This document discusses considerations for Internet of Things (IoT) solution design. It outlines key factors such as objectives, operational environment, technology environment, data consumers, analytics strategy, and data framework. It provides an example of how Intel's edge analytics platform can reduce data transfers by analyzing data at the edge. The document also describes Intel cloud services, edge and cloud analytics, and an end-to-end HVAC monitoring system using Intel hardware and software.

1. The Internet Of Things
Tiffany A. Sargent
IoT Senior Solutions Architect
Intel Federal LLC.
“Things” to consider in your solutions planning

2. INTEL: ENABLING THE IOT FOR 30 YEARS
Retail
CONNECTED  MANAGED  SECURED  DATA ANALYTICS  SAFETY
ManufacturingAutomotive
Energy GamingImaging Digital
Surveillance
& Security
Military,
Aerospace &
Government
Health

3. Considerations in IoT Solution Design
Objectives, Problem Statements, Use Cases
Operational Environment (People, Processes, Business) – Internal and External
Technology and Data Environment (Green vs Brown Field)
Data Consumers
Analytics & Compute Strategy
Data Interoperability Framework ( Data DNA, Data Policy, Data Governance, Data Quality)
Intel Confidential
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4. Intel Cloud Services
Intel Cloud Analytics
Local Cloud
Intel Technology - Use Case Example
Analytics Visualization Solutions
APIs
Intel Hardware
• Smart Sensor
• Gateway
DevelopersIntel Edge Analytics
End to End System:
Intel Sensor, Gateway, Edge Analytics SW, Cloud Analytics SW

5. Intel Cloud Services
Intel Cloud Analytics
Local Cloud
Intel Technology - Use Case Example
Analytics Visualization Solutions
APIs
DevelopersIntel Edge Analytics
“Intel’s Edge Data
Analytics Platform”
reduced data to 5-20
megabytes per day with
Edge Analytics Compute
Originally the Sensors
generated 1 gigabyte per day
Intel Hardware
• Smart Sensor
• Gateway
End to End System:
Intel Sensor, Gateway, Edge Analytics SW, Cloud Analytics SW

6. IOTG
Edge-to-Cloud Distributed Analytics
Instrumented HVAC Machines
• Energy data from smart sensors & HVAC controller
input gateway is cleaned, averaged, encrypted and sent
every 15 minutes to customer and to cloud.
• HVAC Operational Event data synthesized from high
speed data sent on event to cloud analytics.
Remote & Centralized Data Visualization
• Unit dashboard with near real time energy data
• HVAC Fleet management dashboard and
reports
• Aggregated reports for building-wide
performance; financial impact
Users (Personas)
• Sales & AEs: Point customers to potential savings offered by
intelligent HVACs.
• HVAC Installers / Contractors: Use baseline data to do initial
commissioning of HVAC performance.
• Factory Service & Support: Identify and disposition
equipment failures, out of spec operation.
• Energy Services: Provide fleet demand / response services to
customers in conjunction with participating electric utilities.
• Building Managers: Continuously commission (est. 15% yr. by
yr. energy savings over single commissioning) HVAC
operation.
• Energy Services Professionals: Use services to survey
building electrical energy performance by combining basic
services with advanced load recognition abilities.
Cloud Analytics
• Presentation of individual and aggregated fleet data
• Recognition of subsystem operation tracking/trending
• Tracking and trending of consumed energy data
• Tracking of load and operational error events
• Tracking and trending of power quality events
• Fleet Demand / Response management
• Fleet Energy Efficiency management
Cloud Services
Cloud Analytics
Edge Analytics
• Data Cleaner / averaging (present only significant data)
• Alarm flag (Power Quality & Load excursions)
• Gateway API for input and output
Developers (using SDK / API)
• Custom reports
• Custom equations for alerts, tracking and trending
• Decision support using collected data and
customer’s algorithms
Complex End to End System Delivers Intelligence 9

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