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.
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.
Using an Open Source RESTful Backend for IoT ApplicationsJan Liband
Presentation from IoT DevCon 2015 explaining how an open source RESTful backend can be used for IoT applications. Presented by Bill Appleton, DreamFactory CEO and co-founder.
The document discusses the integration of Internet of Things (IoT) and cloud computing, referred to as Cloud of Things. It identifies several key issues with this integration, such as protocol support, energy efficiency, resource allocation, identity management, and security/privacy. Potential solutions are provided for some of the issues. The conclusion discusses the need for more study on the impact of these issues based on the specific IoT application and services provided.
This document summarizes an Internet of Things (IoT) meetup that covered various topics:
- Introduction to IoT and how objects can transfer data over networks.
- Introduction to cloud computing and how resources are shared over the internet.
- IoT architecture including things, gateways, and networks/cloud.
- IoT gateways like Raspberry Pi that interface devices and cloud.
- Sensor interfaces like XBee and RS-485 that connect to gateways.
- Network interfaces like WiFi and GPRS to connect gateways to cloud.
- Cloud architecture models from various sources.
- Data acquisition from devices using open-source Ponte software.
- Data storage
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.
IoT World - creating a secure robust IoT reference architecturePaul Fremantle
This document discusses creating a secure Internet of Things (IoT) architecture. It recommends three rules for IoT security: don't be stupid, be smart, and think about what's different for IoT devices. It also notes unique challenges for IoT security like long device lifecycles and limited capabilities. The document advocates for using federated identity and access control to securely manage devices and data. It presents a reference architecture for IoT that incorporates real-time stream processing, analytics, identity management, and open source components.
This document discusses implementing IOTA solutions on embedded devices for Internet of Underwater Things (IoUT) systems. It presents the IOTA Tangle and Masked Authenticated Messaging (MAM) as supporting technologies. It then describes the methodology of performing a feasibility study, reverse engineering the workflow, and implementing a pure C version to integrate with embedded environments. Test results show execution times for fetching data and code size. The document concludes the proposed solution enables IoUT and outlines future work including optimization and additional IOTA features.
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.
Using an Open Source RESTful Backend for IoT ApplicationsJan Liband
Presentation from IoT DevCon 2015 explaining how an open source RESTful backend can be used for IoT applications. Presented by Bill Appleton, DreamFactory CEO and co-founder.
The document discusses the integration of Internet of Things (IoT) and cloud computing, referred to as Cloud of Things. It identifies several key issues with this integration, such as protocol support, energy efficiency, resource allocation, identity management, and security/privacy. Potential solutions are provided for some of the issues. The conclusion discusses the need for more study on the impact of these issues based on the specific IoT application and services provided.
This document summarizes an Internet of Things (IoT) meetup that covered various topics:
- Introduction to IoT and how objects can transfer data over networks.
- Introduction to cloud computing and how resources are shared over the internet.
- IoT architecture including things, gateways, and networks/cloud.
- IoT gateways like Raspberry Pi that interface devices and cloud.
- Sensor interfaces like XBee and RS-485 that connect to gateways.
- Network interfaces like WiFi and GPRS to connect gateways to cloud.
- Cloud architecture models from various sources.
- Data acquisition from devices using open-source Ponte software.
- Data storage
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.
IoT World - creating a secure robust IoT reference architecturePaul Fremantle
This document discusses creating a secure Internet of Things (IoT) architecture. It recommends three rules for IoT security: don't be stupid, be smart, and think about what's different for IoT devices. It also notes unique challenges for IoT security like long device lifecycles and limited capabilities. The document advocates for using federated identity and access control to securely manage devices and data. It presents a reference architecture for IoT that incorporates real-time stream processing, analytics, identity management, and open source components.
This document discusses implementing IOTA solutions on embedded devices for Internet of Underwater Things (IoUT) systems. It presents the IOTA Tangle and Masked Authenticated Messaging (MAM) as supporting technologies. It then describes the methodology of performing a feasibility study, reverse engineering the workflow, and implementing a pure C version to integrate with embedded environments. Test results show execution times for fetching data and code size. The document concludes the proposed solution enables IoUT and outlines future work including optimization and additional IOTA features.
This document discusses Internet of Things (IoT) cloud integration and IoT cloud systems. It begins with an overview of cloud computing and the IoT. There are several common models for integrating IoTs and clouds, including using cloud platforms for data analytics and storage from sensors. Effective engineering of IoT cloud systems requires techniques like virtualization, composition and orchestration of services, and the ability to deploy across private, public and hybrid clouds. The integration of IoTs and clouds enables many application domains and helps connect physical things to online services.
This document discusses Internet of Things (IoT) and cloud computing. It defines IoT as connecting physical objects to the internet and collecting data from sensors. The cloud provides shared computing resources over the internet. The document outlines an IoT architecture with things, gateways, and a network/cloud. Gateways interface devices like sensors to the cloud using protocols like RS-485 and WiFi. The cloud provides services like software, platforms and infrastructure on a pay-per-use basis.
Infrastructure today is increasingly distributed, virtual, and abstract. Letu2019s look at a few interesting technologies that are steering the modern IT landscape.
Zero Incident FrameworkTM(ZIF) is a pure-play AI Platform for IT Operations, powered entirely by Unsupervised Pattern-based Machine Learning. ZIF enables AI-led Discovery, Monitoring, Noise Reduction, Event Correlation, Outage Predictions and Prescriptive Remediation.
Design and Development of Internet System for Residential Smart-Grid Ateeq Ur Rehman
The document discusses the design and development of an internet system for residential smart grids. It covers key topics like wireless communication, the internet of things, smart devices, smart grids, digital grid communication, and internet systems. It also examines the various layers and protocols involved, including the device layer, network layer, cloud management layer, and application layer. Finally, it discusses the merits and demerits of such a system and provides references for further information.
Open IoT Cloud Architecture, Web of Things, Shenzhen, China.Jollen Chen
This document discusses the Open IoT Cloud architecture proposed by Mokoversity. It describes how IoT is entering a new phase of integration with the Web called the Web of Things. It outlines some key aspects of the proposed Open IoT Cloud architecture, including using RESTful objects and protocols like HTTP, WebSockets, and CoAP to connect physical objects. The architecture aims to be open, decentralized, privacy-respecting and give users control over their personal data.
This document discusses fog computing. Fog computing extends cloud computing by providing data, compute, storage, and application services closer to the edge of the network. It was introduced by Cisco to efficiently share and store data between distributed devices in the Internet of Things. Fog computing helps address issues with cloud computing like high latency by processing data locally at edge devices instead of sending all data to a centralized cloud. It provides advantages like improved security, reduced data transfers across networks, and better support for real-time applications. The document compares fog and cloud computing and concludes that fog computing will grow in helping network paradigms that require fast processing.
This document discusses security concerns with connecting internet of things (IoT) devices to the internet. As more devices are connected, they become targets for hackers. Traditional security approaches are infeasible for IoT due to lack of infrastructure, resources, and proprietary systems. The document proposes developing an independent integrated security device that uses machine learning to provide security as a service for IoT networks by observing threats. This would allow security to be turned on or off by placing the device in a network, providing a more consolidated peer-to-peer approach compared to traditional hierarchical and distributed systems.
The document discusses the Internet of Things (IoT) and provides an overview of some key concepts. It defines IoT as connecting billions of devices by 2020 and describes examples like Nest products and smart refrigerators. It also covers basic microelectronics, the .NET Micro Framework for programming microcontrollers, and how to connect devices to the internet using gateways.
Big Data and Internet of Things: A Roadmap For Smart Environments, Fog Comput...Jiang Zhu
1) The document proposes Fog Computing as a new platform that extends cloud computing to the edge of the network in order to address the needs of latency-sensitive IoT applications.
2) Two use cases are described to illustrate the key requirements of Fog Computing: a smart traffic light system that requires local subsystem latency of less than 10ms, and a wind farm that involves real-time analytics and coordination across a wide geographical area.
3) The key attributes that Fog Computing aims to address include mobility, geo-distribution, low and predictable latency, interplay between fog and cloud for data analytics, consistency in highly distributed systems, multi-tenancy, and multi-agency coordination.
Fog computing is a model that processes data and applications at the edge of the network, rather than sending all data to the cloud. It helps address issues with IoT networks like high latency and bandwidth usage. Fog computing can overcome cloud limitations by keeping data local, reducing congestion and improving security. It is well-suited for applications that require real-time, localized processing like connected vehicles, smart grids, smart cities, and healthcare. Fog computing lowers costs and improves efficiencies compared to relying solely on cloud infrastructure.
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
Internet of Things is a global phenomenon and like any other such phenomenon requires a robust architecture for its happening. This presentation covers a web based architecture for IOT called Web of Things
Edge and Fog computing, a use-case prespectiveChetan Kumar S
This document discusses edge and fog computing use cases from an industrial perspective. It provides examples of applications that require low latency such as autonomous vehicles, industrial automation, and healthcare. Pushing large amounts of video and sensor data to distant cloud servers is not feasible for these applications due to bandwidth limitations and latency constraints. The document then presents two example use cases where edge/fog computing solutions were implemented: 1) A smart surveillance system for an industrial township using edge devices to run video analytics locally instead of sending all video to the cloud. 2) Using edge devices to optimize operations of steam boilers by collecting sensor data, making decisions, and performing actions locally to reduce latency. Overall, the document argues that edge and fog computing are necessary
Today Home Automation is one of the growing requirement in the society. This paper presents the implementation of Home Automation using Raspberry Pi. The Raspberry Pi is a basic embedded system and being a low cost single-board computer used to reduce the complexity of systems in real time applications. This application mainly serves as an efficient base to control various home appliance like Fan, Tube light, Refrigerator through mobile based application. The application is designed to provide a facility to user to access control of many appliances used in homes.
Modeling self-adaptative IoT architecturesIván Alfonso
This document proposes a domain-specific language (DSL) to model self-adaptive Internet of Things (IoT) architectures. The DSL allows modeling IoT systems with multiple layers including device, edge, fog, and cloud layers. It also models deployment of container-based applications across these layers. The DSL includes a sublanguage for expressing self-adaptation rules to enable systems to dynamically adapt to changes at runtime. Example adaptation rules and a tool for generating IoT system configurations from models are presented. Future work includes expanding the DSL to model more complex adaptation strategies and validating the approach in industrial settings.
The document discusses Cisco's Fog Computing and IOx platform for enabling applications at the network edge in Internet of Things (IoT) environments. It highlights challenges with cloud-only solutions for IoT due to bandwidth limitations, latency, and network reliability issues. Cisco's Fog Computing approach, implemented through its IOx platform, addresses these challenges by supporting application execution across the cloud, network edge, and IoT devices.
This document discusses the history and future of connectivity in devices from electric motors to the emerging Internet of Things (IoT). It notes that electrification starting in the early 1900s brought electric motors to homes, improving quality of life. Then in the 1950s, transistors and integrated circuits brought computers and information to homes. Now, IoT will connect everyday objects to networks, increasing software complexity for embedded systems. IoT will also change how devices are built and paid for as more startups enter the market. The document outlines ARM's vision and strategy for the mbed ecosystem to support this transition to a world of smart, low-power, connected devices.
This document provides an introduction to the Internet of Things. It outlines that IoT allows for collecting more data from sensors, controlling devices remotely, and automating processes. The document discusses how IoT started with early microcontrollers like Arduino and has expanded to include various hardware options. It also examines the software used for prototyping, professional programming, data storage and analysis, and building complete IoT solutions. Key components of IoT include sensors, local processing and storage, networks, cloud processing and storage. A variety of hardware and software options exist to enable IoT applications.
KNoT - a framework for iot interoperabilityTiago Barros
There are more than 450 IoT platforms today. These platforms create isolated silos with their own devices, and the devices can not exchange data between platforms. To solve this problem, CESAR is developing the KNoT meta-platform, which presents an architectural interoperability framework for IoT.
Io t & amp; industry 4.0,internet of thingsSumanPramanik7
The document provides an overview of the Internet of Things (IoT). It defines IoT as the network of physical objects embedded with sensors that collect and exchange data. It describes how IoT works through a process of devices collecting data, communicating it, analyzing it, and acting on it. Some key points made include that the amount of data generated by IoT is expected to grow significantly and IoT connectivity is growing rapidly. The document also outlines common IoT technologies, protocols, communication models, applications and challenges.
This document discusses Internet of Things (IoT) cloud integration and IoT cloud systems. It begins with an overview of cloud computing and the IoT. There are several common models for integrating IoTs and clouds, including using cloud platforms for data analytics and storage from sensors. Effective engineering of IoT cloud systems requires techniques like virtualization, composition and orchestration of services, and the ability to deploy across private, public and hybrid clouds. The integration of IoTs and clouds enables many application domains and helps connect physical things to online services.
This document discusses Internet of Things (IoT) and cloud computing. It defines IoT as connecting physical objects to the internet and collecting data from sensors. The cloud provides shared computing resources over the internet. The document outlines an IoT architecture with things, gateways, and a network/cloud. Gateways interface devices like sensors to the cloud using protocols like RS-485 and WiFi. The cloud provides services like software, platforms and infrastructure on a pay-per-use basis.
Infrastructure today is increasingly distributed, virtual, and abstract. Letu2019s look at a few interesting technologies that are steering the modern IT landscape.
Zero Incident FrameworkTM(ZIF) is a pure-play AI Platform for IT Operations, powered entirely by Unsupervised Pattern-based Machine Learning. ZIF enables AI-led Discovery, Monitoring, Noise Reduction, Event Correlation, Outage Predictions and Prescriptive Remediation.
Design and Development of Internet System for Residential Smart-Grid Ateeq Ur Rehman
The document discusses the design and development of an internet system for residential smart grids. It covers key topics like wireless communication, the internet of things, smart devices, smart grids, digital grid communication, and internet systems. It also examines the various layers and protocols involved, including the device layer, network layer, cloud management layer, and application layer. Finally, it discusses the merits and demerits of such a system and provides references for further information.
Open IoT Cloud Architecture, Web of Things, Shenzhen, China.Jollen Chen
This document discusses the Open IoT Cloud architecture proposed by Mokoversity. It describes how IoT is entering a new phase of integration with the Web called the Web of Things. It outlines some key aspects of the proposed Open IoT Cloud architecture, including using RESTful objects and protocols like HTTP, WebSockets, and CoAP to connect physical objects. The architecture aims to be open, decentralized, privacy-respecting and give users control over their personal data.
This document discusses fog computing. Fog computing extends cloud computing by providing data, compute, storage, and application services closer to the edge of the network. It was introduced by Cisco to efficiently share and store data between distributed devices in the Internet of Things. Fog computing helps address issues with cloud computing like high latency by processing data locally at edge devices instead of sending all data to a centralized cloud. It provides advantages like improved security, reduced data transfers across networks, and better support for real-time applications. The document compares fog and cloud computing and concludes that fog computing will grow in helping network paradigms that require fast processing.
This document discusses security concerns with connecting internet of things (IoT) devices to the internet. As more devices are connected, they become targets for hackers. Traditional security approaches are infeasible for IoT due to lack of infrastructure, resources, and proprietary systems. The document proposes developing an independent integrated security device that uses machine learning to provide security as a service for IoT networks by observing threats. This would allow security to be turned on or off by placing the device in a network, providing a more consolidated peer-to-peer approach compared to traditional hierarchical and distributed systems.
The document discusses the Internet of Things (IoT) and provides an overview of some key concepts. It defines IoT as connecting billions of devices by 2020 and describes examples like Nest products and smart refrigerators. It also covers basic microelectronics, the .NET Micro Framework for programming microcontrollers, and how to connect devices to the internet using gateways.
Big Data and Internet of Things: A Roadmap For Smart Environments, Fog Comput...Jiang Zhu
1) The document proposes Fog Computing as a new platform that extends cloud computing to the edge of the network in order to address the needs of latency-sensitive IoT applications.
2) Two use cases are described to illustrate the key requirements of Fog Computing: a smart traffic light system that requires local subsystem latency of less than 10ms, and a wind farm that involves real-time analytics and coordination across a wide geographical area.
3) The key attributes that Fog Computing aims to address include mobility, geo-distribution, low and predictable latency, interplay between fog and cloud for data analytics, consistency in highly distributed systems, multi-tenancy, and multi-agency coordination.
Fog computing is a model that processes data and applications at the edge of the network, rather than sending all data to the cloud. It helps address issues with IoT networks like high latency and bandwidth usage. Fog computing can overcome cloud limitations by keeping data local, reducing congestion and improving security. It is well-suited for applications that require real-time, localized processing like connected vehicles, smart grids, smart cities, and healthcare. Fog computing lowers costs and improves efficiencies compared to relying solely on cloud infrastructure.
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
Internet of Things is a global phenomenon and like any other such phenomenon requires a robust architecture for its happening. This presentation covers a web based architecture for IOT called Web of Things
Edge and Fog computing, a use-case prespectiveChetan Kumar S
This document discusses edge and fog computing use cases from an industrial perspective. It provides examples of applications that require low latency such as autonomous vehicles, industrial automation, and healthcare. Pushing large amounts of video and sensor data to distant cloud servers is not feasible for these applications due to bandwidth limitations and latency constraints. The document then presents two example use cases where edge/fog computing solutions were implemented: 1) A smart surveillance system for an industrial township using edge devices to run video analytics locally instead of sending all video to the cloud. 2) Using edge devices to optimize operations of steam boilers by collecting sensor data, making decisions, and performing actions locally to reduce latency. Overall, the document argues that edge and fog computing are necessary
Today Home Automation is one of the growing requirement in the society. This paper presents the implementation of Home Automation using Raspberry Pi. The Raspberry Pi is a basic embedded system and being a low cost single-board computer used to reduce the complexity of systems in real time applications. This application mainly serves as an efficient base to control various home appliance like Fan, Tube light, Refrigerator through mobile based application. The application is designed to provide a facility to user to access control of many appliances used in homes.
Modeling self-adaptative IoT architecturesIván Alfonso
This document proposes a domain-specific language (DSL) to model self-adaptive Internet of Things (IoT) architectures. The DSL allows modeling IoT systems with multiple layers including device, edge, fog, and cloud layers. It also models deployment of container-based applications across these layers. The DSL includes a sublanguage for expressing self-adaptation rules to enable systems to dynamically adapt to changes at runtime. Example adaptation rules and a tool for generating IoT system configurations from models are presented. Future work includes expanding the DSL to model more complex adaptation strategies and validating the approach in industrial settings.
The document discusses Cisco's Fog Computing and IOx platform for enabling applications at the network edge in Internet of Things (IoT) environments. It highlights challenges with cloud-only solutions for IoT due to bandwidth limitations, latency, and network reliability issues. Cisco's Fog Computing approach, implemented through its IOx platform, addresses these challenges by supporting application execution across the cloud, network edge, and IoT devices.
This document discusses the history and future of connectivity in devices from electric motors to the emerging Internet of Things (IoT). It notes that electrification starting in the early 1900s brought electric motors to homes, improving quality of life. Then in the 1950s, transistors and integrated circuits brought computers and information to homes. Now, IoT will connect everyday objects to networks, increasing software complexity for embedded systems. IoT will also change how devices are built and paid for as more startups enter the market. The document outlines ARM's vision and strategy for the mbed ecosystem to support this transition to a world of smart, low-power, connected devices.
This document provides an introduction to the Internet of Things. It outlines that IoT allows for collecting more data from sensors, controlling devices remotely, and automating processes. The document discusses how IoT started with early microcontrollers like Arduino and has expanded to include various hardware options. It also examines the software used for prototyping, professional programming, data storage and analysis, and building complete IoT solutions. Key components of IoT include sensors, local processing and storage, networks, cloud processing and storage. A variety of hardware and software options exist to enable IoT applications.
KNoT - a framework for iot interoperabilityTiago Barros
There are more than 450 IoT platforms today. These platforms create isolated silos with their own devices, and the devices can not exchange data between platforms. To solve this problem, CESAR is developing the KNoT meta-platform, which presents an architectural interoperability framework for IoT.
Io t & amp; industry 4.0,internet of thingsSumanPramanik7
The document provides an overview of the Internet of Things (IoT). It defines IoT as the network of physical objects embedded with sensors that collect and exchange data. It describes how IoT works through a process of devices collecting data, communicating it, analyzing it, and acting on it. Some key points made include that the amount of data generated by IoT is expected to grow significantly and IoT connectivity is growing rapidly. The document also outlines common IoT technologies, protocols, communication models, applications and challenges.
We provide platforms and frameworks for rapid development to unify Everything on the Internet for innovations to be created. Our customers has chosen our technology to be on the edge into the future of Internet. The future of Internet is not about a single technology or protocol, but to make them coexist.
INTEROPERABILITY, FLEXIBILITY AND INDUSTRIAL DESIGN REQUIREMENTS IN THE IoTMuhammad Ahad
The document discusses several key requirements for Internet of Things (IoT) systems, including:
1. Interoperability and flexibility are important so that IoT devices can easily connect to different systems and components according to user needs. IoT devices should also be reusable in new contexts.
2. Industrial design focuses on user demands, comfort, functionality, and serviceability.
3. IoT devices need to be able to adapt to different situations and combine wireless technologies to improve connectivity and bandwidth. Standardized interfaces are also important for integration.
4. Managing complexity requires transparency rather than opaque "black box" components. Open source components and business models will become more common.
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.
This document provides an overview of the Internet of Things (IoT), including definitions, characteristics, and the physical and logical design of IoT systems. It defines IoT as a network that connects devices to the internet to exchange data and communicate. The key characteristics are intelligence, heterogeneity, dynamic changes, enormous scale, safety/security, and connectivity. The physical design includes IoT devices, protocols for communication between devices and cloud servers, and the layers of the network including physical, link, network, transport and application layers. The logical design describes functional blocks, communication models like request-response and publish-subscribe, and APIs including REST and WebSocket-based APIs.
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
The document discusses Internet of Things (IoT), which connects physical objects through sensors and software to exchange data over the Internet. It describes how technologies like affordable sensors, connectivity, cloud computing, machine learning, and AI have enabled IoT. The number of connected IoT devices is expected to grow from over 7 billion today to 22 billion by 2025. Network virtualization is also discussed, which abstracts network resources into software to combine or divide physical networks flexibly. This improves agility, security, and efficiency.
The document discusses Internet of Things (IoT), which connects physical objects through sensors and software to exchange data over the Internet. It describes how technologies like affordable sensors, connectivity, cloud computing, machine learning, and AI have enabled IoT. The number of connected IoT devices is expected to grow from over 7 billion today to 22 billion by 2025. Network virtualization is also discussed, which abstracts network resources into software to combine or divide physical networks flexibly. This improves agility, security, and efficiency.
Alfresco Process Services (APS) and the Internet of ThingsNathan McMinn
The document discusses using Alfresco Process Services (APS) to manage processes triggered by Internet of Things (IoT) devices. APS can provide capabilities like device provisioning, decoupling process logic from event handling, and analytics on process activities triggered by IoT events. The document presents an architecture where IoT devices publish messages via MQTT and AWS IoT, which can trigger Lambda functions to start APS processes. APS can then update IoT device shadows stored in AWS IoT to communicate back to devices. This allows processes to manage state changes even if devices disconnect. Tools like Cloud9 and AWS IoT MQTT Client help develop and test IoT/APS integrations.
Your upcoming IoT project can significantly profit from using .NET, as there are several advantages to doing so. The platform is an excellent option for creating intricate systems because of its scalability and versatility.
The Internet of things describes physical objects that are embedded with sensors, processing ability, software, and other technologies that connect and exchange data with other devices and systems over the Internet or other communications networks.
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/
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.
This document provides an introduction to IoT including definitions and key characteristics. It discusses the four layers of an IoT architecture: sensing, network, data processing, and application. Common IoT protocols at each layer like MQTT, CoAP, and HTTP are also outlined. The document then covers microprocessors, comparing CISC and RISC architectures. Microcontrollers are defined as specialized microprocessors used in embedded systems. ARM is highlighted as a popular architecture for IoT devices due to its low power consumption and integrated components.
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 Cloud Application Development is backed by some really advanced and proven technologies like Amazon EC2 in combination with EBS (Elastic Block Store). A few others are G Suite from Google, and Microsoft Azure.
https://www.embitel.com/blog/embedded-blog/role-of-cloud-backend-in-iot-and-basics-of-iot-cloud-applications
IoT platforms provide tools and services to connect heterogeneous IoT devices, enable data flow and storage, and offer data analysis capabilities. They are scalable to handle billions of devices and messages per hour. Key features of IoT platforms include powerful data analytics and visualization dashboards, integration with other tools and platforms, and pay-as-you-go pricing models. Popular IoT platforms include Google Cloud Platform, Salesforce IoT Cloud, ThingWorx, IBM Watson IoT, Amazon AWS IoT Core, Microsoft Azure IoT Suite, Oracle IoT, and Cisco IoT Cloud Connect.
REC'n'Play 2019 - Aplicações industriais de internet das coisas: nem tudo é o...Tiago Barros
O documento discute as aplicações industriais da Internet das Coisas (IoT) e como nem tudo é o que parece. Apresenta o que é IoT, desafios da IoT, cenário global e brasileiro de IoT e como identificar unicamente produtos pode permitir oferecer novos serviços.
Providing Infrastructure to Enable IoT SolutionsTiago Barros
This document discusses enabling Internet of Things (IoT) solutions through infrastructure. It covers why home devices are not yet connected to the Internet, what IoT is, and that there is no single standard yet due to the diversity of things and applications in IoT. It also discusses IoT enablers like open platforms and building IoT solutions using devices, apps, platforms, and clouds. Further, it describes Brazil's efforts towards IoT, including its ecosystem master plan for verticals and horizontals. Finally, it discusses creating an IoT solutions ecosystem through interoperability, standardization, educational and internationalization efforts.
Presentation for the IEEE IoT Open Standards Committee about the standards landscape at ITU-T Study Group 20 - Internet of Things, Smart Cities and Communities.
CESAR School - Prototipação Eletrônica com ArduinoTiago Barros
O documento descreve um curso de prototipagem eletrônica que aborda:
1) O desenvolvimento de técnicas de prototipagem com sistemas computacionais, cobrindo conceitos de computação física, eletricidade, eletrônica e a plataforma Arduino.
2) O conteúdo inclui computação física, conceitos básicos de eletricidade e eletrônica, a plataforma Arduino, sinais analógicos e digitais e sensores e atuadores.
3) A plataforma Ar
KNoT - Uma plataforma de IoT interoperável para o BrasilTiago Barros
KNoT é uma meta-plataforma de IoT open source, com foco em interoperabilidade. Seu objetivo é oferecer uma plataforma fim a fim que conecte as plataformas de IoT existentes para permitir que essas plataformas conversem entre si.
O documento fornece uma introdução abrangente à Internet das Coisas (IoT), discutindo sua evolução, arquiteturas, protocolos de comunicação, casos de uso e desafios. Ele explica como a Internet está mudando para conectar não apenas pessoas, mas também "coisas" através de dispositivos embarcados, sensores e protocolos sem fio.
O que falta na internet para as coisas?Tiago Barros
Nos últimos anos, a internet vem evoluindo de um repositório de documentos interconectados para um ambiente dinâmico, que interliga pessoas, aplicações e dispositivos. Para que isto se estabeleça, é necessária uma arquitetura para internet que consiga lidar com estes novos desafios de intercomunicação entre as coisas. Nesta apresentação iremos discutir sobre as plataformas, padrões, protocolos de comunicação e a infra-estrutura necessária para a internet das coisas.
Interfaces fisicas para dispositivos moveisTiago Barros
O documento fornece uma introdução às interfaces físicas para dispositivos móveis, abordando conceitos como computação física, alternativas de interfaces como Arduino e Amarino, e protocolos de comunicação serial.
O documento apresenta Tiago Barros e resume seus principais tópicos de ensino sobre Arduino e computação física, incluindo conceitos básicos de eletricidade e eletrônica, a plataforma Arduino, sensores, atuadores, comunicação serial, bibliotecas e práticas com protótipo.
O documento introduz conceitos básicos de eletricidade, eletrônica e computação física utilizando a plataforma Arduino. São apresentados sensores, atuadores e comunicação serial, além de exemplos práticos de programação para acender LEDs, ler entradas digitais e analógicas e emitir sons.
Práticas de Desenvolvimento de SoftwareTiago Barros
O curso aborda os seguintes tópicos:
1) Construção de software, incluindo o que é construção de software e como ela se encaixa no processo de desenvolvimento;
2) Paradigmas de programação e como eles afetam a construção de software;
3) Arquiteturas de software e padrões de projeto.
C.E.S.A.R - Prototipación Electronica en DiseñoTiago Barros
1) O documento discute a importância da prototipação no processo de design e inovação centrado no usuário.
2) A prototipação eletrônica com Arduino é apresentada como uma plataforma útil para prototipar interações físicas através de sensores e atuadores.
3) Exemplos demonstram como Arduino pode ser usado para criar protótipos interativos como instrumentos musicais controlados por toque.
Este documento discute validação e gerenciamento de requisitos no processo de engenharia de software. Ele descreve os objetivos da validação de requisitos, formas de validação como revisão de documentos, prototipagem e testes, e ferramentas para gerenciamento de requisitos e mudanças.
O documento apresenta o professor Tiago Barros, que ministrará o curso de especialização em Engenharia de Software. O curso abordará processos de desenvolvimento de software, engenharia de requisitos, documentação e elicitação de requisitos. Os alunos formarão equipes para definir e documentar os requisitos de um projeto de software.
Técnicas de Prototipação II - Physical Computing - Aula 02Tiago Barros
O documento resume conceitos sobre sensores e atuadores sonoros e eletrônicos utilizados na plataforma Arduino. Inclui instruções para conectar e controlar microfones, buzzer, motores DC e displays de 7 segmentos, além de comunicação serial para enviar dados para o PC.
Técnicas de Prototipação II - Physical Computing - Aula 03Tiago Barros
O documento apresenta conceitos sobre sensores e atuadores sonoros e sua utilização com a plataforma Arduino. Inclui instruções para detectar sons e emitir notas musicais controlando um buzzer piezoelétrico, além de exemplos de código para ler um microfone e produzir sons. Também aborda comunicação serial, displays de 7 segmentos e o controle de motores DC.
Técnicas de Prototipação II - Physical Computing - Aula 01Tiago Barros
O documento discute conceitos básicos de eletricidade, sistemas computacionais reativos, a plataforma Arduino e como prototipar interações físicas usando computação. Explica conceitos como corrente elétrica, resistência, circuitos elétricos e apresenta a arquitetura de sistemas computacionais reativos e a plataforma Arduino, incluindo hardware, programação e exemplos de código.
Técnicas de Prototipação II - LEGO Aula 05Tiago Barros
O documento descreve os blocos de programação disponíveis no software Mindstorms NXT para trabalhar com sensores, manipulação de dados e variáveis. Ele explica como cada bloco funciona, quais portas e valores podem ser conectados e o que cada bloco representa ou faz. Além disso, pede perguntas sobre os blocos descritos.
Técnicas de Prototipação II - LEGO Aula 04Tiago Barros
O documento descreve o software Mindstorms NXT para programar robôs Lego Mindstorms. Ele explica os principais componentes da interface como a paleta de ferramentas, área de trabalho e centro de treinamento. Também descreve blocos comuns como mover, gravar ações, tocar som, exibir na tela, esperar sensores e repetição.
This presentation by Yong Lim, Professor of Economic Law at Seoul National University School of Law, was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
This presentation by Nathaniel Lane, Associate Professor in Economics at Oxford University, was made during the discussion “Pro-competitive Industrial Policy” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/pcip.
This presentation was uploaded with the author’s consent.
This presentation by Professor Alex Robson, Deputy Chair of Australia’s Productivity Commission, was made during the discussion “Competition and Regulation in Professions and Occupations” held at the 77th meeting of the OECD Working Party No. 2 on Competition and Regulation on 10 June 2024. More papers and presentations on the topic can be found at oe.cd/crps.
This presentation was uploaded with the author’s consent.
Mastering the Concepts Tested in the Databricks Certified Data Engineer Assoc...SkillCertProExams
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This presentation by OECD, OECD Secretariat, was made during the discussion “Competition and Regulation in Professions and Occupations” held at the 77th meeting of the OECD Working Party No. 2 on Competition and Regulation on 10 June 2024. More papers and presentations on the topic can be found at oe.cd/crps.
This presentation was uploaded with the author’s consent.
This presentation by OECD, OECD Secretariat, was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
This presentation by Juraj Čorba, Chair of OECD Working Party on Artificial Intelligence Governance (AIGO), was made during the discussion “Artificial Intelligence, Data and Competition” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/aicomp.
This presentation was uploaded with the author’s consent.
XP 2024 presentation: A New Look to Leadershipsamililja
Presentation slides from XP2024 conference, Bolzano IT. The slides describe a new view to leadership and combines it with anthro-complexity (aka cynefin).
This presentation by OECD, OECD Secretariat, was made during the discussion “Pro-competitive Industrial Policy” held at the 143rd meeting of the OECD Competition Committee on 12 June 2024. More papers and presentations on the topic can be found at oe.cd/pcip.
This presentation was uploaded with the author’s consent.
Suzanne Lagerweij - Influence Without Power - Why Empathy is Your Best Friend...Suzanne Lagerweij
This is a workshop about communication and collaboration. We will experience how we can analyze the reasons for resistance to change (exercise 1) and practice how to improve our conversation style and be more in control and effective in the way we communicate (exercise 2).
This session will use Dave Gray’s Empathy Mapping, Argyris’ Ladder of Inference and The Four Rs from Agile Conversations (Squirrel and Fredrick).
Abstract:
Let’s talk about powerful conversations! We all know how to lead a constructive conversation, right? Then why is it so difficult to have those conversations with people at work, especially those in powerful positions that show resistance to change?
Learning to control and direct conversations takes understanding and practice.
We can combine our innate empathy with our analytical skills to gain a deeper understanding of complex situations at work. Join this session to learn how to prepare for difficult conversations and how to improve our agile conversations in order to be more influential without power. We will use Dave Gray’s Empathy Mapping, Argyris’ Ladder of Inference and The Four Rs from Agile Conversations (Squirrel and Fredrick).
In the session you will experience how preparing and reflecting on your conversation can help you be more influential at work. You will learn how to communicate more effectively with the people needed to achieve positive change. You will leave with a self-revised version of a difficult conversation and a practical model to use when you get back to work.
Come learn more on how to become a real influencer!
Carrer goals.pptx and their importance in real lifeartemacademy2
Career goals serve as a roadmap for individuals, guiding them toward achieving long-term professional aspirations and personal fulfillment. Establishing clear career goals enables professionals to focus their efforts on developing specific skills, gaining relevant experience, and making strategic decisions that align with their desired career trajectory. By setting both short-term and long-term objectives, individuals can systematically track their progress, make necessary adjustments, and stay motivated. Short-term goals often include acquiring new qualifications, mastering particular competencies, or securing a specific role, while long-term goals might encompass reaching executive positions, becoming industry experts, or launching entrepreneurial ventures.
Moreover, having well-defined career goals fosters a sense of purpose and direction, enhancing job satisfaction and overall productivity. It encourages continuous learning and adaptation, as professionals remain attuned to industry trends and evolving job market demands. Career goals also facilitate better time management and resource allocation, as individuals prioritize tasks and opportunities that advance their professional growth. In addition, articulating career goals can aid in networking and mentorship, as it allows individuals to communicate their aspirations clearly to potential mentors, colleagues, and employers, thereby opening doors to valuable guidance and support. Ultimately, career goals are integral to personal and professional development, driving individuals toward sustained success and fulfillment in their chosen fields.
Collapsing Narratives: Exploring Non-Linearity • a micro report by Rosie WellsRosie Wells
Insight: In a landscape where traditional narrative structures are giving way to fragmented and non-linear forms of storytelling, there lies immense potential for creativity and exploration.
'Collapsing Narratives: Exploring Non-Linearity' is a micro report from Rosie Wells.
Rosie Wells is an Arts & Cultural Strategist uniquely positioned at the intersection of grassroots and mainstream storytelling.
Their work is focused on developing meaningful and lasting connections that can drive social change.
Please download this presentation to enjoy the hyperlinks!
4. Why our home devices are still not connected to the
internet?
Every "thing" has its specific
connectivity needs:
! communication range
! baud rate
! power consumption
! cost
5. Why our home devices are still not connected to the
internet?
…and this leads to many
protocols:
! physical layer
! data link and network layer
! transport layer
6. There is no standard yet
“It is very difficult to have a unique
standard for IoT as we have for the
WWW, with HTML and browsers. The
THINGS in IoT are so different and the
applications as diverse that many
standards and protocols will coexist.”
29. Components - KNoT Thing
protocol state machine
protocol messages
hardware interface
and abstraction
manages sensors
and actuators
multiple hardware
configurations for
µC, power and radio
30. SW
Components - KNoT Gateway
buildroot based linux distribution
hardware interface
and abstraction.
manages devices
from one radio.
one daemon for
each radio interface.
connects to all radio
daemons and creates
a bridge to the fog
cloud instance
deployed on
gateway
web app for
gateway setup
and config
31. Components - KNoT Cloud
planning to integrate
with ConASys
non-relational
database
currently supporting meshblu and FIWARE.
planning to integrate with AWS IoT and Google
Cloud.
32. Components - KNoT Lib
library that abstracts the cloud
services and is used to develop
applications. currently
implemented for Android, iOS
and Javascript libraries.
36. Construction of applied knowledge
The group's researches turns into
experiments in observatories,
enabling CESAR to apply the
knowledge acquired in IoT
projects.
37. Integrate many platforms into a unique one
It allows interoperability across platforms and across data
from many devices.
38. More agility in developing IoT projects
A KNoT Lamp can be simple like this:
1. Get a KNoT device core schematic and customize it
by adding a lamp actuator.
2. Write 3 functions on KNoT μOS that define your
lamp behavior.
3. Write a mobile app using KNoT lib to interact with
the lamp.