Internet of Things IoT For Leaders and Managers Training

• Leaders & Managers
• Enterprise Architects
• Development management
• Business Owners

• Internet of Things (IoT)
• IoT applications
• IoT platforms

A desire to understand the foundations, application, and usages for Internet of Things (IoT)

Three days

Outline of Internet of Things (IoT) For Leaders and Managers Training Chapter 1. Introduction TO IoT

• Introduction
• What is Internet of Things?
• Why Internet of Things is important?
• How Internet of Things is changing the way we live?
• Impact of Internet of Things?
• Case study on RFID
• The Web of Things
• Linked data – value is greatest when linked
• Enterprise data – shared vs. public vs. private
• Importance of security, privacy, and authenticity
• Industry standards
• Web of Things layer as the driver for IoT systems
• IoT: Architecture
• Sensing-extending the physical world
• Time series data processing
• Connectivity
• Analytics
• Data storage and analysis
• Is the Internet the right technology to hook together a network of things?
• The key Chapters that our experience with the Internet teaches us about a future of things
  • Capabilities
  • Network management
  • Security
  • Mobility
  • Longevity
  • Device Management
• Key features of a distributed architecture for a system of things
• Summary

Chapter 2. iot Challenges

• Standards in IoT
• Evolution of Internet of Everything (IoE)
• Smart but Fragile
• Cybersecurity
• Security in IOT
• Digitizing infrastructure
• Managing high rate sensor data
• Processing data streams
• Data consistency in an intermittently connected or disconnected environment
• Identifying outliers and anomalies
• HCI and IoT World
• Spoken dialogue for human-computer interaction
• Speech with other modalities for natural interaction
• Considerations for multilingual interactions
• Paralinguistic information from speech for enhanced HCI
• Future challenges for ubiquitous speech interfaces
• Robotics and Autonomous Vehicles
• Sensing and data processing
• Simultaneous mapping and localization
• Autonomy and monitoring
• Future research challenges

Chapter 3. Iot platforms

• Functional Areas of IoT platforms
  • Connectivity
  • Analytics
  • Management
  • Enablement
  • Security
  • Identity & Access
• Vendor offerings
  • GE Predix
  • IBM Watson IoT Platform
  • SAP Hana
  • Cisco Jasper
  • Microsoft Azure IoT Service
  • AWS IoT
  • PTC ThingWorx
  • Zebra Zatar IoT Cloud
  • Exosite Murano IoT Platform
  • Backing services from Time Series, Big Data, NoSQL and RDBMS
• POV, POC, Flash builds, and Spikes in IoT
  • IoT connectivity layer
  • Device data simulation
  • Monitoring dashboards
  • End-user application
  • Integrated Development Environments
• Cloud-native & IoT
  • Is Cloud required?
  • Platforms for Cloud-native
  • • RedHat OpenShift
    • Containerization & Microservices
    • Pivotal Cloud Foundry (PCF)
  • Key attributes of Cloud for IoT
  • • Reliability
    • Velocity
    • Resiliency
    • Scalability

Chapter 4. Iot Sensors and connectivity

• Introduction to Wireless Sensors Networks
• Wireless protocols
• One size does not fit all: why are there dozens of connectivity options?
• Three key dimensions: application duty cycle and data rate, battery consumption, and communication range
• Three case studies: low-power design (Bluetooth Low Energy), range extension techniques (data mining and mesh networking), and data-intensive IoT for continuous recognition applications
• Predictions for the next few years
• Wired Connectivity
• Ethernet
• Serial Communications
• Wireless Communication Protocols
• Wi-Fi
• RF & RFID
• IPV4 & IPV6
• 6LOWPAN
• Zigbee (IEEE 802.15.4)
• Bluetooth or Bluetooth Low Energy
• GSM(2G/3G/LTE)
• 5G and the Future
• LoRaWAN
• NB-IoT
• SigFox
• LTE CAT 1
• CAT M1

Chapter 5. Application of iot

• Smart cities
• Localization
• Localization algorithms
• Indoor localization
• Localization for mobile systems
• Applications
• Brainstorming
• Open Innovation
• Conception
• Industrial design and practices
• Adaptive risk assessment
• Defensive strategies and examples
• Human computer interaction
• Assisted knowledge management
• Collaboration and communication
• Connections and device management
• Data ingestion, storage and transformation
• Data analytics
• Dashboards