Noise is one of the main environmental risk factors to health. It is estimated that in Western Europe, 1.6 million years of healthy life are lost annually due to road traffic noise. DBWAVE, an ISQ Group company, has developed an innovative solution, incorporating artificial intelligence, to address this problem, helping various sectors of industry and public and private entities.
Exposure to environmental noise can lead to stress reactions, sleep disturbance, mental health and well-being, cognitive impairment in children, as well as negative effects on the cardiovascular and metabolic systems. The WHO has identified noise as the second most significant environmental cause of disease in Western Europe, after air pollution.
This reality has put increasing pressure on organizations that are related to noise emission, such as transport infrastructures (airports, roads, railways), energy production and distribution, entertainment and leisure activities, as well as on public entities responsible for land management, such as municipalities.
Also governments and the European Union, along with most international organizations, recognizing this reality, have been setting targets, rules, and sanctions, in order to create conditions for the reduction of this environmental problem.
It is in this context that the MIRA project emerges, an innovative solution from DBWAVE, an ISQ Group company, which consists of the development of an intelligent system for monitoring environmental noise, with multiple configurations, consisting of sound level meters and sensors that communicate with a platform for data management, processing and analysis, with the ability to detect and classify different types of sounds by incorporating artificial intelligence, as well as notification of warnings and information for decision making.
This system will help various sectors: from industry to transport operators/infrastructure, to municipalities and all private and public entities that are responsible for compliance with noise legislation and regulations, and/or want greater efficiency in managing their production equipment, improving the production cycle.
How it works:
In order to achieve the defined objectives, the proposed solution consists of an Intelligent Environmental Noise Monitoring system (MIRA), consisting of sound level meters and sensors (hardware) that communicate with a data management, processing and analysis platform (software), with the capacity to detect and classify distinct types of sounds and sound events, by incorporating artificial intelligence.
The general concept of the proposed solution is illustrated in the following figure.
- One or more networked sensors/noise monitors, to measure and process sound signals in outdoor environments, with more or less local analysis and processing capability – typically they will be sound level meters or monitoring stations of accuracy class 1, and in certain applications simpler IoT-type sensors may be suitable;
- A data acquisition system collected by sensors that allows continuous monitoring of noise indicators (short LAeq and derivatives) and with access to the sound signal (audio) recorded for detailed analysis, whenever a trigger situation is pre-detected in the equipment itself (configurable) or continuously, in audio streaming or by intermittent sending of audio packets stored in the equipment;
- An integrated digital platform, MIRA, to (i) receive, store, and process data, (ii) monitor noise indicators and sound signals in real time, or historical information, (iii) analyze sound data with artificial intelligence algorithms;
- Artificial intelligence algorithms to detect patterns and identify specific and known sounds, detect anomalies in sound signatures and detect external noises or contaminants from sound samples