You are currently viewing Data Nerd Diaries #1: BE QUIET! A deeper dive into noise pollution

Data Nerd Diaries #1: BE QUIET! A deeper dive into noise pollution

We thought it would be entertaining for you to get a first-hand view of what it is like to see the data world from our perspective, so welcome to our first edition of the Data Nerd Diaries.


Ask anyone if they’re concerned with pollution derived from internal combustion engines, and if they deem there is a problem, they’ll almost certainly answer the issues are with fuel emissions. State and private organisations are making great strides to reduce emissions (or hide them — I’m looking at you Volvo).

Reducing emissions usually comes from more efficient vehicles that guzzle less fuel. Funnily, these vehicles are not necessarily cheaper as the cost of owning a car keeps going up as the fuel consumption per km keeps going down.

However, here are a couple of other forms of pollution vehicles that will potentially become the target of the next rounds of regulation.

There are currently several hush-hush trials beginning and already started by local governments and transport authorities designed to create a mesh network of sensors across neighbourhoods and towns. The sensors are designed to collect information on temperature, weather, humidity, light levels and sounds.

The mesh network of these devices will provide live data feeds of what’s going on around your home. The benefits of such a network — if the data is made available (to those who know how to use it) might be to have a sunlight profile closer to what you’d receive if you were investigating solar. A more targeted humidity level might mean you make better choices of what to plant, or it may mean councils could start to target low humidity areas as opportunities for local ‘terraforming’ by improving the local greenery.

The opportunity from noise is also lucrative. A mesh network of sound sensors, all finely tuned with an accurate clock, could mean noise triangulation. The chance for police to know where a gunshot came from. The science community and emergency services could make use of light night strike information. The council could be proactive in locating and taking action against loud canines or monitoring bird communities’ health.

In all, it can help build a profile of noise and start to define a “quiet” neighbourhood using benchmarking empirically. This is why real-estate companies are interested in the data and are willing to fund the project.

Noise pollution sensors aren’t new, but they’ve become more mainstream, especially by Airbnb property owners who wish to know if their tenants are having a loud party. Making this topic fleet-related could also help identify the source of noisy cars, either that of hoons, goons or industry. Police would have another option for law enforcement, to track a vehicle by sound where it is and going even if it’s beyond the line of sight.

Consider there are many highways around the world fitted with sensors in the lane dividers; these sensors can pick up the sound of a car engine and identify that specific engine for the next 40 km as it travels along; this type of data is currently used for traffic authorities to monitor the flow of traffic. Police might decide to call off a dangerous chase of young people knowing that the car’s engine noise print has been recorded. It could simply be that the guy down the block who installed the loud muffler is getting picked up on neighbourhood mesh and is single-handedly lowering the property values due to his noise level – an interesting liability.

Another unsung hero of vehicle pollution is wind. The wind generated by a vehicle dramatically increases the dispersal of emissions through a neighbourhood. Those speed limits posted at 50km/h aren’t just about being able to break in time to stop hitting a kid getting a ball in the street. It’s also about the dispersal of emissions from vehicles into airways where people are living. A good reason for the change to electric cars is that the emissions are reduced locally where people live and work where there is less opportunity for carbon sink.

The final form of pollution I’ll discuss when it comes to cars is an interesting one with a half solution. Vehicles generate an awful lot of light pollution. Anyone who’s driven at night, especially during spring, and has had their vehicle covered in insects because of their headlights, streetlights, or a combination of both knows the pain of seeing their car riddling.

However, if we pause and put our green hats on, those were insects that were part of a food web – they were supposed to be food for frogs, turtles, birds etc. An exciting solution to light pollution from cars and lighting highways comes in the form of self-driving vehicles. Self-driving vehicles do not need the same intensity nor the same wavelengths of light required by humans to drive a car at night.

There is on the horizon the ability to drive low light-emitting vehicles again lowering the pollution contributed by cars. Who knows how a soft-light, low-noise car will be received? Indeed, animals large and small might never hear nor see the car coming to speed them on their way. Maybe the self-driving car sees them first, and it creates noise and sound to avoid a collision.

Either way, there are some interesting problems and solutions on the horizon, all of which will require lots of data and rich analysis.

Brodie Ruttan

Brodie's specialties lie in Data Janitorial work and business empathy to deeply understand what a client, employee, and business is trying to achieve. These skills combined help businesses bring their numerous, disparate, unrelated data sets together to achieve insightful results.