We see video being used as an Inescapable Data gathering technology more broadly than ever before, and across a wide range of applications. Certainly, video is used for surveillance (both in homes and across public areas), and we will later examine how video can be used by retailers in ways that now go beyond monitoring for security purposesways that allow retailers to gather customer data that was previously unavailable. In the manufacturing sector, video is becoming a key element in process automation, rapidly optimizing many activities. What has changed recently is the move to the use of all-digital video, which in turn allows for process examination and analysis by systems as opposed to eyeballs. Use of digitized video analysis driven by manufacturing needs will in turn drive significant advances and availability of digitized video as a surveillance tool in more pervasive ways (crime, antiterror, and home security). The coming pervasiveness of digitized video has been enabled by several factors, including the following:
Cognex Corporation is a leading supplier of video-based machine vision systems.[9] Dr. Robert Shillman (better known as "Dr. Bob"), CEO of Cognex, describes the changes taking place in the machine vision industry:
Dr. Bob goes on to describe the challenges that machine vision had to overcome to be useful in the "real world":
The good news: With modern CPU horsepower and years of work improving the associated algorithms, machine vision can finally solve these complex challenges. Five or so years ago, the machine vision paradigm was to communicate the raw analog signals produced by standard video cameras through coax cables back to a remote computer system that performed the analysis of all the images. These early machine vision systems were too expensive and too difficult to use for all but the most demanding applications. But, because of the increasing power and decreasing cost and size of digital signal processing chips (DSPs), modern machine vision systems can now be about the same size as a cell phone, and contain a camera, illumination, vision software, and image-processing hardware. And, because they are low in cost and compact, these "vision sensors" can be placed at every point of the production line where value is added. They automatically snap images of each product moving by, and then they communicate pre-processed results (not the images) back to the factory control systems, which take the necessary corrective actions. Much of the data gathering and processing challenges are akin to those of RFIDtons of packets of information snippets that must be stored (cached) and processed using complex-event processing models (e.g., mis-cappings on toothpaste is increasing while another system is detecting mis-feeds in the cap-loading line). And, as vision systems become more and more prevalent, more real-time information will be made available for correlation with a wider set of processes in the manufacturing complex. "For example, today, an executive at a paper products manufacturing company can now sit in his office and literally 'watch' 10 different manufacturing plants around the globe and compare their production results," explains Dr. Bob. "In today's world, it is not good enough to wait for the end-of-week manufacturing report. A business executive needs to know the exact status (including quality metrics) of all of his production facilities so that he can optimize them." In the new world of higher intercompany tie-ins, the data and images could also be made available to both suppliers and customers, in real time. Imaging is data-intensive and will strain back-end existing systems. Thankfully, the costs of key enabling technologies (disk space, processing power, and 10Gb Ethernet networking gear) are all trending downward. As a result, image data gathered from a manufacturing operation can now be "mined" more economically. Engineers can sift through millions of images and look for trends, correlations, or deviations against time, or against established specifications for components that are sourced from outside suppliers. Historically, the manufacturing segment has never had this kind of data available. Moving forward, we can predict that, because of their affordability, these systems will be used, and that data correlations will emerge that have not yet been anticipated. As in the usage of Inescapable Data technologies in the medical and commercial segments, the mining of image data will have extraordinary value to manufacturers as well. |