1. Visualizing IOT Data for Smarter Decision Support Systems
Devi Kyanam & Joe Wartick
January 12th, 2017

2. Agenda Background Problem Definition High-level Architecture
Visualization
Q & A

3. IOT and Connected Devices
Exponentially increasing development of machines that can communicate data to other machines
Retrofitting options for existing devices to allow them to communicate machine to machine (making them “Smart”)
Estimates of devices capable to machine to machine communication (“Smart” Devices):
2012 = 5 billion devices
Today = 20 billion devices
2020 = 50 billion devices

4. Application of Internet of Things in Target Property Management
Enables ability to remotely control and troubleshoot in-store assets from Target Headquarters such as Refrigeration, Heating, Ventilation, Cooling, and Lighting equipment
Allows implementation of efficient data driven asset and energy management strategies near real time

5. Properties Network Enabled Assets
HVAC:
Zone Temperatures
Component Functionality
Influences Guest Comfort / Energy
Lighting:
Lighting Status (%)
Scheduled Changes to Lighting
Influences Brand / Energy
Refrigeration:
Case Temperatures / Dew Points
Component Functionality
Influences Food Spoilage / Energy
Electrical Submetering:
Electrical Usage by Area
Detect Power Outages / Surges
Influences Energy
Irrigation:
Water Consumption / Runtime
Potential Leak Detection
Influences Brand / Water Usage
Trash Compactor:
Pressure within Unit
Estimates Fullness of Unit
Influences Hauling Costs

6. Store View - Retail Perspective

7. Store View – Asset / Equipment Perspective
* Note: Numbers and metrics displayed are not accurate and only for illustration

8. Problem: How to identify problematic dehumidification units
Context: Condensation during summer months is problem for retailers across the industry. Dehumidification units are designed to reduce humidity in stores, resulting in less condensation. What could be done to proactively address condensation? Can we use data to identify and rectify problematic dehumidification units? How do we communicate to members of field operations teams to address issues effectively? How do we keep this communication simple and actionable?

9. High Level Architecture

10. Visualization: Communicating Summary Level Data

11. Visualization: Communicating Detailed Level Data

12. Visualization: Key Takeaways
What action should be taken based on the visualizations that you create and what metric result will signal that action
Summary metrics should shape high-level decision making and users should know what action will be driven from these visualizations when certain
A visualization that does not provide value will quickly be discarded by users
Involve your users in creating visualization to ensure it is most effective