating big data challenges.
- Fog computing is a new distributed computing model that processes data at the edge of the network, near the data sources, to help address these challenges. It extends cloud computing out to endpoints and access networks.
- Open source software will be important for fog computing and IoT, as it has been
This document discusses using JavaScript and the Internet of Things (IoT) for bioinformatics applications. It notes that JavaScript is well-suited for bioinformatics due to its use in web development, data visualization, and its ability to run on both the front-end and back-end. The IoT connects physical devices to the internet and is already web-based. The document proposes a collaborative, open-source workflow system called IoB that uses JavaScript and connects databases and other "things" to enable sharing of reusable analysis components.
Performance Analysis of Internet of Things Protocols Based Fog/Cloud over Hig...Istabraq M. Al-Joboury
The document analyzes the performance of Internet of Things (IoT) protocols like MQTT and HTTP when used with fog and cloud computing over high traffic networks. The research tests response time, throughput, and packet loss for different IoT protocols (MQTT with QoS 0 and 1) and transmission methods (fog vs cloud) using realistic IoT sensors and traffic loads. The results showed MQTT generally had lower response times and higher throughput than HTTP, especially when using fog computing rather than cloud. MQTT QoS 1 also outperformed QoS 0 in most tests. Overall, fog computing with MQTT QoS 1 was found to have the best performance for high traffic IoT applications.
Fog computing provides compute, storage, and networking services between edge devices and cloud data centers. It helps address issues with cloud computing like latency, limited bandwidth, and data protection. Fog computing, located at the network edge, can process real-time, geographically distributed data from millions of IoT devices like vehicles, factories, and infrastructure. This localized processing allows analysis and action on IoT data within seconds, addressing needs that cloud alone cannot meet. Fog enhances cloud computing for IoT scenarios by extending cloud capabilities closer to the edge.
This document is a presentation by Naveen P. V. on the emerging trend of fog computing. It begins with an introduction that defines fog computing as operating on network ends rather than centralized cloud, placing transactions and resources at the edge of the cloud. It notes fog computing reduces bandwidth needs and costs while improving efficiencies. Examples are given where fog computing is useful, such as applications requiring low latency, distributed applications, and large control systems. Trends discussed include use in connected cars, smart grids, smart cities, and healthcare. The impact in the next 5 years is predicted to include increased mobile-based transportation interventions and adoption of smart metering to reduce emissions. Naveen expresses interest in working on smart cities and network
An increasing number of Consumer and Internet Internet of Things applications require some form of edge computing characterised by low latency, peer-to-peer communication, and mobility. Fog computing has recently emerged as the paradigm to address the needs of edge computing in IoT applications. Fog computing complements Cloud computing to allow the design and implementation of IoT systems that scale better, are more reactive and in which local communication and decision is enabled whenever possible.
This presentation introduces the key concepts behind Fog Computing, compare and contrast it with Cloud Computing and explain how the VORTEX platform enables Fog computing architectures.
The Internet of Things (IoT) is defined by embedded computing devices endowed with cross-network connectivity. This era of computing has huge potential for connected enterprises and consumers, and already has many successful use cases. IoT systems encompass many types of connectivity patterns, proprietary systems and network types. Just as the Web plays a significant role in providing an open, interoperable, easily deployable framework for today’s enterprise systems, it is not surprising the Web will provide similar benefits to IoT. New Web standards have allowed enterprises to extend their internal real-time systems over the firewall in a natural, unimpeded fashion to provide real-time, dynamic information to their customers and partners to ensure consistency and efficiency. These same Web standards can and should be applied to IoT systems to obtain advantages such as global reach, ease of deployment, economies of scale, ease of development, etc. We will discuss this evolution and explore the further impact of the Web on IoT.
IBM Bluemix Paris Meetup #27 20171219 - introIBM France Lab
This document summarizes an event discussing artificial intelligence held at Le Village by CA on December 19, 2017. It included presentations on AI in 2025, deploying virtual assistants at scale, using natural language processing to enrich text and conversations, and probabilistic AI. The event was hosted by IBM's France Lab and discussed IBM's cognitive capabilities including reasoning, understanding, learning, and interacting with unstructured data like language. It also covered IBM's cloud and AI infrastructure options for deploying applications and workloads.
During this presentation, KeyLines creator Joe Parry introduces you to the complexities of dynamic networks and demonstrate how KeyLines 2.0 can help you make sense of your evolving connected data.
A recording of this webinar, complete with the demons omitted from this slidedeck, can be found at KeyLines.com/downloads
Fog computing provide security to data in cloud pptpriyanka reddy
This document discusses fog computing and a proposed system to improve security of data stored in the cloud. It proposes using decoy technology to monitor for abnormal access patterns and generate fake documents to confuse attackers. The system would profile user behavior to validate authorized access and deploy decoys when abnormal access is detected. This helps prevent attackers from distinguishing real user data from fake data.
Internet of Things (IoT) represents a remarkable transformation of the way in which our world will soon interact. Much like the World Wide Web connected computers to networks, and the next evolution connected people to the Internet and other people, IoT looks poised to interconnect devices, people, environments, virtual objects and machines in ways that only science fiction writers could have imagined.
The document discusses the integration of fog computing with Internet of Things (IoT) applications. It introduces fog computing and how it extends cloud computing by providing data processing and storage locally at IoT devices to address challenges of latency and mobility. Benefits of fog computing include low latency, scalability, and flexibility to support various IoT applications like smart homes, healthcare, traffic lights, and connected cars. Challenges of integrating fog computing with IoT include security, privacy, resource estimation, and ensuring communication between fog servers and the cloud. The document reviews open issues and concludes by discussing future research directions for fog computing and IoT integration.
As HTML5 and the surrounding API´s has matured and grown in popularity we see more and more web-applications being built for mobile devices replacing old native applications.
In this article I walk through some of the challenges we face when developing real-time web-apps and also show one of the many ways to overcome these challenges.
The document discusses how the growth of IoT devices and data is creating challenges around scaling, security, storage, and analytics. It predicts that there will be trillions of connected devices generating zettabytes of data by 2020. This massive amount of data will be costly and inefficient to store and process in the cloud alone. The document proposes that a "fog computing" model, which processes data at the edge using gateways and local device intelligence, will be needed to efficiently handle the scale of IoT data. Cooperation between organizations on standards, APIs, and education will be important to support fog computing architectures for IoT.
Fog computing is a model that processes and stores data near network edge devices rather than solely in cloud data centers. It extends cloud computing to the edge of the network to provide low latency services to end users. Key characteristics include proximity to users, dense geographical distribution, and support for mobility. Fog computing is well-suited for applications requiring real-time processing like industrial automation and IoT networks of sensors. It helps improve quality of service by bringing services closer to users and enabling real-time analytics on distributed data sources.
This document discusses the growth of the Internet of Things (IoT) and the rise of fog computing. It notes that:
- 50 billion devices are expected to be internet-connected by 2020, up from 12.5 billion in 2010, representing rapid growth.
- Most of the world's data is now being generated by IoT devices like sensors and smart objects, creating big data challenges.
- Fog computing is a new distributed computing model that processes data at the edge of the network, near the data sources, to help address these challenges. It extends cloud computing out to endpoints and access networks.
- Open source software will be important for fog computing and IoT, as it has been
This document discusses using JavaScript and the Internet of Things (IoT) for bioinformatics applications. It notes that JavaScript is well-suited for bioinformatics due to its use in web development, data visualization, and its ability to run on both the front-end and back-end. The IoT connects physical devices to the internet and is already web-based. The document proposes a collaborative, open-source workflow system called IoB that uses JavaScript and connects databases and other "things" to enable sharing of reusable analysis components.
Performance Analysis of Internet of Things Protocols Based Fog/Cloud over Hig...Istabraq M. Al-Joboury
The document analyzes the performance of Internet of Things (IoT) protocols like MQTT and HTTP when used with fog and cloud computing over high traffic networks. The research tests response time, throughput, and packet loss for different IoT protocols (MQTT with QoS 0 and 1) and transmission methods (fog vs cloud) using realistic IoT sensors and traffic loads. The results showed MQTT generally had lower response times and higher throughput than HTTP, especially when using fog computing rather than cloud. MQTT QoS 1 also outperformed QoS 0 in most tests. Overall, fog computing with MQTT QoS 1 was found to have the best performance for high traffic IoT applications.
Fog computing provides compute, storage, and networking services between edge devices and cloud data centers. It helps address issues with cloud computing like latency, limited bandwidth, and data protection. Fog computing, located at the network edge, can process real-time, geographically distributed data from millions of IoT devices like vehicles, factories, and infrastructure. This localized processing allows analysis and action on IoT data within seconds, addressing needs that cloud alone cannot meet. Fog enhances cloud computing for IoT scenarios by extending cloud capabilities closer to the edge.
This document is a presentation by Naveen P. V. on the emerging trend of fog computing. It begins with an introduction that defines fog computing as operating on network ends rather than centralized cloud, placing transactions and resources at the edge of the cloud. It notes fog computing reduces bandwidth needs and costs while improving efficiencies. Examples are given where fog computing is useful, such as applications requiring low latency, distributed applications, and large control systems. Trends discussed include use in connected cars, smart grids, smart cities, and healthcare. The impact in the next 5 years is predicted to include increased mobile-based transportation interventions and adoption of smart metering to reduce emissions. Naveen expresses interest in working on smart cities and network
An increasing number of Consumer and Internet Internet of Things applications require some form of edge computing characterised by low latency, peer-to-peer communication, and mobility. Fog computing has recently emerged as the paradigm to address the needs of edge computing in IoT applications. Fog computing complements Cloud computing to allow the design and implementation of IoT systems that scale better, are more reactive and in which local communication and decision is enabled whenever possible.
This presentation introduces the key concepts behind Fog Computing, compare and contrast it with Cloud Computing and explain how the VORTEX platform enables Fog computing architectures.
The Internet of Things (IoT) is defined by embedded computing devices endowed with cross-network connectivity. This era of computing has huge potential for connected enterprises and consumers, and already has many successful use cases. IoT systems encompass many types of connectivity patterns, proprietary systems and network types. Just as the Web plays a significant role in providing an open, interoperable, easily deployable framework for today’s enterprise systems, it is not surprising the Web will provide similar benefits to IoT. New Web standards have allowed enterprises to extend their internal real-time systems over the firewall in a natural, unimpeded fashion to provide real-time, dynamic information to their customers and partners to ensure consistency and efficiency. These same Web standards can and should be applied to IoT systems to obtain advantages such as global reach, ease of deployment, economies of scale, ease of development, etc. We will discuss this evolution and explore the further impact of the Web on IoT.
IBM Bluemix Paris Meetup #27 20171219 - introIBM France Lab
This document summarizes an event discussing artificial intelligence held at Le Village by CA on December 19, 2017. It included presentations on AI in 2025, deploying virtual assistants at scale, using natural language processing to enrich text and conversations, and probabilistic AI. The event was hosted by IBM's France Lab and discussed IBM's cognitive capabilities including reasoning, understanding, learning, and interacting with unstructured data like language. It also covered IBM's cloud and AI infrastructure options for deploying applications and workloads.
During this presentation, KeyLines creator Joe Parry introduces you to the complexities of dynamic networks and demonstrate how KeyLines 2.0 can help you make sense of your evolving connected data.
A recording of this webinar, complete with the demons omitted from this slidedeck, can be found at KeyLines.com/downloads
Fog computing provide security to data in cloud pptpriyanka reddy
This document discusses fog computing and a proposed system to improve security of data stored in the cloud. It proposes using decoy technology to monitor for abnormal access patterns and generate fake documents to confuse attackers. The system would profile user behavior to validate authorized access and deploy decoys when abnormal access is detected. This helps prevent attackers from distinguishing real user data from fake data.
Internet of Things (IoT) represents a remarkable transformation of the way in which our world will soon interact. Much like the World Wide Web connected computers to networks, and the next evolution connected people to the Internet and other people, IoT looks poised to interconnect devices, people, environments, virtual objects and machines in ways that only science fiction writers could have imagined.
The document discusses the integration of fog computing with Internet of Things (IoT) applications. It introduces fog computing and how it extends cloud computing by providing data processing and storage locally at IoT devices to address challenges of latency and mobility. Benefits of fog computing include low latency, scalability, and flexibility to support various IoT applications like smart homes, healthcare, traffic lights, and connected cars. Challenges of integrating fog computing with IoT include security, privacy, resource estimation, and ensuring communication between fog servers and the cloud. The document reviews open issues and concludes by discussing future research directions for fog computing and IoT integration.
As HTML5 and the surrounding API´s has matured and grown in popularity we see more and more web-applications being built for mobile devices replacing old native applications.
In this article I walk through some of the challenges we face when developing real-time web-apps and also show one of the many ways to overcome these challenges.
DevSum15 - having fun with BLE, Raspberry Pi and AzureUffe Björklund
The document discusses using Bluetooth Low Energy (BLE), Raspberry Pi, and Azure to connect devices. It describes challenges with different connectivity protocols and recommends allowing "cross-protocol" communication. Code examples show connecting to a TI-CC2650 sensor device over BLE and reading sensor data. The presentation argues that developers should control transports and advocates an approach using state to reduce complexity and message size.
http://inarocket.com
Learn BEM fundamentals as fast as possible. What is BEM (Block, element, modifier), BEM syntax, how it works with a real example, etc.
Lightning Talk #9: How UX and Data Storytelling Can Shape Policy by Mika Aldabaux singapore
How can we take UX and Data Storytelling out of the tech context and use them to change the way government behaves?
Showcasing the truth is the highest goal of data storytelling. Because the design of a chart can affect the interpretation of data in a major way, one must wield visual tools with care and deliberation. Using quantitative facts to evoke an emotional response is best achieved with the combination of UX and data storytelling.
How to Build a Dynamic Social Media PlanPost Planner
Stop guessing and wasting your time on networks and strategies that don’t work!
Join Rebekah Radice and Katie Lance to learn how to optimize your social networks, the best kept secrets for hot content, top time management tools, and much more!
Watch the replay here: bit.ly/socialmedia-plan
The document discusses how personalization and dynamic content are becoming increasingly important on websites. It notes that 52% of marketers see content personalization as critical and 75% of consumers like it when brands personalize their content. However, personalization can create issues for search engine optimization as dynamic URLs and content are more difficult for search engines to index than static pages. The document provides tips for SEOs to help address these personalization and SEO challenges, such as using static URLs when possible and submitting accurate sitemaps.
This document summarizes a study of CEO succession events among the largest 100 U.S. corporations between 2005-2015. The study analyzed executives who were passed over for the CEO role ("succession losers") and their subsequent careers. It found that 74% of passed over executives left their companies, with 30% eventually becoming CEOs elsewhere. However, companies led by succession losers saw average stock price declines of 13% over 3 years, compared to gains for companies whose CEO selections remained unchanged. The findings suggest that boards generally identify the most qualified CEO candidates, though differences between internal and external hires complicate comparisons.
Internet of Things (IoT) - in the cloud or rather on-premises?Guido Schmutz
You want to implement a Big Data or Internet of Things (IoT) solution and like to know if it should be implemented in the cloud or on-premises. You are interested in the cloud offerings of vendors and what benefits they provide and if a similar solution would not be possible on-premises.
This presentation deals with this and other questions. Starting from a vendor-independent reference architecture and corresponding design patterns, different cloud solutions from various vendors are compared and rated. Additionally, it will be shown how such solution could be implemented on-premises and how a hybrid IoT solution could look like.
Independent of the source of data, the integration of event streams into an Enterprise Architecture gets more and more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analyzed, often with many consumers or systems interested in all or part of the events. Dependent on the size and quantity of such events, this can quickly be in the range of Big Data. How can we efficiently collect and transmit these events? How can we make sure that we can always report over historical events? How can these new events be integrated into traditional infrastructure and application landscape?
Starting with a product and technology neutral reference architecture, we will then present different solutions using Open Source frameworks and the Oracle Stack both for on premises as well as the cloud.
IoT Architecture - Are Traditional Architectures Good Enough or do we Need Ne...Guido Schmutz
Independent of the source of data, the integration of event streams into an Enterprise Architecture gets more and more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analysed, often with many consumers or systems interested in all or part of the events. Dependent on the size and quantity of such events, this can quickly be in the range of Big Data. How can we efficiently collect and transmit these events? How can we make sure that we can always report over historical events? How can these new events be integrated into traditional infrastructure and application landscape?
Starting with a product and technology neutral reference architecture, we will then present different solutions using Open Source frameworks and the Oracle Stack both for on premises as well as the cloud.
Increased Scalability: IoT devices need a lot of storage to share information for valuable purposes. Iot in cloud , like the StoneFly Cloud Connect to Microsoft Azure can provide customers with greater space which can increase as per the users demand. Helping to resolve the storage needs of customers.
Internet of Things (IoT) - in the cloud or rather on-premises?Guido Schmutz
You want to implement an Internet of Things (IoT) solution and would like to know if it should be implemented in the cloud or on-premises. You are interested in the cloud offerings of vendors and what benefits they provide and if a similar solution would not be possible on-premises.
This presentation deals with this and other questions. Starting from an vendor-independent reference architecture and corresponding design patterns, different cloud solutions from various vendors are compared and rated. Additionally it will be shown how such solution could be implemented on-premises and how a hybrid IoT solution could look like.
IoT and Maker Crossover (IMCO) Conference 2015Jollen Chen
This document discusses open Internet of Things (IoT) cloud architectures and protocols. It introduces Mokoversity and its open IoT cloud platform Openmbed, which uses web technologies like HTTP and open standards to simplify and liberate IoT development. Openmbed aims to make developing for the Web of Things easier and more open than existing solutions by providing free and open-source tools and projects.
1) The document discusses truths and myths about the Internet of Things (IoT), including that IoT technologies are still being defined and standardized and that creating an IoT solution is a time-consuming and expensive process.
2) While some see IoT arriving in 2020 or having a "big wishlist," the truth is that IoT will come gradually and have practical limitations like costs and device capabilities.
3) Rather than needing to create an IoT ecosystem, the author argues that the ecosystem already exists and one should become part of supporting it through innovation and using emerging IoT technologies, hardware, and development tools.
Independent of the source of data, the integration of event streams into an Enterprise Architecture gets more and more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analysed, often with many consumers or systems interested in all or part of the events. Dependent on the size and quantity of such events, this can quickly be in the range of Big Data. How can we efficiently collect and transmit these events? How can we make sure that we can always report over historical events? How can these new events be integrated into traditional infrastructure and application landscape?
Starting with a product and technology neutral reference architecture, we will then present different solutions using Open Source frameworks and the Oracle Stack both for on premises as well as the cloud.
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.
IOT Based Smart City: Weather, Traffic and Pollution Monitoring System IRJET Journal
This document describes an Internet of Things (IoT) system to monitor weather, traffic, and pollution conditions in a smart city. Sensors are connected to a Raspberry Pi to collect real-time data on temperature, humidity, rainfall, noise, and air quality. The Raspberry Pi then sends this sensor data to the Amazon Web Services (AWS) cloud platform using MQTT and WebSocket protocols. In AWS, the IoT service connects devices to applications, DynamoDB stores the sensor data in a database, and rules trigger actions like inserting data into DynamoDB tables or invoking Lambda functions. Developers can build a web interface to extract real-time sensor readings from DynamoDB and display traffic, weather, and pollution conditions for
Internet Of Things What You Need To Know - TechFuseRichard Harbridge
The Internet of Things (IoT) is here today in the devices, sensors, cloud services, and data your business uses. Microsoft delivers a flexible cloud-based approach that enables enterprises to capitalize on IoT by gathering, storing, and processing data centrally. When centrally connecting distributed LoB assets, the edge of an enterprise’s infrastructure can be redefined, and the breadth of the Microsoft data platform can be harnessed. Join Richard Harbridge as you learn about Microsoft’s position on IoT, and the technology and services being delivered from Microsoft to help you create the Internet of Your Things.
Monitoring water temperature, opening a yard gate and detecting water flood are just few samples of the many scenarios that simple IoT system can answer. Azure IoT Hub can be used to connect many different types of devices. At the lowest end, you can use it to connect a less than 3$ WiFi capable system on a cheap microcontroller, such as the WeMos D1 Pro and NodeMCU. In this lecture we will dive into the details of the Azure IoT hub. We will understand its service and its SDKs. We will see how we can build a WiFi capable, Arduino based, cloud controlled IoT smart switch. We will then use a cross platform Xamarin based application to activate the smart switch.
You will learn:
· An Internet of Thing system overview
· How to create and use the Azure IoT Hub
· Implementing an Azure IoT client SDK based solution
· Provisioning IoT devices, sending information to the cloud and receiving commands
· Arduino development using Visual Studio
NashTech - Azure IoT Solutions on Microsoft AzurePhi Huynh
This document discusses Internet of Things (IoT) solutions using Microsoft Azure. It begins with an agenda and some statistics about IoT growth. It then defines IoT and discusses the layers and reference architecture of an IoT solution. It describes Azure IoT Hub and Stream Analytics and how they enable device connectivity, management, and real-time analytics of streaming data. It also discusses Azure IoT preconfigured solutions and provides an example of a connected car solution. Finally, it outlines a smart city solution showcase using Azure services like IoT Hub, Stream Analytics, and Machine Learning.
Why don't you have all your home devices connected to the internet yet? Here we will present the KNoT meta-platform, an interoperability solution for IoT.
The document discusses definitions of the Internet of Things (IoT). It provides several definitions from various organizations that describe the IoT as connecting physical objects through standard internet protocols and allowing them to generate, exchange and consume data. The document also discusses the evolution of the IoT through different waves, starting with connecting PCs, then people through mobile/cloud, and the current wave of connecting everything through ubiquitous embedded systems like sensors. Finally, the document outlines some of the key enabling technologies and standards that help make the IoT possible, such as 6LoWPAN, CoAP and IEEE protocols.
The internet of things in now , see how golang is a part of this evolutionYoni Davidson
This document discusses how Golang can help with Internet of Things (IoT) development. It summarizes that IoT development requires skills in many areas, from embedded programming to backend development, which makes it challenging. Golang can help unify development by allowing code to run natively on devices and be used for both device and backend code, simplifying context switching. It also discusses examples of using Golang with IoT, including a code sample accessing a webcam from a Raspberry Pi. Recommended Golang packages for IoT are also listed.
In this session, Markus van Kempen discusses Internet of Things (IoT) use cases and examples. He demonstrates a geo-fencing application that tracks workers on a construction site using mobile devices and delays detonations if workers are still in danger areas. He also outlines how IoT connects devices to applications using MQTT and topics to publish and subscribe to sensor data.
The document is a presentation about Internet of Things (IoT) given by Andri Yadi, CEO of DycodeX. It defines IoT as network-connected devices with embedded processing and discusses how IoT represents the third wave of internet connectivity, after the internet of information and internet of people. It outlines key IoT technologies like wireless sensors, microcontrollers, communication protocols, and cloud platforms. Examples are given of an IoT weather station and smart farm. The presenter discusses the business opportunities in IoT and highlights several Indonesian IoT companies.
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Go real-time with the InternetOfThings
1. Go real-time with
"Internet of Things"
RealTime communication and IoT walks hand in hand
Uffe Bjorklund - @ulfbjo
2. About Me
In RealTimeWeb since 2009.
Web (mostly backend, and you will see why)
Kinect, Arduino, Netduino, RaspberryPI, AR Drone etc
P2P (like WebRTC)
M2M
...Full-Duplex communication in general...
3. Todays agenda
Intro to "realtime" development
Show that state is important
Communicate cross-protocol
Add "things" to the mix
4. HTTP/REST/AJAX
Designed for delivering resources (HTML, JS, CSS)
Half-Duplex (stateless)
~870 bytes average header
5. Why is "RealTime" important
Well...
Event driven architecture
Should decrease complexity
Will increase speed
But...
A client should never (or rarely) ask for data
You should never send data to a client that does not need it
So...
Simple
Fast
Saves resources
8. Framework Capabilities
The most imporant parts (IMO) of a "real-time" framework?
Modular architecture
So that functionality can be overriden/added in a smooth way
State
So that we get control over where messages are sent
Cross-Protocol Communication
So that we can connect things/systems regardles of protocol
But also...
Scaling
Security
Etc...
13. Sources/Credits
IoT statistics 1: Intel
IoT statistics 2: ReadWrite.com
Image of "Communication Patterns" by Phil Leggetter
Graphs by Wijmo
Game by html5quintus
Code samples by XSockets.NET
MissileSharp by Christian Specht
SharpDX by Alexandre Mutel
RevealJS by Hakim El Hattab