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    Course data sheet

    Internet of Things H9P43S

    Internet of Things (IoT) is a new revolution of the Internet to enable things to be connected anytime, anyplace, with anything and anyone ideally using any path/network and any service. This 2-day course introduces IoT from an all rounded perspective including what technologies are available and used, the application areas and solutions, business benefits, challenges in deploying IoT solutions (such as business integration, security and privacy issues, data management and analysis issues, governance issues) and choosing right technologies for a project.

    Audience

    This course is designed for all levels of IT managers/consultants/ administrators, software developers and project managers who want to learn latest technologies about Internet of Things.

    Course objectives After completion of the course, participants will be able to understand:

    What is Internet of Things (IoT) and why IoTis needed.

    The elements in IoT.• RFID as the core technologies enabling IoT.

    • Sensor and sensor network as the coretechnologies enabling IoT.

    H9P43S

    2 Days

    ILT

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    Prerequisites

    Participants shall have basic information technology knowledge.

    Localization as the core technologiesenabling IoT.

    The business ecosystem, scenarios andbusiness models. The key areas that can apply IoT. The different application solutions that area available in the market.

    The different practical considerations in evolving an IoT project.

    From case studies the way to adopt IoT and to deploy an IoT project.

    The future and open directions of IoT.

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  • Course data sheet Page 2

    Introduction to IoT • What is IoT?

    • Why IoT?

    • Elements in IoT

    • RFID

    • Wireless Sensor Networks (WSN)

    • Addressing schemes

    • Data storage and analytics

    Core Technology – RFID • Overview of RFID

    • RFID technology internals

    • RF communications

    • Protocol

    • Middleware architecture

    • RFID business aspects

    • Security and Privacy

    Core Technology - Sensor and sensor network • Sensing and Sensors

    • Motivation for a Network of Wireless Sensors Networks

    • Applications

    • Health Care

    • Pipeline Monitoring

    • Structural Health Monitoring

    • Traffic Control

    • Precision Agriculture

    Core Technology – Localization • Defining location

    • Methods for determining location • Location Systems (e.g. GPS, RSS-based

    indoorlocalization)

    Business Ecosystem, Scenarios and Model • Business drivers • Business ecosystems and scenarios

    • Business model • Framework/Architecture for IoT business models

    IoT Application Areas • Market segments, their size and growth • Key Area #1: Transportation

    • Healthcare

    • Key Area #3: Connected Home

    IoT Application Solutions • Smart Cities •

    Smart Agriculture

    Evolving the IoT • Business challenges in implementing IoT

    Detailed course outline

    Visualization•

    Underground Mining•

    • Coverage and Connectivity issues

    Smart Environment

    Smart Water

    Smart Metering

    Security & Emergencies

    Retail

    Logistics

    Industrial Control

    Smart Animal Farming

    Home Automation

    e-Health

    • •

    Strategic approach for adopting IoT

    Integrating IoT into business process Adaptive and event-driven processes Processes dealing with unreliable data Processes dealing with unreliable resources

    Highly distributed processes

    Data management and analysis considerations

    Security and Privacy considerations

    Governance considerations

    Standardization Adoption – Case study

    Evolving the IoT

    Strategic approach for adoption Choosing the right technology

    Critical success factors

    • • •

    Future of IoT Architecture evolution Energy efficient sensing

    Secure reprogrammable networks and privacy Quality of Service

    New protocols

    Participatory sensing

    Data mining

    Cloud computing

    GIS-based visualization

    International activities

    • •

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    Learn more at hpe.com/ww/bigdata

    © Copyright 2019 Hewlett Packard Enterprise Development LP. The information contained herein is subject to change without notice. The only warranties for Hewlett Packard Enterprise products and services are set forth in the express warranty statements accompanying such products and services. Nothing herein should be construed as constituting an additional warranty. Hewlett Packard Enterprise shall not be liable for technical or editorial errors or omissions contained herein.

    Microsoft is either a registered trademark or trademark of Microsoft Corporation in the United States and/or other countries. The OpenStack Word Mark is either a registered trademark/service mark or trademark/service mark of the OpenStack Foundation, in the United States and other countries and is used with the OpenStack Foundation’s permission. We are not affiliated with, endorsed or sponsored by the OpenStack Foundation or the OpenStack community. Pivotal and Cloud Foundry are trademarks and/or registered trademarks of Pivotal Software, Inc. in the United States and/or other countries. Linux is the registered trademark of Linus Torvalds in the U.S. and other countries. VMware is a registered trademark or trademark of VMware, Inc. in the United States and/or other jurisdictions. "Python" and the Python logos are trademarks or registered trademarks of the Python Software Foundation. TensorFlow, the TensorFlow logo and any related marks are trademarks of Google Inc.

    H9P43S A.00, January 2019, c04656912

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