Solar System in MµSE, log10 scaling
During this period I was working at MUSE Technologies in Albuquerque, NM. MUSE merged with Advanced Visual Systems (AVS) around 2000.
While with AVS I worked with Mark Kruger and Brian Selle on projects for Consolidated Edison Company of New York (Con Edison), a regulated utility, that provides electric service in New York City. We built engineering and management tools to help analyze the primary distribution network in Manhattan. One of the Tools was called Executive Information System (EIS). The system enabled high-level users to obtain a view of the current operating conditions of the distribution network. The EIS tool displayed data from the Feeder Mapping System and some of ConEd’s internal systems that served up semi-realtime sensor data from their power network.
AVS OpenViz generated the 3D representation of system state. We used VB for the graphical user interface and created an ActiveX component with Internet Explorer as the COM container. The VB codes talked to OpenViz, and to some other COM components that marshaled data, and communicated with ConEd’s real-time servers.
EIS Small
I worked on another project for ConEd called, Interactive Display of Network Configuration (IDNC). The IDNC was designed to assist distribution engineering in the simulation of current and future network configurations under normal, contingency and restorative situations. The system allowed engineers to easily configure the distribution network and view the resulting loadflow calculations from ConEd’s simulators and servers.
The image below shows a close up view of some feeders (electrical cables) in Manhattan being viewed and/or edited.
IDNC small
I wrote a VB app that used AVS VizWorks Charts COM-based component to look at lost-profit data as a result of equipment failure for an electricity-generating power plant. The X-axis contains the date range for the data being viewed (in this case just about the entire data set). The Y-axis shows the name cause attributed to an event (in this case the power plant de-rating cause). The Z-axis shows lost profit in dollars.
Notice
the unexpected pattern in the data — the diagonal line that seems to cut the
x-y plane in half.
MUSE marketed a software development API that fell in the area that became referred to as Perceptual Computing. The main idea was to be able to present large quantities of data in a way to the user that was akin to the way the human brain receives information in the real world.
The thinking was that if we could “feed the brain”, so to speak, with data as fast as possible, using multi-modal techniques (20-60 fps graphics, voice recognition, speech synthesis, haptics, etc.), that the user would perceive, or understand the data orders of magnitude faster than with current technologies.
When I wasn’t working on client applications, I worked on enhancing the MuSE development product. See Vitae for more information.
Ken Gant[1]
and I worked on a prototype demonstration application for United Parcel
Service. We were given sanitized data[2]
representing package flow across the UPS network over a period of two weeks.
We used the Fltk API to generate the user interface. Here’s a picture of one of the tabs that controlled aspects of the visualization of the network.
Here’s a picture from the visualization of package flow across the network. The lines represent routes. The thickness of the line represents the volume of shipments along that route. The colored boxes represent shipments of packages. The colors of the boxes were based upon their SLIC code (a sort of shortened zip code).
Larger and in Sequence
images 1-6
Larger and in Sequence images 7-12
In 1999 we wrote a joint NSF proposal with Jim Meyer of Arizona State University for an education in Materials Science project to help students better understand the atomic-level processes behind X-ray fluorescence and electron microprobing
It was funded in 2000. I was the project and technical lead, and we finished the work in 2001.
Coworker Jeff Mauldin and I worked on a project called NTS — National Transportation System based upon trucking simulation data with LANL. The goal was to create a visualization of the truck (and other shipping modalities — air, train, water) routes as they evolved over time.
The following is a snapshot of day 2 showing truck and air routes departing from the LA area. The volume of shipping along a particular route was mapped to height of the “walls.” The color of the walls were mapped to the shipping type:
yellow = long distance trucking
orange = short-haul trucks
purple = train routes
blue arcs = air shipping routes
A group of about five MUSE engineers collaborated with a group of 7-10 NASA engineers to simulate the International Space station, and certain space-based scenarios.
I worked on getting the exterior models displayed…
And on Crew Departure Scenarios.
The Image below shows a simulated Astronaut inside the HAB (Human Habitat module), just before departing in the CRV (Crew Return Vehicle).