Loud traffic noises can prevent people from getting a good night’s rest and break their concentration during work. Now, researchers at Nanyang Technological University’s School of Electrical and Electronic Engineering (EEE) have come up with not one, but two methods to tackle these and other noise pollution problems.
The team has developed an active noise control (ANC) system that can be installed at homes’ windows, as well as an automated monitoring system that can help authorities to nab excessive noise offenders.
The inventions could give people peace of mind in their homes and protect their health, with the World Health Organization calling noise pollution “an underestimated threat that causes a lot of short and long–term health problems”, including sleep disturbance and poorer work and school performance.
While most people in Singapore close their windows to mute external noise and switch on their air–conditioners for coolness and ventilation, this is not an environment-friendly solution.
The EEE researchers’ ANC system consists of an array of small microphones and loudspeakers placed near windows. When the microphones detect incoming noise, the loudspeakers generate sounds that are the same in amplitude but opposite in phase – anti–noises, in effect, that cancel the incoming noise.
Such active noise control technology has been used in headphones, industrial plant air–ducts and car exhaust pipes, but not in homes. When pitted against typical traffic sounds of 85 A–weighted decibels, or dBA — a form of measurement that takes into account how the human ear perceives loudness — the EEE system achieved noise reduction of more than 10 dBA.
EEE Professor Woon–Seng Gan said the system can also play soothing soundtracks to mask residual noises in the room: “This hybrid approach of noise control is more suited to cover a broader bandwidth of noise with changing noise patterns.”
To further improve and tailor the system for specific neighborhoods, a moving vehicle with microphones could be used to capture the typical noises in the estate. “This information can then be programmed into the memory of the noise controllers to generate the best anti–noise wave–fronts,” Prof Gan said.
Mitigating noise pollution, however, is only part of the battle. The EEE researchers also designed an automatic noisy vehicle detection and surveillance camera system — dubbed NoivelCam — to track moving vehicles on roads and capture footage of those that exceed stipulated noise level thresholds.
The government agencies currently set up road blocks and check vehicles’ tailpipe noise emission levels manually, but this enforcement method is carried out less than 10 times a year due to the huge manpower cost incurred per road block.
The checks are also conducted by getting the driver to accelerate the vehicle while it is in a static position, which may not reflect the actual noise level when the vehicle is traveling at high speed and under hard acceleration.
NoivelCam consists of two microphones, a high–speed camera to take photographs, a wide–angled video camera and a computer. The prototype was designed to monitor a single lane in expressways but the researchers plan to scale it up for multi–lane use.
The directional microphones can track vehicular noise on only the monitored lane as they weaken sounds from other directions. When the noise exceeds the stipulated threshold, the high–speed camera captures the offending vehicle’s number plate. The video camera continuously records footage for use as proof or to evaluate possible false triggers due to loud vehicles in neighboring lanes.
Tests in NTU’s premises and on a busy expressway showed that the system is generally able to differentiate between noises from the monitored lane and its neighboring lanes. Future iterations will be able to classify the acquired noise signals into different vehicle types for greater confidence in the results.
The EEE team added 3G connectivity to the system to stream the recorded data to a server, and plan to incorporate other features such as data analytic tools to generate useful information including vehicle speed, traffic density and sound level patterns over time.