Helping you to understand the sound environment with automated noise source detection. Automatically generate deeper insights into the sound sources you are measuring.
Automate your noise monitoring to save time and money with our EM2030 Sound Level Monitor. Capture the data you need without the effort and control noise levels with online alerts.
Manage all your site emissions with one boundary monitoring station. Combine noise and dust monitoring into a single unit to easily monitoring compliance with environmental limits.
Noisy sound sources are the most likely cause of complaints and compliance issues. Identifying the cause of high noise levels can be a labour intensive process involving hours on site or listening back to audio recordings.
ANI is our artificial intelligence (AI) assistant. ANI can automatically recognise sound sources to tell you what is causing the highest sound level readings at your measurement site.
Save time and effort by letting ANI help you identify your noise issues.
We take information from measurement sites all over the world and use that data to help identify the causes of noise complaints.
ANI can do the hard work for you to turn your noise measurements into useful actions that you can take to tackle sources of high noise levels.
Get an overview at a glance to see what’s happening at your site and take action to address what matters.
Making smart decisions about what noise sources to tackle will help to save time, effort and money.
Our smart reporting tools will identify the sources of high noise levels at your site and label audio samples for you to listen back.
You can spend your time focusing on the areas that cause the most noise issues and take steps to tackle those sources that will have the greatest impact.
A single source of truth to understand the causes of complaints or non-compliance with sound level limits. Listen back to audio samples that are triggered by high noise levels.
There is no need to wade through hours of audio clips, we do that automatically for you. Just select the category that is relevant and spend your time addressing the noise sources that matter.