How are new IoT devices being designed, built & integrated to big data platforms such as Hadoop. Ammeon design such systems to integrate with and provide critical support for new device creators to bring their products to market.
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.
Device to Intelligence, IOT and Big Data in OracleJunSeok Seo
The document discusses Internet of Things (IoT) and big data in the context of Oracle technologies. It provides examples of how Oracle solutions have helped companies in various industries like transportation, healthcare, manufacturing, and telecommunications manage IoT and big data. Specifically, it highlights how Oracle technologies allow for efficient processing, analysis and management of large volumes of data from IoT devices and sensor networks in real-time.
Cloudera - Enabling the IoT Revolution Driving Insights in a Connected Worldandreas kuncoro
The document discusses the growing Internet of Things (IoT) ecosystem and how Cloudera's analytics platform can help organizations extract value from IoT data. Some key points:
- The IoT market is expected to grow significantly over the next few years, with over 30 billion connected devices generating huge amounts of data.
- Most IoT data is unstructured, intermittent, and from diverse sources, making it challenging to analyze and derive insights from.
- Cloudera provides a next-gen analytics platform that can handle diverse IoT data at scale in real-time, and extract value by combining data from multiple sources.
- The document outlines several IoT use cases across industries like manufacturing,
3 Things to Learn About:
*The IoT ecosystem and data management considerations for IoT
*Top IoT use cases and data architecture strategies for managing the sheer volume and variety of IoT data
*Real-life case studies on how our customers are using Cloudera Enterprise to drive insights and analytics from all of their IoT data
Big Data in IoT & Deep Learning
Challenges of IoT Big Data Analytics Applications
Challenges of Cloud-based IoT Platform
Cloud-based IoT Platform Use Case: GE Predix for Smart Building Energy Management
Fog/Edge Computing & Micro Data Centers
Deep Learning for IoT Big Data Analytics Introduction
Deep Learning for IoT Big Data Analytics Use Case
Distributed Deep Learning
Big Data + IoT + Cloud + Deep Learning Insights from Patents
Big Data + IoT + Cloud + Deep Learning Strategy Development
Designing Data-Intensive Applications
Xanadu Functionality
Xanadu Use Case
Xanadu + Deep Learning + Hadoop Integration
Without the right data management strategy, investments in Internet of Things (IoT) can yield limited results. Cloudera is pioneering next generation data management solutions, enabling organizations to build an enterprise data hub (EDH) as the backbone to any IoT initiative.
In depth cases of mature companies using IoT to transform their operations. Includes John Deere, Boeing. Economic estimates of the benefits to companies are included.
This document discusses Internet of Things (IoT) concepts including the IoT value chain and challenges of IoT implementation. It then summarizes a case study of a Logicalis solution for waste collection optimization using an IoT platform. The solution resulted in 30% reductions in kilometers traveled, time spent, bins visited and operational costs as well as 30% less CO2 emissions. Finally, the document introduces Eugenio, an IoT platform from Logicalis, and provides contact information for any questions.
The document discusses the convergence of IoT, big data, and cloud technologies. It describes how IoT generates large amounts of data with characteristics like velocity and volume that challenge traditional big data approaches. The cloud is presented as a way to provide scalable, distributed infrastructure for processing and managing IoT and big data. Two approaches for the convergence are described: a centralized approach that brings IoT data and functions into the cloud, and a distributed approach that leverages edge/fog computing to move cloud capabilities closer to devices and end users.
This document introduces Microsoft Azure IoT services and patterns for building Internet of Things (IoT) solutions. It describes the key components of an IoT product including sensors, communication methods, devices, device management, and data processing. It outlines how Azure IoT Hub, IoT Suite, gateways, and other services can be used to ingest sensor data, apply machine learning, store and analyze data, and send commands to devices. An example scenario of a simulated car device is provided. The document encourages leveraging Azure's breadth of platform as a service offerings to build transformative IoT applications.
Watson IoT Platform Sizing & Pricing - Sept 2016Jason Lu
The document provides information about IBM's Watson IoT Platform, including its pricing and financing options. The platform allows connecting devices and sensors to collect and analyze IoT data. It offers a free tier for basic use as well as paid dedicated and local options that provide more connections and storage. Pricing is based on the amount of data processed and stored each month. Financing options are also available to spread payments for the Watson IoT solutions over time.
To unlock the value from your Industrial IoT initiative, it’s paramount that operational insights are instantly gained from machine generated data that let you make critical decisions in real-time to the advantage of your business. Learn from practical use cases how seamless communications between assets from any corner of the globe, the machinery that analyses the data and the systems and people at the very heart of your business are a key element of successful IoT platforms that scale from initial pilots to global rollouts.
This document discusses big data and the Internet of Things (IoT). It states that while IoT data can be big data, big data strategies and technologies apply regardless of data source or industry. It defines big data as occurring when the size of data becomes problematic to store, move, extract, analyze, etc. using traditional methods. It recommends distributing and parallelizing data using approaches like Hadoop and discusses how technologies like SQL on Hadoop, Pig, Spark, HBase, queues, stream processing, and complex architectures can be used to handle big IoT and other big data.
Integrating AI into IoT networks is becoming a prerequisite for success in today’s data-driven digital ecosystems. The only way to keep up with IoT-generated data and gain the hidden insights it holds is using AI as the catalyst of IoT. Join this webinar to understand how IoT and AI may work together.
Independent of the source of data, the integration of event streams into an Enterprise Architecture gets more and more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analysed, often with many consumers or systems interested in all or part of the events. Dependent on the size and quantity of such events, this can quickly be in the range of Big Data. How can we efficiently collect and transmit these events? How can we make sure that we can always report over historical events? How can these new events be integrated into traditional infrastructure and application landscape?
Starting with a product and technology neutral reference architecture, we will then present different solutions using Open Source frameworks and the Oracle Stack both for on premises as well as the cloud.
CL2015 - Datacenter and Cloud Strategy and PlanningCisco
This document discusses strategies for data center and cloud transformation over the next 5 years. It outlines key digital business trends like data growth, cloud adoption, and security threats that are driving organizations' IT initiatives. These include managing increased data and applications, optimizing cloud strategies, addressing disruptive business models, and securing distributed data and applications. The document advocates adopting flexible consumption models, automation, and supporting edge/IoT applications. It positions Cisco as uniquely able to enable digital transformations through its portfolio of networking, compute, storage, automation, analytics, and security solutions.
Phoenix Data Conference - Big Data Analytics for IoT 11/4/17Mark Goldstein
“Big Data for IoT: Analytics from Descriptive to Predictive to Prescriptive” was presented to the Phoenix Data Conference on 11/4/17 at Grand Canyon University.
As the Internet of Things (IoT) floods data lakes and fills data oceans with sensor and real-world data, analytic tools and real-time responsiveness will require improved platforms and applications to deal with the data flow and move from descriptive to predictive to prescriptive analysis and outcomes.
Powering the Intelligent Edge: HPE's Strategy and Direction for IoT & Big DataDataWorks Summit
Powering the Intelligent Edge is one of the three pillars of Hewlett Packard Enterprise's corporate strategy. The session will cover HPE’s strategic direction and approach in the areas of IoT and data analytics. Join the discussion and learn how HPE’s solutions can help businesses prepare for the big data era.
1. The document discusses AIoT and edge computing.
2. It introduces Microsoft's Azure IoT platform and services for connecting, processing, analyzing and acting on IoT data.
3. Edge computing with Azure IoT Edge is described which analyzes data locally on IoT devices to reduce latency and cloud requirements.
This event summary describes a presentation by Alex G. Lee from Xanadu Big Data about their technology platform. The event is by invitation only on June 29th, 2017 from 11:30am to 3pm at the DLA Piper office in Palo Alto, California. The agenda includes check-in, lunch, an introduction by DLA Piper, a presentation by Alex G. Lee on Xanadu and how it can support big data, deep learning, cloud, and IoT applications, and a networking session.
Cloud Computing, SDN, Big Data and Internet of Everything - Lew TuckerLew Tucker
1) The document discusses emerging technologies including cloud computing, software defined networking, the Internet of Things, and how they are driving new applications and business opportunities.
2) Key trends include more mobile devices and traffic, more apps running on virtual machines in the cloud, and everything becoming connected which generates large amounts of data.
3) New technologies like software defined networking and open cloud platforms allow for more flexible, scalable infrastructure and applications.
Independent of the source of data, the integration of event streams into an Enterprise Architecture gets more and more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analyzed, often with many consumers or systems interested in all or part of the events. Dependent on the size and quantity of such events, this can quickly be in the range of Big Data. How can we efficiently collect and transmit these events? How can we make sure that we can always report over historical events? How can these new events be integrated into traditional infrastructure and application landscape?
Starting with a product and technology neutral reference architecture, we will then present different solutions using Open Source frameworks and the Oracle Stack both for on premises as well as the cloud.
Operational information processing: lightning-fast, delightfully simpleXylos
How can you as an industrial company or service provider collect and analyse data from your operational production equipment in a simple, fast and smart way? During this session, HPE gives you some practical examples – and what’s more, you’ll discover the underlying reference architecture. As a result, you’ll boost the efficiency of your production process and tune the services you provide to the needs of your customers.
IoT - Retour d'expérience de projets clients dans le domaine IoT. Michael Epprecht, Technical Specialist in the Global Black Belt IoT Team at Microsoft. Conférence donnée dans le cadre du Swiss Data Forum, du 24 novembre 2015 à Lausanne
The document discusses how Cloudera provides a data management platform for IoT data. It handles massive volumes of data from diverse sources in real-time and batch. The platform includes capabilities for data storage, processing, machine learning, analytics and management. Example use cases show how customers use the platform for predictive maintenance, smart cities, connected vehicles and other IoT applications.
Hadoop Self-Service Data Prep Fuels AnalyticsSenturus
See self-service data prep solutions for Hadoop. View the webinar video recording and download this deck: http://www.senturus.com/resources/fuel-analytics-self-service-hadoop-data-prep/.
Trifecta provides a demo of its Data Wrangler and discuss the following topics. 1) The challenges self-service data prep solutions are designed to solve and why the space has quickly gained in popularity. 2) How organizations are implementing self-service data prep to execute new types of analysis or augment existing processes. 3) The range of user and administrative features of self-service data prep tools like Trifecta. 4) How companies like PepsiCo and Royal Bank of Scotland use self-service data prep.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
The first presentation for Kafka Meetup @ Linkedin (Bangalore) held on 2015/12/5
It provides a brief introduction to the motivation for building Kafka and how it works from a high level.
Please download the presentation if you wish to see the animated slides.
This is the slide deck which was used for a talk 'Change Data Capture using Kafka' at Kafka Meetup at Linkedin (Bangalore) held on 11th June 2016.
The talk describes the need for CDC and why it's a good use case for Kafka.
This document discusses Internet of Things (IoT) concepts including the IoT value chain and challenges of IoT implementation. It then summarizes a case study of a Logicalis solution for waste collection optimization using an IoT platform. The solution resulted in 30% reductions in kilometers traveled, time spent, bins visited and operational costs as well as 30% less CO2 emissions. Finally, the document introduces Eugenio, an IoT platform from Logicalis, and provides contact information for any questions.
The document discusses the convergence of IoT, big data, and cloud technologies. It describes how IoT generates large amounts of data with characteristics like velocity and volume that challenge traditional big data approaches. The cloud is presented as a way to provide scalable, distributed infrastructure for processing and managing IoT and big data. Two approaches for the convergence are described: a centralized approach that brings IoT data and functions into the cloud, and a distributed approach that leverages edge/fog computing to move cloud capabilities closer to devices and end users.
This document introduces Microsoft Azure IoT services and patterns for building Internet of Things (IoT) solutions. It describes the key components of an IoT product including sensors, communication methods, devices, device management, and data processing. It outlines how Azure IoT Hub, IoT Suite, gateways, and other services can be used to ingest sensor data, apply machine learning, store and analyze data, and send commands to devices. An example scenario of a simulated car device is provided. The document encourages leveraging Azure's breadth of platform as a service offerings to build transformative IoT applications.
Watson IoT Platform Sizing & Pricing - Sept 2016Jason Lu
The document provides information about IBM's Watson IoT Platform, including its pricing and financing options. The platform allows connecting devices and sensors to collect and analyze IoT data. It offers a free tier for basic use as well as paid dedicated and local options that provide more connections and storage. Pricing is based on the amount of data processed and stored each month. Financing options are also available to spread payments for the Watson IoT solutions over time.
To unlock the value from your Industrial IoT initiative, it’s paramount that operational insights are instantly gained from machine generated data that let you make critical decisions in real-time to the advantage of your business. Learn from practical use cases how seamless communications between assets from any corner of the globe, the machinery that analyses the data and the systems and people at the very heart of your business are a key element of successful IoT platforms that scale from initial pilots to global rollouts.
This document discusses big data and the Internet of Things (IoT). It states that while IoT data can be big data, big data strategies and technologies apply regardless of data source or industry. It defines big data as occurring when the size of data becomes problematic to store, move, extract, analyze, etc. using traditional methods. It recommends distributing and parallelizing data using approaches like Hadoop and discusses how technologies like SQL on Hadoop, Pig, Spark, HBase, queues, stream processing, and complex architectures can be used to handle big IoT and other big data.
Integrating AI into IoT networks is becoming a prerequisite for success in today’s data-driven digital ecosystems. The only way to keep up with IoT-generated data and gain the hidden insights it holds is using AI as the catalyst of IoT. Join this webinar to understand how IoT and AI may work together.
Independent of the source of data, the integration of event streams into an Enterprise Architecture gets more and more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analysed, often with many consumers or systems interested in all or part of the events. Dependent on the size and quantity of such events, this can quickly be in the range of Big Data. How can we efficiently collect and transmit these events? How can we make sure that we can always report over historical events? How can these new events be integrated into traditional infrastructure and application landscape?
Starting with a product and technology neutral reference architecture, we will then present different solutions using Open Source frameworks and the Oracle Stack both for on premises as well as the cloud.
CL2015 - Datacenter and Cloud Strategy and PlanningCisco
This document discusses strategies for data center and cloud transformation over the next 5 years. It outlines key digital business trends like data growth, cloud adoption, and security threats that are driving organizations' IT initiatives. These include managing increased data and applications, optimizing cloud strategies, addressing disruptive business models, and securing distributed data and applications. The document advocates adopting flexible consumption models, automation, and supporting edge/IoT applications. It positions Cisco as uniquely able to enable digital transformations through its portfolio of networking, compute, storage, automation, analytics, and security solutions.
Phoenix Data Conference - Big Data Analytics for IoT 11/4/17Mark Goldstein
“Big Data for IoT: Analytics from Descriptive to Predictive to Prescriptive” was presented to the Phoenix Data Conference on 11/4/17 at Grand Canyon University.
As the Internet of Things (IoT) floods data lakes and fills data oceans with sensor and real-world data, analytic tools and real-time responsiveness will require improved platforms and applications to deal with the data flow and move from descriptive to predictive to prescriptive analysis and outcomes.
Powering the Intelligent Edge: HPE's Strategy and Direction for IoT & Big DataDataWorks Summit
Powering the Intelligent Edge is one of the three pillars of Hewlett Packard Enterprise's corporate strategy. The session will cover HPE’s strategic direction and approach in the areas of IoT and data analytics. Join the discussion and learn how HPE’s solutions can help businesses prepare for the big data era.
1. The document discusses AIoT and edge computing.
2. It introduces Microsoft's Azure IoT platform and services for connecting, processing, analyzing and acting on IoT data.
3. Edge computing with Azure IoT Edge is described which analyzes data locally on IoT devices to reduce latency and cloud requirements.
This event summary describes a presentation by Alex G. Lee from Xanadu Big Data about their technology platform. The event is by invitation only on June 29th, 2017 from 11:30am to 3pm at the DLA Piper office in Palo Alto, California. The agenda includes check-in, lunch, an introduction by DLA Piper, a presentation by Alex G. Lee on Xanadu and how it can support big data, deep learning, cloud, and IoT applications, and a networking session.
Cloud Computing, SDN, Big Data and Internet of Everything - Lew TuckerLew Tucker
1) The document discusses emerging technologies including cloud computing, software defined networking, the Internet of Things, and how they are driving new applications and business opportunities.
2) Key trends include more mobile devices and traffic, more apps running on virtual machines in the cloud, and everything becoming connected which generates large amounts of data.
3) New technologies like software defined networking and open cloud platforms allow for more flexible, scalable infrastructure and applications.
Independent of the source of data, the integration of event streams into an Enterprise Architecture gets more and more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analyzed, often with many consumers or systems interested in all or part of the events. Dependent on the size and quantity of such events, this can quickly be in the range of Big Data. How can we efficiently collect and transmit these events? How can we make sure that we can always report over historical events? How can these new events be integrated into traditional infrastructure and application landscape?
Starting with a product and technology neutral reference architecture, we will then present different solutions using Open Source frameworks and the Oracle Stack both for on premises as well as the cloud.
Operational information processing: lightning-fast, delightfully simpleXylos
How can you as an industrial company or service provider collect and analyse data from your operational production equipment in a simple, fast and smart way? During this session, HPE gives you some practical examples – and what’s more, you’ll discover the underlying reference architecture. As a result, you’ll boost the efficiency of your production process and tune the services you provide to the needs of your customers.
IoT - Retour d'expérience de projets clients dans le domaine IoT. Michael Epprecht, Technical Specialist in the Global Black Belt IoT Team at Microsoft. Conférence donnée dans le cadre du Swiss Data Forum, du 24 novembre 2015 à Lausanne
The document discusses how Cloudera provides a data management platform for IoT data. It handles massive volumes of data from diverse sources in real-time and batch. The platform includes capabilities for data storage, processing, machine learning, analytics and management. Example use cases show how customers use the platform for predictive maintenance, smart cities, connected vehicles and other IoT applications.
Hadoop Self-Service Data Prep Fuels AnalyticsSenturus
See self-service data prep solutions for Hadoop. View the webinar video recording and download this deck: http://www.senturus.com/resources/fuel-analytics-self-service-hadoop-data-prep/.
Trifecta provides a demo of its Data Wrangler and discuss the following topics. 1) The challenges self-service data prep solutions are designed to solve and why the space has quickly gained in popularity. 2) How organizations are implementing self-service data prep to execute new types of analysis or augment existing processes. 3) The range of user and administrative features of self-service data prep tools like Trifecta. 4) How companies like PepsiCo and Royal Bank of Scotland use self-service data prep.
Senturus, a business analytics consulting firm, has a resource library with hundreds of free recorded webinars, trainings, demos and unbiased product reviews. Take a look and share them with your colleagues and friends: http://www.senturus.com/resources/.
The first presentation for Kafka Meetup @ Linkedin (Bangalore) held on 2015/12/5
It provides a brief introduction to the motivation for building Kafka and how it works from a high level.
Please download the presentation if you wish to see the animated slides.
This is the slide deck which was used for a talk 'Change Data Capture using Kafka' at Kafka Meetup at Linkedin (Bangalore) held on 11th June 2016.
The talk describes the need for CDC and why it's a good use case for Kafka.
The Business Advantage of Hadoop: Lessons from the Field – Cloudera Summer We...Cloudera, Inc.
451 Analyst Matt Aslett, Cloudera CEO Mike Olson and Cloudera customers RIM and YP (formerly AT&T Interactive) to learn:
» Why Cloudera customers have chosen CDH to get started with Hadoop
» The business value resulting from analyzing new data sources in new ways
» How Hadoop will change these Customers’ business and industry over the next 3-5 years
Distributed Computing with Apache Hadoop is a technology overview that discusses:
1) Hadoop is an open source software framework for distributed storage and processing of large datasets across clusters of commodity hardware.
2) Hadoop addresses limitations of traditional distributed computing with an architecture that scales linearly by adding more nodes, moves computation to data instead of moving data, and provides reliability even when hardware failures occur.
3) Core Hadoop components include the Hadoop Distributed File System for storage, and MapReduce for distributed processing of large datasets in parallel on multiple machines.
The document discusses Internet of Things (IoT) including its definition, characteristics, architecture layers, technologies, protocols, devices, gateways, clouds, issues and applications. It specifically describes LoRa technology, its architecture and how it enables long range wireless connectivity for IoT applications. Commercial IoT cloud platforms and popular hardware platforms for IoT development are also mentioned.
The document provides an overview of the Internet of Things (IoT). It defines IoT as connecting everyday devices to the internet to collect and exchange data. It discusses how IoT works using devices, gateways, cloud platforms and applications. It also describes common IoT domains like smart home, healthcare and transportation. Finally, it discusses IoT devices, boards, platforms and tools as well as example IoT projects.
This document summarizes a presentation about low power Internet of Things (IoT). It discusses DycodeX's focus on asset tracking and precision agriculture using IoT. Common IoT architecture and low power considerations are outlined. DycodeX's cattle tracking product, SMARTernak, is presented as a case study. It monitors cattle location, health, and productivity using low power devices. Challenges of unstable electricity and internet in rural farms are addressed. Optimizing hardware, connectivity, and software for low power usage is described, including the use of ESP32, LPWA networks, and power-efficient software design.
Introduction to IoT Technologies - The need to know basicsJaco Bester
This document provides an introduction to Internet of Things (IoT) technologies. It discusses what IoT is, its application areas, and key aspects like platforms, security, analytics, device management, event stream processing, hardware, operating systems, standards, and low-power IoT networks. Specific technologies covered include Amazon Web Services IoT, Azure IoT Suite, Zigbee, Sigfox, and LoRa. The document aims to explain the basics needed to understand IoT.
The document discusses Internet of Things (IoT) architecture and topologies. It describes how IoT connects physical devices via the internet, enabling them to send and receive data. Key components include IoT devices, gateways that facilitate communication between devices and the cloud, and the IoT cloud platform that stores and processes device data. The document outlines common IoT architectures, technologies, protocols, issues, and provides examples of IoT applications.
Global Azure boot camp 2015 - Microsoft IoT Solutions with AzureVinoth Rajagopalan
This document discusses Microsoft IoT solutions using Azure. It introduces Internet of Things concepts and why the cloud is important for IoT. It describes key Azure IoT services like Event Hubs and Stream Analytics. Popular IoT protocols like MQTT and AllJoyn are covered. Microsoft operating systems for IoT devices from Windows Embedded to Windows 10 IoT editions are explained. Finally, it demos connecting devices to Azure services and discusses the Connect the Dots open source project.
This document provides an overview of Internet of Things (IoT) and Industrial Internet of Things (IIoT). It discusses key concepts including sensors, gateways, connectivity protocols, cloud platforms, security, and applications. Specifically, it describes how sensors collect data and transmit it via protocols like MQTT and AMQP to gateways, which perform edge analytics and send data to the cloud for storage and processing using services like AWS IoT. The cloud platform then makes this data available to applications and end users.
The document provides an overview of the Internet of Things (IoT). It discusses the evolution of IoT from local networks to today's interconnected world and envisions a future where everything is connected. The key characteristics of IoT including connectivity, intelligence, scalability and heterogeneous environments are described. Two reference models for IoT architecture are presented - the ITU-T model with four layers and the IWF model with seven layers. The main components of IoT like identification, sensing, actuation, communication and computation are explained. Popular applications of IoT across various industries like transportation, smart cities, manufacturing, retail and more are listed. Finally, the challenges of IoT especially around security, privacy and complexity are covered.
The document discusses fog networks and cloud computing in the context of an Internet of Things course. It covers the following key points:
- Fog networks refer to decentralized computing infrastructure located closer to IoT devices to help process some data locally instead of sending everything to the cloud. This helps address issues like latency.
- Cloud computing provides on-demand access to shared computing resources, allowing IoT systems to extend functionality by processing and storing data in the cloud.
- Common cloud service models for IoT include Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Major cloud providers like Amazon AWS offer services tailored to IoT applications
This document provides information about an IoT workshop hosted by Null Mumbai. It introduces the workshop organizers, Nitesh Malviya and Ganesh Naik, and their backgrounds in security and embedded systems. It then defines IoT and discusses its various components, including physical devices, sensors, networks, and cloud services. The document outlines common processor architectures, operating systems, protocols, and hardware that are used in IoT, such as Arduino, Raspberry Pi, MQTT, and more. It provides examples of how these pieces fit together in an IoT system and references materials for further learning.
The document discusses various components of IoT including control units, communication modules, and wireless technologies. Control units include sensors and actuators that convert physical phenomena into electrical signals. Common sensors detect humidity, temperature, motion etc. Communication modules allow connection and data transfer between IoT devices using short-range wireless technologies like Bluetooth, Zigbee and WiFi. Bluetooth supports audio/video transfer while Bluetooth Low Energy focuses on low power. Zigbee is optimized for large sensor networks with low data rates and power consumption.
An infrastructual secure wireless sensing and actuating solutionusman sarwar
This document discusses Intel's 6LoWPAN solution for connecting low-power wireless sensors and devices to the internet. It provides an overview of 6LoWPAN and its benefits, Intel's NetContiki operating system, the Intel IoT gateway architecture, security features, and optimizations for the 6LoWPAN stack. It also mentions Intel achieving interoperability with the IPSO Alliance and current support for Quark and Baytrail systems.
This document provides an overview of the course "18BME18 INTERNET OF THINGS FOR BIOMEDICAL ENGINEERS". The course aims to discuss IoT concepts, interpret wireless sensor network protocols, illustrate IoT applications in healthcare using tools and embedded systems. The document outlines the various units that will be covered, including IoT and M2M communication models, functional blocks, and protocols. It also compares IoT with M2M and describes software-defined networking.
Building the Internet of Things with Thingsquare and Contiki - day 1, part 1Adam Dunkels
How to build the Internet of Things - what is an Internet of things device and how do we connect it? This is the first Thingsquare IoT workshop slide deck.
Building a Citizen IoT Network on Microsoft AzureRichard Conway
This document discusses crowd sourcing smart cities using low-power wide-area networks (LPWAN) like LoRaWAN. It outlines how The Things Network (TTN) is being used to build skills and inspire innovation in Norwich by experimenting with LoRaWAN gateways and developing inexpensive sensor nodes. Current and potential projects using the TTN in Norfolk and Suffolk are described, including air quality monitoring, parking space monitoring, and integrating sensor data with platforms like Azure and IoT Central.
This document discusses quantified wellness and assisted living. It outlines a research project exploring wellness management through technology. The project team aims to use technology to improve resident wellness, quality of care, and staff behavior. Key questions are posed around establishing baselines, interpreting signals, integrating technology with care processes, and managing organizational change. Factors related to resident biological, psychological, and social wellness are identified.
This document discusses neurofeedback training (NFT) provided by Actualise-Cognifyx, which aims to optimize performance by developing understanding of the brain. NFT works by measuring and mapping brain function in real-time, then improving undesirable brain activity through positive reinforcement on an on-screen display to change psychological functioning and brain health. Case studies show changes in brain activity for an 8-year-old boy with autism, ADHD and ODD across NFT sessions. The document also summarizes global and Irish mental health trends and Cognifyx's capabilities in understanding cognition, emotion and behavior using technology, psychology experts and AI to detect, prevent and develop cognitive skills.
Can we track what we ate from our blood? From our pee?
The Nutri-Markers team from UCD are exploring this as part of the UCD-Nutrimarkers study, gaining a deeper understanding of the link between nutrition and health.
The potential for this is huge - no more food diaries for a start.
The science of nutrigenomics, metabolomics, is still very much in it's infancy, with advanced testing with DNA and blood analysis.
You can find out more on the UCD project on their website - http://www.ucdnutrimarkers.com/
This document discusses gut hormones and their role in appetite regulation and digestion. It describes how hormones like ghrelin, cholecystokinin, peptide YY, glucagon-like peptide-1, and oxyntomodulin are released during digestion to promote feelings of fullness and reduce food intake. Maintaining healthy levels of these gut hormones through diet and lifestyle can help with weight management and metabolic health. The document also advertises for a research study looking at the effects of food on gut hormones.
This document discusses quantifying various health metrics including resting heart rate, heart rate variability, sleep, blood glucose, blood biomarkers, and gut health. Tracking these metrics can help improve health and fitness by providing more useful data on diet changes, training, stress levels, sleep quality, weight loss efforts, and diagnosing conditions. The document describes what each metric is, why it's important to track, and how tools like fitness trackers, apps, blood testing services, and at-home microbiome tests can be used to quantify these health data points.
How can we improve our sleep using Biohacking principals? Darragh talks about how we can all improve our sleep and talks about his own personal journey of how he's improving his own sleep, and how is current lifestyle is impacting his sleep
Using big data analysis to better understand our sleep, Alex talks about how he used 18 months worth of data to understand his own sleeping patterns, and where he can see key events in his life over the last 18 months in the data.
The science behind the sleep trackers. Emer talks about what makes a good night's sleep, and how we can use sleep tracker data to understand and improve our sleep.
Wearables are no longer just about 10'000 steps. Wearables are increasingly been used heavily in competitive sports and health care, and are being used to to bring massive advantage to those who use them in both.
Working with the latest in cutting edge technologies to measure stress levels in the body, and using theraputic techniques like chiropractic therapy, Tammy & Peter Ross talked to Dublin's Quantified Self meetup group on how they treat patients in their practice
This document discusses a study on the potential of self-monitoring and self-tracking for health promotion. The study explored the experiences of self-trackers through an online survey and interviews. Key findings included that self-trackers engaged in tracking for self-knowledge, curiosity and health optimization. While self-tracking provided benefits like empowerment and motivation, barriers included issues with data interpretation and consistency. Overall self-tracking improved self-awareness and informed decision making for health, though future research should explore long term impacts and how to better integrate these tools into healthcare.
This document discusses quantified self and self-tracking in health. It provides examples of individuals who track various health metrics like blood glucose, exercise, diet, biomarkers and have found benefits like reduced insulin needs, weight loss, and cured illnesses. Common metrics tracked include blood glucose, heart rate, inflammation, microbiome, and DNA. The quantified self movement values first-person observations and experimentation to gain insights into one's own health and ways to improve it through lifestyle tracking and changes. There is a goal to aggregate user data to gain broader health insights through projects like the 100k Wellness Project.
This document describes a new technology for accurate consumer health monitoring using metabolomic profiling of blood samples. The system uses a home blood sampling kit, lifestyle tracking app, and mass spectrometry analysis to measure over 2000 metabolites and biomarkers in a user's blood. This provides insights into an individual's biochemical state, how their diet and lifestyle affect their metabolism and health, and can detect changes indicating potential health issues before symptoms appear. The goal is to help users better understand their body and lifestyle factors to stay healthy and improve wellbeing over time.
This document discusses automatic detection of foods and activities in lifelogging images. It describes the MyFood project for automatic monitoring of eating habits using lifelogging images. MyFood could help people track their diets and raise awareness of eating behaviors. The document also discusses the NTCIR-12 Lifelogging evaluation campaign, the first to evaluate tasks related to lifelogging data like images and location data. The campaign involved a test collection of lifelogging documents and sample queries to evaluate systems' ability to retrieve relevant documents. The best performing system in the campaign was from Laboratoire D’Informatique de Grenoble.
With the Quantified Mind web-app, Justin tracked his performance & correlated with diet, exercise, and sleep over 6 months.
Justin can be found at http://justinlawler.net
Google Fit is an open ecosystem that allows fitness data from different devices and apps to be stored in a central repository accessible from multiple devices. Developers can integrate with Google Fit using a REST API or Android SDK to upload fitness data from any wearable or sensor to the central repository, and access data created by other apps. This allows users' fitness data to persist even if they upgrade their fitness devices.
Increasing Retail Store Efficiency How can Planograms Save Time and Money.pptxAnoop Ashok
In today's fast-paced retail environment, efficiency is key. Every minute counts, and every penny matters. One tool that can significantly boost your store's efficiency is a well-executed planogram. These visual merchandising blueprints not only enhance store layouts but also save time and money in the process.
HCL Nomad Web – Best Practices und Verwaltung von Multiuser-Umgebungenpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-nomad-web-best-practices-und-verwaltung-von-multiuser-umgebungen/
HCL Nomad Web wird als die nächste Generation des HCL Notes-Clients gefeiert und bietet zahlreiche Vorteile, wie die Beseitigung des Bedarfs an Paketierung, Verteilung und Installation. Nomad Web-Client-Updates werden “automatisch” im Hintergrund installiert, was den administrativen Aufwand im Vergleich zu traditionellen HCL Notes-Clients erheblich reduziert. Allerdings stellt die Fehlerbehebung in Nomad Web im Vergleich zum Notes-Client einzigartige Herausforderungen dar.
Begleiten Sie Christoph und Marc, während sie demonstrieren, wie der Fehlerbehebungsprozess in HCL Nomad Web vereinfacht werden kann, um eine reibungslose und effiziente Benutzererfahrung zu gewährleisten.
In diesem Webinar werden wir effektive Strategien zur Diagnose und Lösung häufiger Probleme in HCL Nomad Web untersuchen, einschließlich
- Zugriff auf die Konsole
- Auffinden und Interpretieren von Protokolldateien
- Zugriff auf den Datenordner im Cache des Browsers (unter Verwendung von OPFS)
- Verständnis der Unterschiede zwischen Einzel- und Mehrbenutzerszenarien
- Nutzung der Client Clocking-Funktion
Social Media App Development Company-EmizenTechSteve Jonas
EmizenTech is a trusted Social Media App Development Company with 11+ years of experience in building engaging and feature-rich social platforms. Our team of skilled developers delivers custom social media apps tailored to your business goals and user expectations. We integrate real-time chat, video sharing, content feeds, notifications, and robust security features to ensure seamless user experiences. Whether you're creating a new platform or enhancing an existing one, we offer scalable solutions that support high performance and future growth. EmizenTech empowers businesses to connect users globally, boost engagement, and stay competitive in the digital social landscape.
UiPath Community Berlin: Orchestrator API, Swagger, and Test Manager APIUiPathCommunity
Join this UiPath Community Berlin meetup to explore the Orchestrator API, Swagger interface, and the Test Manager API. Learn how to leverage these tools to streamline automation, enhance testing, and integrate more efficiently with UiPath. Perfect for developers, testers, and automation enthusiasts!
📕 Agenda
Welcome & Introductions
Orchestrator API Overview
Exploring the Swagger Interface
Test Manager API Highlights
Streamlining Automation & Testing with APIs (Demo)
Q&A and Open Discussion
Perfect for developers, testers, and automation enthusiasts!
👉 Join our UiPath Community Berlin chapter: https://community.uipath.com/berlin/
This session streamed live on April 29, 2025, 18:00 CET.
Check out all our upcoming UiPath Community sessions at https://community.uipath.com/events/.
TrustArc Webinar: Consumer Expectations vs Corporate Realities on Data Broker...TrustArc
Most consumers believe they’re making informed decisions about their personal data—adjusting privacy settings, blocking trackers, and opting out where they can. However, our new research reveals that while awareness is high, taking meaningful action is still lacking. On the corporate side, many organizations report strong policies for managing third-party data and consumer consent yet fall short when it comes to consistency, accountability and transparency.
This session will explore the research findings from TrustArc’s Privacy Pulse Survey, examining consumer attitudes toward personal data collection and practical suggestions for corporate practices around purchasing third-party data.
Attendees will learn:
- Consumer awareness around data brokers and what consumers are doing to limit data collection
- How businesses assess third-party vendors and their consent management operations
- Where business preparedness needs improvement
- What these trends mean for the future of privacy governance and public trust
This discussion is essential for privacy, risk, and compliance professionals who want to ground their strategies in current data and prepare for what’s next in the privacy landscape.
Semantic Cultivators : The Critical Future Role to Enable AIartmondano
By 2026, AI agents will consume 10x more enterprise data than humans, but with none of the contextual understanding that prevents catastrophic misinterpretations.
Dev Dives: Automate and orchestrate your processes with UiPath MaestroUiPathCommunity
This session is designed to equip developers with the skills needed to build mission-critical, end-to-end processes that seamlessly orchestrate agents, people, and robots.
📕 Here's what you can expect:
- Modeling: Build end-to-end processes using BPMN.
- Implementing: Integrate agentic tasks, RPA, APIs, and advanced decisioning into processes.
- Operating: Control process instances with rewind, replay, pause, and stop functions.
- Monitoring: Use dashboards and embedded analytics for real-time insights into process instances.
This webinar is a must-attend for developers looking to enhance their agentic automation skills and orchestrate robust, mission-critical processes.
👨🏫 Speaker:
Andrei Vintila, Principal Product Manager @UiPath
This session streamed live on April 29, 2025, 16:00 CET.
Check out all our upcoming Dev Dives sessions at https://community.uipath.com/dev-dives-automation-developer-2025/.
Technology Trends in 2025: AI and Big Data AnalyticsInData Labs
At InData Labs, we have been keeping an ear to the ground, looking out for AI-enabled digital transformation trends coming our way in 2025. Our report will provide a look into the technology landscape of the future, including:
-Artificial Intelligence Market Overview
-Strategies for AI Adoption in 2025
-Anticipated drivers of AI adoption and transformative technologies
-Benefits of AI and Big data for your business
-Tips on how to prepare your business for innovation
-AI and data privacy: Strategies for securing data privacy in AI models, etc.
Download your free copy nowand implement the key findings to improve your business.
Big Data Analytics Quick Research Guide by Arthur MorganArthur Morgan
This is a Quick Research Guide (QRG).
QRGs include the following:
- A brief, high-level overview of the QRG topic.
- A milestone timeline for the QRG topic.
- Links to various free online resource materials to provide a deeper dive into the QRG topic.
- Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic.
QRGs planned for the series:
- Artificial Intelligence QRG
- Quantum Computing QRG
- Big Data Analytics QRG
- Spacecraft Guidance, Navigation & Control QRG (coming 2026)
- UK Home Computing & The Birth of ARM QRG (coming 2027)
Any questions or comments?
- Please contact Arthur Morgan at [email protected].
100% human made.
IT help desk outsourcing Services can assist with that by offering availability for customers and address their IT issue promptly without breaking the bank.
Special Meetup Edition - TDX Bengaluru Meetup #52.pptxshyamraj55
We’re bringing the TDX energy to our community with 2 power-packed sessions:
🛠️ Workshop: MuleSoft for Agentforce
Explore the new version of our hands-on workshop featuring the latest Topic Center and API Catalog updates.
📄 Talk: Power Up Document Processing
Dive into smart automation with MuleSoft IDP, NLP, and Einstein AI for intelligent document workflows.
Quantum Computing Quick Research Guide by Arthur MorganArthur Morgan
This is a Quick Research Guide (QRG).
QRGs include the following:
- A brief, high-level overview of the QRG topic.
- A milestone timeline for the QRG topic.
- Links to various free online resource materials to provide a deeper dive into the QRG topic.
- Conclusion and a recommendation for at least two books available in the SJPL system on the QRG topic.
QRGs planned for the series:
- Artificial Intelligence QRG
- Quantum Computing QRG
- Big Data Analytics QRG
- Spacecraft Guidance, Navigation & Control QRG (coming 2026)
- UK Home Computing & The Birth of ARM QRG (coming 2027)
Any questions or comments?
- Please contact Arthur Morgan at [email protected].
100% human made.
Book industry standards are evolving rapidly. In the first part of this session, we’ll share an overview of key developments from 2024 and the early months of 2025. Then, BookNet’s resident standards expert, Tom Richardson, and CEO, Lauren Stewart, have a forward-looking conversation about what’s next.
Link to recording, presentation slides, and accompanying resource: https://bnctechforum.ca/sessions/standardsgoals-for-2025-standards-certification-roundup/
Presented by BookNet Canada on May 6, 2025 with support from the Department of Canadian Heritage.
#StandardsGoals for 2025: Standards & certification roundup - Tech Forum 2025BookNet Canada
Book industry standards are evolving rapidly. In the first part of this session, we’ll share an overview of key developments from 2024 and the early months of 2025. Then, BookNet’s resident standards expert, Tom Richardson, and CEO, Lauren Stewart, have a forward-looking conversation about what’s next.
Link to recording, transcript, and accompanying resource: https://bnctechforum.ca/sessions/standardsgoals-for-2025-standards-certification-roundup/
Presented by BookNet Canada on May 6, 2025 with support from the Department of Canadian Heritage.
2. About me
Sriram Reddy
Architect
www.Ammeon.com
Software Architect with a passion for
• Linked Devices
• Device Multi Tenancy
• Low Power Wide Area Networks
• Distributed Device Management
• Low Power Device Security
• Distributed Data Persistence
• Distributed Data Processing
• Analytics
3. Index
1. Introduction
2. Internet Of Things
• Micro Controller & Processor
• Power Management
3. IOT Networks
• Long Range
• Short Range
4. IOT Data Types
• Binary (MQTT & Proto buff)
• Jason
5. IOT Data Acquisition
• MQTT
• CoAP
• Kafka
5. IOT Data processing
• Spark
• Nifi
• StreamSets
6. Data Persistence
• Hadoop
• Cassandra
• OrentDB
• Titan
• Mongo
7.Reporting
• BIRT Reporting
• Eclipse RCP
8. Analytics
9. Market Vertices
10. Q&A
4. Introduction
Nothing is new.
There are devices, there is network and there is data.
Challenge is Lot Of Devices, Network Everywhere, Lot Of Data
6. IOT Devices
Microprocessor Based Devices
Microcontroller Based Devices
Raspberry Pi, Orange Pi, Banana Pi, Nano Pi,
Bagel Bone, Panda board, Onion, Chip etc.
• SOCs from Boradcom, Rock chip, All winner, Intel etc
• Runs full Linux/Windows
• Powerful
• Power-hungry
Arduino, Wiring, Sypris etc
• Micro-chip, Atmel, Nordic etc
• SOC with memory and other peripherals
• Low power
• Less power consumption
7. IOT Communications
Long Range
Short Range
Networks to span full metros to countries
• Traditional operator provided 2G/3G/4G
• LORA
• SIGFOX
With in 100 meter range
• WIFI
• BLE
8. IOT DataTypes
Binary Data
JSON
Binary data provides size advantage but adds more
processing.
• MQTT
• Protobuffs
JSON or any markup payloads offer human readability
and existing processing infrastructure.
9. IOT Data Acquisition
MQTT
CoAP
Kafka
• Lot of queues (millions)
• Light Weight
• Open source brokers
• Well Integrated
• Well supported
• HTTP like
• Matured with telco industry
• Human readable
• Light server
• Not very heavy client
• Client controlled
• Fast
• Easy to scale
• Easy to replicate