Initiatives For the Planet
Chung Lern Lee, Computer Science Student
Reducing the amount of energy used by computers has become increasingly important as systems' performance becomes limited by temperature.
However, the environmental issues associated with the energy required to power the Internet revolution are substantial. Moreover, mobile systems' functionality is often limited by the charge life of batteries.
The PM2 project, in NICTA's ERTOS group with UNSW COMPUTING students, is looking at ways of reducing the energy consumed by computers, especially in embedded systems (those devices with chips built into them). Their present research is investigating some common misconceptions regarding the impact of frequency and voltage scaling on both system performance and energy. They have found that many of the assumptions used by other research groups worldwide to develop energy-saving algorithms are incorrect.
Using these revised models will allow the development of algorithms for selecting frequencies which save much more energy than previously possible and it will also allow a system designer to work out when the system's sleep modes are best used. Ongoing research aims to address some other assumptions made by system designers in this field. This research will lead to lower power consumption levels and reduce these devices impact on the environment.
Improving Traffic Saves Fuel
The Smart Transport and Roads (STaR) Project is using advanced information and communications technologies to help solve Australia's traffic management problems.
With better information and modelling capabilities provided by STaR, traffic controllers will be better able to predict and respond to traffic build-ups, and accidents. The project will improve traffic sensing and surveillance, develop reliable and secure communications over wide area wireless mesh networks, build new algorithms and models for traffic control, and explore multimodal user interfaces to streamline control room operations.
STaR's vision uses cameras on top of every traffic light and software algorithms to detect traffic build-up and provide information not currently available from the wire loop sensors, such as the queue length and types of vehicles in the queue.
This more comprehensive sensory input, and the latest mathematical and computational techniques, establishes an understanding of how traffic is flowing over the wide area network of roads. It uses that information to compute changes at the level of each traffic light to optimise traffic flows across the entire network, rather than just at individual intersections.
The project aims to deliver more reliable travel times and reduced traffic congestion, which leads to fuel savings and a reduced environmental impact.
