Edge computing is becoming a key architectural component for industrial IoT deployments. Gartner Group identifies edge computing as one of their top Tech Trends for 2019. The opportunity to process data at the edge of the network, closer to the sensors and actuators, before data is sent to the cloud results in improved security, more efficient data movement, and better performance for industrial IoT use cases.
This presentation will explore three aspects of edge computing:
The benefits of edge computing for industrial IoT use cases
The key features delivered in edge computing solutions
A survey of different edge computing options available to customers.
Will Edge Computing IoT Solutions be a Real Trend in 2019?Tyrone Systems
Edge computing is a method of optimizing Internet of Things applications by performing data processing at the edge of the network, near the source of the data. Edge computing IoT technology is attracting huge investments, to ensure security, ruggedness and establish ROI driven use cases.
The truth about IoT field gateways (Sam Vanhoutte @IoT Convention Europe 2017) Codit
Should you connect devices directly to the cloud, or rather consolidate them via a field gateway? Discover the main raisons behind introducing a gateway into your IoT architecture, how they accelerate a rollout and what capabilities should you look for. Learn how gateways cope with connectivity issues and security challenges. Discover from Sam’s experiences how crucial IoT field gateways are for the future roadmap of your IoT solution. Being a connected company is no small decision. But you can make it easy;
Edge computing is a method of enabling small processing units near to the source of the data from sensors and central data servers. It utilizes cloud computing systems by performing data processing at the edge of the network, near the source of the data. This reduces the communications bandwidth needed between sensors by performing analytics and data processing.
Edge computing is becoming a key architectural component for industrial IoT deployments. Gartner Group identifies edge computing as one of their top Tech Trends for 2019. The opportunity to process data at the edge of the network, closer to the sensors and actuators, before data is sent to the cloud results in improved security, more efficient data movement, and better performance for industrial IoT use cases.
This presentation will explore three aspects of edge computing:
The benefits of edge computing for industrial IoT use cases
The key features delivered in edge computing solutions
A survey of different edge computing options available to customers.
Will Edge Computing IoT Solutions be a Real Trend in 2019?Tyrone Systems
Edge computing is a method of optimizing Internet of Things applications by performing data processing at the edge of the network, near the source of the data. Edge computing IoT technology is attracting huge investments, to ensure security, ruggedness and establish ROI driven use cases.
The truth about IoT field gateways (Sam Vanhoutte @IoT Convention Europe 2017) Codit
Should you connect devices directly to the cloud, or rather consolidate them via a field gateway? Discover the main raisons behind introducing a gateway into your IoT architecture, how they accelerate a rollout and what capabilities should you look for. Learn how gateways cope with connectivity issues and security challenges. Discover from Sam’s experiences how crucial IoT field gateways are for the future roadmap of your IoT solution. Being a connected company is no small decision. But you can make it easy;
Edge computing is a method of enabling small processing units near to the source of the data from sensors and central data servers. It utilizes cloud computing systems by performing data processing at the edge of the network, near the source of the data. This reduces the communications bandwidth needed between sensors by performing analytics and data processing.
My slides from IoT conference Athens 2017 keynote presentation, discussing the common problems with enterprise IoT projects / digital transformation and key failure points: Waterfall vs Agile methodology and open source vs closed approach/technologies. Also presenting an example agile approach of a multi-tenant IoT Solution for a Refrigerator Manufacturer.
Developing Enterprise-Level IoT Solutions by Fariz SaracevicBosnia Agile
This session will present challenges with building enterprise-level IoT solutions, the use of Continuous Engineering practices and lifecycle management tools to address those challenges, and the resulting business value from the perspective of business and engineering leaders. One of the scenarios that we will look at more details is around IoT-connected car.
Why integration is key in IoT solutions? (Sam Vanhoutte @Integrate2017)Codit
While working on several Internet of Things projects with different customers in Europe, it became clear that Integration matters more than ever. Building an overall IoT solution requires many different technologies and skills. The Architect role is crucial to combining different services into one solid solution. Integration skills are extremely important in building robust and scalable IoT solutions. Every phase of the IoT value chain requires integration, since IoT solutions are distributed and decoupled by nature. Retro-fitting existing devices? Routing of telemetry data? Or even exposing analytics results through secured APIs? All these challenges require integration skills. Skills that are very familiar to specialists in the Integration business. This presentation will explain why these are great times to be an Integration expert and how we can help tackling current challenges.
Meaningful Lawful Intercept (LI) demands the capture and analysis of 100 percent of the traffic crossing a network—whether in 10G or 1G interfaces, or a combination. Sharon likens the challenge to “finding the needle in the haystack,”
IoT IMPLEMENTATION CHALLENGES and the future of IoT connectivity by Matija Pu...Bosnia Agile
Everything around us is getting smarter. A digital layer is being put on top of everything electrical and mechanical out there. All these things that no longer are just things – The wise, the smart, the intelligent, the connected, the intertwined and the synced. We know them by heart. We let them share knowledge to learn from each other, becoming wiser every day. So we can get smarter with our world.
Webinar presentation March 31, 2016.
The Internet of Things (IoT) is one of the most exciting and dynamic areas of IT at the present time. IoT involves the linking of physical entities (“things”) with IT systems that derive information about or from those things which can be used to drive a wide variety of applications and services which may be directly or indirectly connected or related to those things. IoT covers a very wide spectrum of applications, spanning enterprises, governments and consumers and represents the integration of systems from traditionally different communities: Information Technology and Operational Technology. As a result, it is important for IoT systems to have architectures, systems principles, and operations that can accommodate the interesting scale, safety, reliability, and privacy requirements.
The CSCC deliverable, Cloud Customer Architecture for IoT, shares best practices for supporting IoT using cloud computing.
Download the deliverable: http://www.cloud-council.org/resource-hub
Edge Computing: An Extension to Cloud ComputingRamneek Kalra
This presentation was shared by Shally Gupta (PhD Research Scholar | IEEE Graduate Member) & Ramneek Kalra (IEEE Impact Creator) at IEEE MRU Student Branch, Faridabad, Haryana, India.
Verso IoT experience – What have we learned from implementations all over the...Bosnia Agile
IoT projects face many obstacles on their journey from idea to end-to-end solution. Technology is less an issue, with many vendors and solutions emerging every day. This brings optimism, but also concerns about proper future proof choice and interoperability issues. Even bigger concerns are present in business model definition, business cases creation, go-to-market strategy preparation which requires organizational changes that companies need to conduct in order to be long-term successful in the IoT domain. Verso deploys many projects worldwide, focusing mainly on communication part of IoT solution, however being involved in business discussion as well. What are common technological and business obstacles and what are best practices to resolve them will be the main feature of our presentation.
Powering the Internet of Things with Apache HadoopCloudera, Inc.
Without the right data management strategy, investments in Internet of Things (IoT) can yield limited results. Apache Hadoop has emerged as a key architectural component that can help make sense of IoT data, enabling never before seen data products and solutions.
Industrial IoT Applications: Making the Connection and Extracting Value (IOT3...Amazon Web Services
Industrial IoT applications are rapidly emerging across industries such as oil and gas, manufacturing, and agriculture. In this chalk talk, we help you architect end-to-end solutions that will deliver value like predictive maintenance, manufacturing quality, and process monitoring. In this interactive session, we help you understand how to connect greenfield and brownfield infrastructure with AWS that leverages both AWS Greengrass (on premises) and other AWS Cloud services. Along the way, we show how the AWS Industrial IoT Reference Architecture is incorporated to build your industrial application.
My slides from IoT conference Athens 2017 keynote presentation, discussing the common problems with enterprise IoT projects / digital transformation and key failure points: Waterfall vs Agile methodology and open source vs closed approach/technologies. Also presenting an example agile approach of a multi-tenant IoT Solution for a Refrigerator Manufacturer.
Developing Enterprise-Level IoT Solutions by Fariz SaracevicBosnia Agile
This session will present challenges with building enterprise-level IoT solutions, the use of Continuous Engineering practices and lifecycle management tools to address those challenges, and the resulting business value from the perspective of business and engineering leaders. One of the scenarios that we will look at more details is around IoT-connected car.
Why integration is key in IoT solutions? (Sam Vanhoutte @Integrate2017)Codit
While working on several Internet of Things projects with different customers in Europe, it became clear that Integration matters more than ever. Building an overall IoT solution requires many different technologies and skills. The Architect role is crucial to combining different services into one solid solution. Integration skills are extremely important in building robust and scalable IoT solutions. Every phase of the IoT value chain requires integration, since IoT solutions are distributed and decoupled by nature. Retro-fitting existing devices? Routing of telemetry data? Or even exposing analytics results through secured APIs? All these challenges require integration skills. Skills that are very familiar to specialists in the Integration business. This presentation will explain why these are great times to be an Integration expert and how we can help tackling current challenges.
Meaningful Lawful Intercept (LI) demands the capture and analysis of 100 percent of the traffic crossing a network—whether in 10G or 1G interfaces, or a combination. Sharon likens the challenge to “finding the needle in the haystack,”
IoT IMPLEMENTATION CHALLENGES and the future of IoT connectivity by Matija Pu...Bosnia Agile
Everything around us is getting smarter. A digital layer is being put on top of everything electrical and mechanical out there. All these things that no longer are just things – The wise, the smart, the intelligent, the connected, the intertwined and the synced. We know them by heart. We let them share knowledge to learn from each other, becoming wiser every day. So we can get smarter with our world.
Webinar presentation March 31, 2016.
The Internet of Things (IoT) is one of the most exciting and dynamic areas of IT at the present time. IoT involves the linking of physical entities (“things”) with IT systems that derive information about or from those things which can be used to drive a wide variety of applications and services which may be directly or indirectly connected or related to those things. IoT covers a very wide spectrum of applications, spanning enterprises, governments and consumers and represents the integration of systems from traditionally different communities: Information Technology and Operational Technology. As a result, it is important for IoT systems to have architectures, systems principles, and operations that can accommodate the interesting scale, safety, reliability, and privacy requirements.
The CSCC deliverable, Cloud Customer Architecture for IoT, shares best practices for supporting IoT using cloud computing.
Download the deliverable: http://www.cloud-council.org/resource-hub
Edge Computing: An Extension to Cloud ComputingRamneek Kalra
This presentation was shared by Shally Gupta (PhD Research Scholar | IEEE Graduate Member) & Ramneek Kalra (IEEE Impact Creator) at IEEE MRU Student Branch, Faridabad, Haryana, India.
Verso IoT experience – What have we learned from implementations all over the...Bosnia Agile
IoT projects face many obstacles on their journey from idea to end-to-end solution. Technology is less an issue, with many vendors and solutions emerging every day. This brings optimism, but also concerns about proper future proof choice and interoperability issues. Even bigger concerns are present in business model definition, business cases creation, go-to-market strategy preparation which requires organizational changes that companies need to conduct in order to be long-term successful in the IoT domain. Verso deploys many projects worldwide, focusing mainly on communication part of IoT solution, however being involved in business discussion as well. What are common technological and business obstacles and what are best practices to resolve them will be the main feature of our presentation.
Powering the Internet of Things with Apache HadoopCloudera, Inc.
Without the right data management strategy, investments in Internet of Things (IoT) can yield limited results. Apache Hadoop has emerged as a key architectural component that can help make sense of IoT data, enabling never before seen data products and solutions.
Industrial IoT Applications: Making the Connection and Extracting Value (IOT3...Amazon Web Services
Industrial IoT applications are rapidly emerging across industries such as oil and gas, manufacturing, and agriculture. In this chalk talk, we help you architect end-to-end solutions that will deliver value like predictive maintenance, manufacturing quality, and process monitoring. In this interactive session, we help you understand how to connect greenfield and brownfield infrastructure with AWS that leverages both AWS Greengrass (on premises) and other AWS Cloud services. Along the way, we show how the AWS Industrial IoT Reference Architecture is incorporated to build your industrial application.
This webinar talks about how to successfully implement IoT to make your enterprise more connected, analytically capable, highly secure, and strongly cognitive.
Level: Introductory
The infinite computing power of cloud is creating new business models and driving operational efficiencies in every sector. But how can you extend cloud capabilities to the edge? Join this webinar for real-world examples of how AWS customers are exploiting both IoT data and the power of the cloud. We'll also discuss how you can deploy analytics and machine learning at the edge through AWS building blocks such as AWS Greengrass and Amazon Sagemaker.
Customer use cases to be explored include:
- Nokia optimises communications to oil platforms by processing data nearer to the source
- Stanley Black&Decker performs predictive maintenance by identifying faulty parts before they fail
- Pentair overcomes intermittent connectivity issues to automate its water filtration plants
Who Should Attend: Business Directors, Business Leaders, Project Managers, IT Managers, Business Consultants, Heads of Innovation, Data Scientists and Product Marketeers.
Building a reliable and scalable IoT platform with MongoDB and HiveMQDominik Obermaier
Today’s Internet of Things (IoT) is enabling companies to blend together the physical and digital worlds, creating new business models and generating insights that increase productivity at once unimaginable levels. However, managing the ever growing volume of heterogeneous IoT data from disparate devices, systems and applications both on premise and in the cloud can be a challenging endeavour without a scalable and reliable IoT platform.
In this webinar, we will explore why and how companies are leveraging HiveMQ and MongoDB to build exactly that: a scalable and reliable IoT platform. Based upon a sample fleet management scenario, we will explain how telematics data can be routed via MQTT and efficiently stored to provide analytics and insights into the data.
Key Learnings
- Common challenges and pitfalls of IoT projects
- Required components for effectively handling data with an IoT platform
- HiveMQ for MQTT to enable bi-directional device communication over unstable networks
- MongoDB as the flexible and scalable modern data platform combining data from different sources and powering your applications
- Why MongoDB and HiveMQ is such a great combination
Gartner Top 10 Strategy Technology Trends 2018Den Reymer
Gartner Top 10 Strategy Technology Trends 2018
1. AI Foundation
2. Intelligent Apps and Analytics
3. Intelligent Things
4. Digital Twin
5. Cloud to the Edge
6. Conversational Platforms
7. Immersive Experience
8. Blockchain
9. Event Driven Model
10. Continuous Adaptive Risk and Trust
The value of the platform play in real world use cases Software AG cwin18 tou...Capgemini
Software AG Cumulocity IoT and Capgemini key enablers to to go beyond the current paradigms and transform the business by seamlessly combining people, things and differentiation.
IBM's Watson is a machine-learning platform that’s been built to mirror the same learning process that humans have: Observe, Interpret, Evaluate and Decide. Through the use of this cognitive framework, Watson can search through a database of information and pull out key insights to bridge gaps in human knowledge. It’s expertise scaling for enterprise.
Watson has already helped businesses across a variety of industries increase their customer engagement, data discovery and informed decision making abilities. Is your business next?
Using AWS IoT for Industrial Applications - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Understand how AWS IoT can be used for Industrial Applications including predictive quality, asset condition monitoring, and predictive maintenance
- Know how features of AWS IoT Core such as the rules engine, device shadow, and message broker are used for industrial applications
- Articulate how AWS IoT Analytics supports machine learning
Similar to Keepler | IoT Analytics & AI on Edge Computing (20)
Summary of the new features of Google Cloud in Cloud Next 2020.
Speaker: Sergio Gordillo, Cloud Architect and Business Development Manager en Keepler Data Tech.
Watch the webinar! https://www.youtube.com/watch?v=TxgLMj773E0
More info, visit www.keepler.io
Keepler | Experiencia de cliente en hoteles post-covidKeepler Data Tech
¿Cómo la tecnología podría ayudar a la experiencia de usuario en la vida post-covid? Hemos diseñado cómo podría utilizarse la tecnología para hacer de los hoteles un lugar más seguro frente a contagios víricos.
Más info, contáctanos en hello@keepler.io
Visita www.keepler.io/tecnologias-covid
Title: Introducción a series temporales en analítica de datos
Author: Marcos Sobrino, Data Analyst en Keepler Data Tech; Axel Blanco, Cloud Engineer & Data Analyst en Keepler Data Tech.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
3. The Keepler’s way
1
2
3
4
DATA
ANALYTICS
PRODUCTS
USERS
MORE
BETTER
BETTER
MORE
Keepler is an IT services boutique
focused on extracting business
value from the data through new
technologies and fast paced ways
of working.
Keepler help companies to get into
the“virtuous circle of data”.
DATA ANALYTICS
CLOUD COMPUTING
MACHINE LEARNING
AGILE & DEVOPS
4. To put it simple, IoT Analytics is the enabler of business
opportunities through the analysis of sensor data
Data Ingestion Event History
Edge
Computing
Event
Analytics
Public Cloud
6. An IoT Analytics liquid platform
A platform with building blocks
Designed to grow in volume and
variety of data
Event history is the first use case Enable building applications
Aligned with a Public
Cloud strategy
1
2 With Big Data
Features
3
Able to enrich
event information
Velocity
Volume
Veracity
Variety
5 With Data Science
Tools
6
Able to deploy ML
models on the cloud
and on the edge
Connectivity
Latency
Time stamp
Order
Size
Historic
Tools
Protocols
liquid features
Enablers
Challenges
4
With Data
Exploration Tools
7. Model deployment and execution on the edge
Event Data
Lake
IoT events feed
Data Science
Environment
IoT Liquid Platform
Video feed
ML Model
Function
Control
System
1
2
3
4
8. 3 examples of use cases supported
by IoT Analytics and Edge Computing
Digital Train
Maintenance
Oil Manufacturing
Data Lake
Work-site security
helmet detection
Serverless
Managed Services
IoT services
Machine Learning
SaaS Factory
Utility leader company
9. 3 examples of use cases supported
by IoT Analytics and Edge Computing
Digital Train
Maintenance
Oil Manufacturing
Data Lake
Work-site security
helmet detection
Serverless
Managed Services
IoT services
Machine Learning
SaaS Factory
Utility leader company
10. 3 examples of use cases supported
by IoT Analytics and Edge Computing
Digital Train
Maintenance
Oil Manufacturing
Data Lake
Work-site security
helmet detection
Serverless
Managed Services
IoT services
Machine Learning
SaaS Factory
Large Energy Provider
11. THANKS
& KEEP IN TOUCH!
www.keepler.io | hello@keepler.io | juan.maria.aramburu@keepler.io
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