CPSLab - Equipments and Testbeds

Smart Vehicles and Communications

iRobot Create

iRobot is a programmable small robot that we used to simulate a vehicle. It has various sensors to provide feedback about speed, directions and environmental obstacles.

USRP Software Radio B210

USRP is the commonly used software defined radio for deploying new wireless communication protocols. Our B210 kit contains the motherboard (for protocol and control), daugther boards (for signal process) and dual antennas.

Laptops and Tablets

Several laptops are used as on-vehicle control units. In addition, Windows Surface tablets are adopted, which are products from Microsoft with the classic Windows operating system and an attachable keyboard.

VSmart Testbed

VSmart is a DSRC-enabled smart vehicle testbed established at CPS-Lab, McGill University, and is partially supported by General Motors Company.

3D Motion Sensing and Gesture Control

Leap Motion Sensors

A number of Leap Motion sensors are used in undergrad/grad students research projects, including in-vehicle gesture control, fast handwriting recognition, gesture dial pad design, etc.

Kinect for Windows V2

Kinect for Windows v2 brings the latest Microsoft technologies (e.g. new IR capabilities, 3D visualization, expanded field of view, etc.), enabling depth sensing, 1080p color image capturing and numbers of applications that allow people to interact naturally with computers.

User Behavior Tracking System

The system uses Leap Motion sensor and Kinect V2 to track user hand gestures and body (head and arms) pose directions.The Leap Motion sensor is connected to the laptop via USB 3.0, reporting hand micro movements. The Kinect camrea tracks human body and head position and report the direction of the user face to the system on real time.

In-Vehicle Driver Gesture Control Study.

In-Vehicle sensing system uses one Leap Motion sensor and one Kinect camera to track driver hand motion and eye distraction problem. The Leap Motion sensor is able to detect micro movement of dirver's hand in a small area, which enables in-vehicle gesture recognition. The Kinect camera is used to detect driver eye gaze directions and analyze the driver distraction problem.

Mobile computing

Android Mobile Devices (Smart Phones, Watches and Tablets)

In both the commercial market and the research community, Android devices are the most widely accepted mobile devices. Its open-source nature makes easy the development of various customized applications and testbeds upon different resesarch demands. Its abundant models also give us the convenience of accessing to all kinds of mobile hardware as well as powerful embedded sensors. Our devices cover all the nexus phones originally designed by Google.

Automatic Application Stress Test

This test suite automatically simulates the real-world use cases of the mobile devices and provides comprehensive stress tests. It can be used to significantly improve the application test efficiency and robustness.

LocME: Human Locomotion based Indoor Localization

Modern mobile devices feature with versatile sensors, including accelerometer, gyroscope, magnetometer, etc., which can be used to detect the human locomotion. Combining it with an indoor map, LocME seeks to locate the user employing soly the inertial sensor data, providing new possiblity for indoor localization.

Real-time Control Testbed

Quanser Universal Power Module 180-25B

The Quanser Universal Power Module UPM-180-25B is a power amplifier designed to drive high-powered systems. The amplifier consists of an on-board current-controlled pulse-width modulated analog output, an independent DC power supply for powering sensors, an analog input interface and embedded safety circuitry.

Quanser Q4/Q8 Extended Terminal Card

The Quanser Q4/Q8 Extended Terminal Card is a robust single-board PCI- based solution developed for multifaceted control systems and complex measurement applications. With its wide range of inputs and outputs, we can easily connect and control a variety of devices instrumented with analog and digital sensors,

Quanser HFLC

The High Fidelity Linear Cart (HFLC) system is ideally suited to introduce advanced control concepts and theories relevant to real world applications of servomotors, taking the classic inverted pendulum challenge to the next level with an array of experiments including double, dual and triple inverted pendulums.

Real-time Control Testbed

The above devices form testbed, which allows us to implement and evaluate real-time control algorithms.

Sensing Platforms

Sensing Platforms

Sensing platforms, including CrossBow TelosB motes, MicaZ motes, Intel Imotes, CH4 sensors, soil sensors, and etc.

Green Computing Devices & Testbeds

The Watts up? PRO model can record all the data as fast as once per second so you can see the load profile as it changes over the course of a day, week , or any time frame desired. The meter is in the same housing as the standard model and the LCD display operates exactly the same. But in addition, there is a USB connector on the side of the meter. The meter comes with needed software and a USB cable (same type as for digital cameras) to download the data directly to a PC.

The Agilent Technologies 34410A builds on the industry-standard 34401A. The 34410A adds improved accuracy, improved measurement speed and throughput, LAN and USB connectivity and expanded measurements.

We built a small prototype testbed to demonstrate the effectiveness of Geographical Load Balancing for data center power management. We use the left three machines to emulate three datacenters in three different locations, and use the rightmost one to generate traffics from the clients.

The SPOT System

Thanks to the generous donation and support from Prof. S. Keshav’s INFORMATION SYSTEMS AND SCIENCE FOR ENERGY (ISS4E) group at University of Waterloo,CPSLAB is also equipped with the SPOT system.

SPOT system is developed by the ISS4E Lab, which aims to make offices more comfortable and office buildings more energy efficient. The SPOT project is also open to other universities and research groups for collaboration. "It has a temperature sensor, a motion sensor, and a fan/heater which are all connected to a Raspberry Pi. SPOT* learns user preferences during a training period and uses that training to control the fan/heater."