Noise pollution or disruptive noise has a negative effect on human health, such as causing stress. The many sources in our environment make it difficult to get a grip on them, and determining the impact on health is also an important challenge. TNO is helping to develop solutions through real-time insight into noise.
Noise is all around us. Technologies to measure that noise are plentiful, from high-tech sonar to track a submarine or torpedo to a low-cost sensor that measures or detects noise at home. TNO focuses on developing data models to derive even more data from noise.
Data derived from noise enables us to build models. By creating real-time noise maps of the environment and by recognising the sources of the noise, we provide information at an individual level so that employees in industry can better protect themselves against noise pollution and thus reduce the impact on their health. The identification of how noise is perceived can help employers work towards a healthier environment and the authorities can prevent noise pollution by identifying the specific sources.
A practical example of the application of noise technology is the detection of fireworks set off in the days leading up to New Year’s Eve, especially in terms of heavy fireworks. By placing approximately four or five measuring points in a city, law enforcers are able to see in an app where they need to confront the person(s) responsible.
Useful applications are also conceivable in industry. Such as oil refinery employees wearing noise protection gear based on the noise map of their workplace. But it may be the case that such a map becomes outdated, that a temporary generator is operating somewhere, or that the insulation material is just being replaced. Then an increase in the noise levels will not be visible on the noise map. But if the noise level can be calculated at any time of the day, employees are better able to protect themselves. TNO is developing the computing power required for this and can make the models in such a way that employees can act sooner.
Getting the information to be able to act earlier is one aspect. But the next question is, what other data does the noise contain? Where does it come from? What else is going on? If a leak occurs in a pipeline in a factory, it will hiss. That sound can also be traced. So noise can provide a great deal of information. TNO has the in-house expertise to further develop the algorithms, using noise recordings and events that demonstrate the link between cause and effect.
The effect on the environment is also an important subject. By modelling the movement of noise through the meteorological conditions and the environment, we can trace where it comes from. Say that the noise of a container being unloaded reaches ten homes, we can specifically indicate to the carrier what can be done about it which other times would be more suitable for unloading.