Another key project in progress at Intel Research Pittsburgh is IrisNet (Internet-scale Resource-Intensive Sensor Network Services). Webcams and other sensors are spread throughout the environment, collecting vast amounts of potentially useful data, but there are no effective tools to query the data. The IrisNet research team is working on a solution. The team is developing a scalable software infrastructure that will enable users with Internet access to query Webcams and other globally distributed collections of high-bit-rate sensors.


"IrisNet is a strategically important technology, a real complement to the mote-style sensing being advanced at Intel Research Berkeley," says Satya. "Both of these sensing technologies are important to enable the ubiquitous computing environments of the future."

The motes pioneered at the Berkeley lab are referred to as "smart dust" because they are tiny, simple machines that are inexpensive enough to be disposable. IrisNet uses much larger sensors, dubbed "brilliant rocks." "The computers we're using have CPU and memory comparable to laptops or handhelds," says Satya. "Compute-intensive algorithms that could not be run on a mote can be run successfully on an IrisNet sensing agent." For example, a sensing agent could handle vision algorithms, such as face recognition code powerful enough to enable identification of a person standing in front of a camera.


IrisNet Research Leads to Innovative Joint Course
The IrisNet research surfaced issues that went beyond the computer science realm, leading to an innovative collaboration between Intel and Carnegie Mellon. Satya explains: "By the fall of 2002, a significant amount of research had been done in the IrisNet project, and it became clear that we were dealing with more than technological issues. Some of the questions that arose from the research involved expertise that went beyond our lab's computer science expertise. They involved privacy and public policy issues."

To address such issues, the team came up with the idea for a graduate level course that would be jointly developed and taught by lab researchers and Carnegie Mellon faculty in several disciplines, including public policy and computer science. In spring 2003, the new interdisciplinary course, "Internet-Scale Sensor Networks: Design and Policy" was offered for the first time. The class filled quickly and enrollment had to be limited largely to Ph.D. students. "It was a very highly subscribed and appreciated course," says Satya.

The course included "hands on" projects that involved improving on IrisNet or building new applications of sensor networks. Intel contributed the Berkeley motes hardware and software and IrisNet software as well as notebook computers with cameras to project teams.


Plans are to offer the course again, perhaps as early as fall 2004. "This is a win-win for Intel and Carnegie Mellon, and without both participants it would not have been possible," says Satya. "Students got a brand new course on a timely, important topic and 'hands on' experience with IrisNet and mote technology, not just the concepts involved. This would have been very hard to accomplish without the lab." Intel benefited also, from new ideas generated by the class and from the greater exposure of IrisNet to the larger academic community. "As a result of the class, almost two dozen graduate students have now learned in depth about a technology that is strategically important to Intel," says Satya.