Artificial Intelligence Software
GE Healthcare - AI Assisted Imaging Software
With conventional imaging technology, such as MRI machines or your standard X-Ray machine, it takes about an hour to obtain images for review by Radiologists. With advancements in GE’s imaging equipment in the field and the Healthcare cloud applications, the scanning time can be less than 10 minutes, making scanning a quicker and a more comfortable process. My task is to integrate a new design system components and AI driven features into an existing GE Healthcare cloud
based application.
(Image Left: Simulated Patient Data - GE Health Cloud Application)
Previous Design
GE Software's design system was based on Bootstrap and marked a first step toward designing for the Industrial Internet of Things in 2013. Through research and working with product design leads and customers, I learned that the needed to improve the clarity, contrast and legibility of the application. I began investigating a direction driven by typographic simplicity: rhythmic spacing, clear visual hierarchy and accentuated amounts of white space.
(Image Right: Old version of the GE Health Cloud Application)
Redesigned Behavioral and Visual UX
I have instituted a new design language that is built on the Google Polymer framework. It empowers designers and developers to rapidly build consistent and horizontally aligned applications. Using this framework I updated the behaviors and UX of the cloud based software.
(Image Left: Redesigned version of the screen above)
Industrial IOT Mobile App
GE Digital - Edge IoT Managment App
As GE endeavored to build a Predix based industrial IoT suite of products, there came a need to support Field Engineers work at the edge. The Edge being the onsite locale that connects industrial machines to a network of gateways, nodes and software. This network enables remote applications (applications not at the user's site) to deliver sensor data to be transferred to the GE Cloud or on premises solutions.
To support these field engineers I conceived, and designed a mobile provisioning application for engineers onsite.
(Image Left: Wireframe for Field Engineer Edge Application)
Created New Mobile Design System Components
Predix Design System did not include mobile app components. I created a new design language based on the existing design system style and standards. I tested the designs against accessibility and localization needs. As well as delivered a native OS and web based applications.
(Image Right: New App Design I created for lights on and lights out views)
Redesigned UX / Research in the Field
This new mobile design language was built on the Google Polymer framework. When deployed in the field I followed up with users to learn how the implementation of the app has worked in practice. I then refine my designs based on feedback and product owner business requirements.
(Image Left: Redesigned version of the screen above)
Edge Network IT Application
GE EdgeManager Application - Edge IoT
The EdgeManager SaaS Application arose from a need of customers to manage their lndustrial IoT resources remotely via the Predix Cloud. Essentially, customers have large equipment in the field, such as wind turbines or jet engines, etc. These machines have thousands of sensors emiting millions of data points per nanosecond. Edge devices running Predix Edge software commit that data to the cloud where the EdgeManager application can do operations on the data, run analytics, diagnose alerts, and make changes to the network remotley.
Geospatial View for Alert Notification
I innovated on the traditional alerting UI of GE applications by creating a geospacial map view that could toggle back to a list view. This view became available due to my advocating on behalf of subject matter experts whom I researched in the field. I worked with engineering leads to deliver the IP address and GPS coordinates data needed for deployment on a map design.
Design Patent Awarded
I was awarded 1 of my multiple patents for my novel approach to a problem related to "context" viewing of networked node relationships. I merged a tree view of parent/child organization, with a peer to peer topography view of a network. This view allows users to traverse their logistical understanding of how networks are deployed with their dependency relationships in a single view.
Design Process & Research
Onsite Research & Subjective Learning
I work with others to deliver key insights from research execution. As in the image to the right, I am seen here learning from Field Engineers at a Power Plant. This research visit was 3 days total and I worked with 3 other design researchers to deliver our findings. I planned the visit 2 weeks in advance and mentored junior designers on planning practices.
Classification, Semantic Efforts & Synthesis
Perhaps the most important part of the design process, I build up an understanding of personas, user journey and workflows. Then I perform audits of existing materials and comparative study of established patterns.
I will develop a brief that captures the research findings and perform tests against initial design patterns that connect to the the synthesized data.
Presenting to Audiences, Engagement & Sharing
I take care to understand problems deeply, and share my findings with other team members. As in the image to the left, I am showing the entire GE Design group the work I completed with EdgeManager and how GE addresses Edge IoT.