top of page


The first 12 months stats speak for themselves

Historically noise recordings could only be deciphered using the human ear to listen to the evidence and interpret the sound. A year ago, that changed when our storage platform Sonitus Cloud took a major leap forward with the introduction of ANI – Automated Noise Identification. An innovative new AI based feature designed to interpret and categorise noise recordings without the need for human involvement.

ANI has been running for 12 months now and the stats from its developer Sonitus Systems are impressive.

ANI statistics after 12 months

1.25 million UK recordings correctly identified

90-man years saved, had a consultant listened to every recording

Last month one of our customers, Winvic Construction received a Green Apple award for their proactive noise management strategy using ANI.

Audio recordings are collected by a monitor each time a noise event occurs. On a city located project not all the sounds will be attributable to site activity, traffic and neighbour noise for example, making the job of noise spike reporting problematic.

But with the ‘march forward’ of artificial intelligence our noise monitors now have the capability to not just record ‘a’ noise event, but to tell consultants what that noise was.

Our noise level monitors from Sonitus Systems, the EM2030 and DM30 SiteSens (air particulate and noise combined), automatically upload their recordings to Sonitus Cloud. Here ANI identifies and tags every event with a noise source and quantifies each category. Accurate results are presented in clear and simple reports in the cloud, for easy identification of construction and non-construction related noise.

It is always good practice to take background noise measurements prior to construction, but the noise climate surrounding a construction site is ever changing and unpredictable, making site management and noise accountability difficult and time consuming.

Examples of non-construction noise picked up by ANI:

· Emergency service vehicles changing routes due to road closures

· Delivery scooters from newly opened facilities

· Natural events such as thunderstorms and seasonal nesting birds

We have 2 Sonitus Systems environmental monitors which utilise ANI (with the audio capture option enabled).

The EM2030 class 1 noise level monitor, perfect for situations with access or safety issues, where reliable measurements from minimum effort is required.

The DM30 SiteSens boundary monitoring station measures noise levels and air quality.

(PM10, PM2.5 and PM1, with MCERTS for PM10 & PM2.5); designed for continuous monitoring in all conditions.


bottom of page