How do APIs and IoT relate? The answer is not as simple as merely adding an API on top of a dumb device, but rather about understanding the architectural patterns for implementing an IoT fabric. There are typically two or three trends:
Exposing the device to a management framework
Exposing that management framework to a business centric logic
Exposing that business layer and data to end users.
This last trend is the IoT stack, which involves a new shift in the separation of what stuff happens, where data lives and where the interface lies. For instance, it's a mix of architectural styles between cloud, APIs and native hardware/software configurations.
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.
This IOT architecture describes about how things get connected via internet.In short, the Internet of Things refers to the rapidly growing network of connected objects that are able to collect and exchange data using embedded sensors. Thermostats, cars, lights, refrigerators, and more appliances can all be connected to the IoT.In short, the Internet of Things refers to the rapidly growing network of connected objects that are able to collect and exchange data using embedded sensors. Thermostats, cars, lights, refrigerators, and more appliances can all be connected to the IoT.
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.
This IOT architecture describes about how things get connected via internet.In short, the Internet of Things refers to the rapidly growing network of connected objects that are able to collect and exchange data using embedded sensors. Thermostats, cars, lights, refrigerators, and more appliances can all be connected to the IoT.In short, the Internet of Things refers to the rapidly growing network of connected objects that are able to collect and exchange data using embedded sensors. Thermostats, cars, lights, refrigerators, and more appliances can all be connected to the IoT.
The internet of things (IoT) is the internetworking of physical devices, vehicles, buildings and other items—embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data.
The slides defines IoT and show the differnce between M2M and IoT vision. It then describes the different layers that depicts the functional architecture of IoT, standard organizations and bodies and other IoT technology alliances, low power IoT protocols, IoT Platform components, and finally gives a short description to one of IoT low power application protocols (MQTT).
State of the market for IoT/IIoT and the cloud: What are the emerging opportunities for using interconnected devices and the cloud to provide enterprises with operational efficiencies and more effective mobility?
The internet of things (IoT) is the internetworking of physical devices, vehicles, buildings and other items—embedded with electronics, software, sensors, actuators, and network connectivity that enable these objects to collect and exchange data.
The slides defines IoT and show the differnce between M2M and IoT vision. It then describes the different layers that depicts the functional architecture of IoT, standard organizations and bodies and other IoT technology alliances, low power IoT protocols, IoT Platform components, and finally gives a short description to one of IoT low power application protocols (MQTT).
State of the market for IoT/IIoT and the cloud: What are the emerging opportunities for using interconnected devices and the cloud to provide enterprises with operational efficiencies and more effective mobility?
This is presentation slide for OpenStack Summit Austin 2016.
// Abstraction
Internet of Things is a hot topic today. Many companies are trying to create new business applications on a concept of IoT such as smart city, connected vehicle or smart grid. The platform for IoT applications has some unprecedented characteristics: (1) needs to accept huge number of connections simultaneously (2) needs to be highly reliable and secure (3) needs to be highly scalable.
We have designed, prototyped and evaluated a highly reliable IoT platform for collecting and storing large-scale data.
We explained our use case and architecture of IoT platform. We are tackling the following very high requirements during the process of prototyping and evaluating the platform.
• Receiving and storing messages from over 10M clients concurrently
• Highly reliable architecture of message broking without losing messages
• Instant scale-out to process burst traffic rapidly
We also discussed how we can adopt OpenStack to IoT backend and share ideas for its enhancement.
For the full video of this presentation, please visit:
https://www.embedded-vision.com/platinum-members/mathworks/embedded-vision-training/videos/pages/may-2017-embedded-vision-summit-venkataramani
For more information about embedded vision, please visit:
http://www.embedded-vision.com
Avinash Nehemiah, Product Marketing Manager for Computer Vision, and Girish Venkataramani, Product Development Manager, both of MathWorks, presents the "Deep Learning and Vision Algorithm Development in MATLAB Targeting Embedded GPUs" tutorial at the May 2017 Embedded Vision Summit.
In this presentation, you'll learn how to adopt a MATLAB-centric workflow to design, verify and deploy your computer vision and deep learning applications onto embedded NVIDIA Tegra-based platforms including Jetson TK1/TX1 and DrivePX boards. The workflow starts with algorithm design in MATLAB, which enjoys universal appeal among engineers and scientists because of its expressive power and ease-of-use. The algorithm may employ deep learning networks augmented with traditional computer vision techniques and can be tested and verified within MATLAB.
Next, a compiler auto-generates portable and optimized CUDA code from the MATLAB algorithm, which is then cross-compiled and deployed to the Tegra board. The workflow affords on-board real-time prototyping and verification controlled through MATLAB. Examples of common computer vision algorithms and deep learning networks are used to describe this workflow, and their performance benchmarks are presented.
Introduction to Digital Image Processing Using MATLABRay Phan
This was a 3 hour presentation given to undergraduate and graduate students at Ryerson University in Toronto, Ontario, Canada on an introduction to Digital Image Processing using the MATLAB programming environment. This should provide the basics of performing the most common image processing tasks, as well as providing an introduction to how digital images work and how they're formed.
You can access the images and code that I created and used here: https://www.dropbox.com/sh/s7trtj4xngy3cpq/AAAoAK7Lf-aDRCDFOzYQW64ka?dl=0
1. New Patent Development Opportunity Analysis
2. New Patent Preparation & Prosecution Strategy
3. Strategic Patent Development Exploiting Existing Patents
4. Monetization Exploiting Strategically Packaged Patent Portfolio
5. Development of Strategically Packaged Patent Portfolio Best Practice
6. Methodology for Developing Strategically Packaged Patent Portfolio
사물인터넷 비즈니스 어프로치 (Internet of Things (IoT) Business Approach)Hakyong Kim
이 자료에서는 사물인터넷 개념을 바탕으로 한 6가지 비즈니스 접근법에 대해 소개합니다. 사업기획 자문이나 강연 문의는 발표자료의 이메일 주소로 해주시기 바랍니다.
In this presentation, we present the 6 business approaches for the Internet of Things (IoT).
MicroEJ OS is a scalable Operating System for resource-constrained embedded and IoT devices, optimized for a wide range of hardware architectures.
With MicroEJ OS, OEMs use proven methods that cut software development time and cost. They create software that delivers incredible user experience and adjusts to Internet business needs.
MicroEJ development tools enable device manufacturers to deliver differentiating firmware using MicroEJ SDK.
In this presentation I do a review of the architecture of an AI application for IoT environments.
Since specific modeling and training aspects also have an impact on the final implementation of an enterprise ready solution, such solutions become very complex pretty soon.
The complexity of AI system for IoT is a big challenge – thus, I want to break this complexity down into particular views, which emphasize the individual but still interconnected aspects more clearly.
This webinar will focus on IoTView, InduSoft’s IoT and IIoT platform agnostic solution for creating HMIs for IoT devices and intelligent systems. In this webinar we’ll learn more about the capabilities of InduSoft IoTView, and how it can be embedded in end point devices such as pumps, motion control, valves, power monitors, and other controllers to create robust IIoT solutions.
Ultimate list of 50 Best IoT platforms of 2019ThingsCloud
IoT has become a key driver of industrial growth in recent time. Along with that quite a lot of IoT platforms is coming in the market place. This is the comprehensive list of IoT Platforms we have classified IoT Platforms into
1. SaaS IoT Platforms
2. Open-Source IoT Platforms
3. Enterprise IoT Platforms
4. Self-Service IoT Platforms
This is a must read presentation for Developers, Students or anyone who is interested in IoT
Bevywise Networks is an IoT Company creating Frameworks & Tools for business that create IoT / IIoT Solutions, System integrators & Enterprises to enable Industry 4.0 automation into their process
Developing Interoperable Components for an Open IoT Foundation Eurotech
In this presentation Eurotech and Red Hat present Kapua, a modular cloud platform that provides management for Internet of Things (IoT) gateways and smart edge devices. It represents a key milestone towards the development of a truly open, end-to-end foundation for IoT and its ecosystem of partners and solutions. Kapua provides a core integration framework with services for device registry, data and device management, message routing, and applications.
The current landscape of Internet of Things (IoT) applications is extremely fragmented because we are still experimenting to discover the correct mix for our respective markets. Unfortunately in the IoT world, one solution does not fit all.We need much more clarity in understanding the challenges of IoT application development, both in terms of technical feasibility as well as business opportunities. In our talk we present a toolkit approach towards accelerating IoT applications by leveraging modular components that can effectively accelerate go to market for end solutions.
As millions of embedded devices get connected to the cloud, it becomes crucial for the teams monitoring the performance of their production systems to get insight into the edge device’s health, and proactively fix problems before the news hits the front page of New York Times. As connected things move into traditional businesses like homes, retail, and industries - the traditional device management and diagnostic tools clash with backend enterprise performance management systems. This talk given at OpenIoTSummit in San Digeo covers best practices on how to bridge the device performance metrics with backend performance analysis to provide a unified view of a connected world.
The LAMP (Linux/Apache HTTP Server/MySQL/PHP) stack has dominated web infrastructures, in the IoT it is believed a similar open source stack will dominate IoT deployments. This presentation will look at the new technology requirements and architectures required for IoT solutions. It will identify three stacks of software required by any IoT solution, and finally present how open source communities, such as the Eclipse IoT community, are already supplying the critical software technology needed by IoT solution providers.
Presented at IoT Evolution, Feb 8 2017
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Neuro-symbolic is not enough, we need neuro-*semantic*
IoT architecture
1. Planning an architecture for the
Internet of Things
IoT Expo , Nov 5, 2014
Sumit Sharma
Director, API Solutions
sumit.sharma@mulesoft.com
2. Leading connectivity platform for
enterprise applications, mobile and IoT
HQ in San Francisco with offices in New York, Atlanta, London, Rotterdam, Munich,
Sydney, Singapore, Hong Kong, Buenos Aires, Rio De Janiero
2
3,500+ on-premise enterprise deployments
25,000+ cloud deployments
50% of the Global 500
www.mulesoft.com
10. At a high level this is the general IoT stack
App
Data Processing and
Platform
Edge
Thing / Device
11. Breaking down the
IoT stack
MuleSoft Confidential - please do not share/distribute 11
12. The IoT Stack
Mobile apps
Mobile aPaaS
Application PaaS ( aPaaS )
Data Management and Intelligence
Device
Management
Hardware / Firmware
API
Design / Build
Sensors
Device
Hub/Gateway
API runtime
management
iPaaS
Middle-ware
Websites
Industry specific
( e.g., appliances, touch
console etc.)
21. Reference capabilities for a gateway
Connectivity
Routing
Enable scalable, real-time, dependable, high-performance
and interoperable data and
device management related exchanges
between publishers and subscribers
Registry
Software mgmt
Control Events Actuator
Aggregation Transformation Provisioning
22. Device, and Device gateway sprawl is going to be a challenge
Too many disparate
ecosystems. Too
many gateways,
hubs, protocols, apps.
23. Solution to the sprawl: A hub of all hubs
Need interoperability
between devices/
machines so they can
all talk to each other.
26. Capabilities required for Data Management and
Intelligence
• Data collection, storage, and analysis of sensor data
• Run rules on data streams
• Trigger alerts
• Advanced analytics/machine learning
• Expose HTTP (REST) APIs
Data, HTTP,
connectivity
Real time event
processing
Batch processing
Data enrichment
Routing and
Orchestration
BigData solution
connectivity
Pattern Discovery/
Model re-training
Driving Forces
Identification
Predictive Analysis
28. API lifecycle tooling can be split between
design time and runtime
Rapidly design, deploy and publish APIs
API
API runtime
Design / Build
management
29. API lifecycle: Design time capabilities
Rapidly design, deploy and publish APIs
API spec
creation
API design
lifecycle
API mocking/
modelling
Reusable API
patterns
Deployment
automation
API
Design / Build
API runtime
management
32. API lifecycle: Runtime capabilities
Rapidly design, deploy and publish APIs
Rate limiting /
Throttling
API SLA
management
Custom policy
engine
Multi-tenant org /
RBAC support
Deployment
automation
API and data
security
API
Design / Build
API runtime
management
42. One final thought: the stack as it exists today is also
converging…
App
Data Processing and
Platform
Edge
Thing / Device
43. Scenarios where the middleware and edge have converged
( i.e., MuleSoft Anypoint Edge )
AApppsp
Data Processing
and Platform
Edge
Thing / Device
44. And there are also scenarios where the app layer is directly
connected to the Thing/Device layer ( i.e., embedded
Android, Java, Javascript etc. )
Data Processing
and Platform
Edge
Apps
Thing / Device