Intel's Pentium IV and Microsoft Windows and Visual Studio .NET are highlighted in a discussion of the development of a machine vision system for detection of smoke. The SigniFire system separates an image into two discrete zones: one that has a steady, high brightness, and another that has dynamic, always changing, or flickering brightness. The distinct pattern of the two zones is easily differentiated with standard pattern matching methods. The pattern created by the physical aspects of fire is 'deeply embedded in our perception and thus can be exploited in the artificial intelligence of a machine vision flame detection system. Flame recognition is divisible into three primary stages. The SigniFire processing unit produces a color coded image, with the red channel assigned the time average brightness and the blue channel assigned the fluctuations factor. Clusters that contain high red and blue values are extracted and scaled to standard size in the second stage of flame recognition. In the third stage, a three-layer feed forward neural network that has been trained to recognize the flames while rejecting nuisance light sources analyzes the scaled clusters. The system can concurrently process up to eight analog video streams via two 4-channel Falcon Quattro frame grabbers. The SigniTalk I/O subsystem is a TCP/IP-based protocol that communicates with the system over the Internet/intranet by software module. The SigniFire system is being fully tested at the U.S. Naval Research laboratory.