Professor Vahid’s Research

Current:   Assistive monitoring   Digital mockups
Previous:   Warp processing   eBlocks

STEM Education Research


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Selected Projects

Assistive Monitoring

This project empowers people to easily setup customized in-home cameras and sensors and monitor the video and data via the web, primarily to assist family/friends in need of care, or to assist oneself (especially for the hearing/vision impaired). The project enables people to setup customized automated notifications (e.g., text message, blinking light) upon detection of critical situations, such as a person not arising in the morning, or to record data to detect longer-term critical trends, such as a person getting less exercise or frequently stumbling. The project’s novel methods emphasize people customizing the system to meet their unique and changing needs and situations, including their privacy wishes.

Assistive monitoring analyzes data from cameras and sensors for events of interest, and notifies the appropriate persons in response. The ability of the end-user to customize an assistive monitoring system is essential to the system’s practical use.

Digital Mockups

“Digital Mockups” is a joint UC Riverside/Irvine research project developing real-time observable/controllable executable models of physical systems. Such real-time models can be used during development/test of the cyber device in cyber-physical systems, such as a medical ventilator, as well as for device-user training. As depicted below, a cyber device can be connected to a mathematical model of the physical environment implemented on a computing platform. That model’s implementation represents a “digital mockup” of the physical environment. For example, a medical ventilator can connect to a human respiratory system model, a cardiac pacemaker to a model of human heart electrocardiography, or a satellite might think that it is in orbit when really it is being fed sensor data by an environmental model of space. Digital mockups enable easier testing of dangerous or expensive scenarios, more thorough testing of border cases, fully automated testing, faster testing, reproducible testing, and even a view of what’s happening inside the physical system. They are useful for test/development of new devices, for training/education (e.g., training of respiratory therapists on ventilator use), and for reproducing field errors. Digital mockups can be used directly (typically requiring bypassing a device’s transducers and instead interfacing directly to internal device processors) or can be incorporated into hybrid physical/digital mockups.


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The goal of eBlocks is to empower regular people, having no programming or electronics experience, to build basic useful electronic systems around the home, office, store, etc. We plan to achieve our goal by creating a set of embedded system building blocks – eBlocks – that regular people could easily connect together to build a huge variety of basic but useful monitor/controller systems. The key to our approach is to add compute intelligence to components that previously had none – to sensors, switches, light-emitting diodes (LEDs), speakers, etc. Adding compute intelligence to those items was previously cost and power prohibitive, but extremely small, cheap and low power processing devices now make such addition possible. Ideally, people could simply connect such eBlocks together to build basic systems.

Warp processors

We are developing a microprocessor that automatically and transparently detects critical code regions of an executing binary and remaps those regions to FPGA, resulting in 10-100x speedups and energy reductions of 50-90%. The task requires the development of on-chip CAD tools and architecture to support dynamic remapping of software kernels to FPGA. The task will include development of decompilation tools that recover high-level constructs needed for effective synthesis, and of place and route tools specifically created to be exceptionally lean in terms of time and memory, to enable on-chip dynamic execution. The FPGA architecture will be developed in concert with the tools, geared towards enabling lean tools. If successful, this task will lead to software implementations that use 10x less energy and execute 10x-100x faster than standard embedded microprocessors, by bringing FPGAs into mainstream computing.