Recently, Soundbox and China Jinan University held a joint R&D center signing ceremony to officially launch the “real-time noise big data” phase II project research and development, and jointly promote real-time noise big data monitoring without base stations.
The project is based on the noise data collected from cell phones, and the analysis and processing of the basic noise data by specific algorithms to distinguish and strip out the effective noise and the artifactual noise, as well as the classification of different noise sources by acoustic pattern recognition.
Through data encryption, noise sources are collected based on sound pressure and frequency response data only, and the data are clustered and then encrypted twice, thus guaranteeing data compliance with specifications and irreversibility.
The biggest challenge in noise pollution prevention is the full coverage of monitoring equipment and noise source tracking’, said Yin Yimin, CEO of Soundbox.
At present, temporary noise data monitoring of urban traffic arteries, construction sites, industrial plants, etc, or noise monitoring when environmental law enforcement departments receive noise complaints or routine inspections; as well as for urban planning and management departments to refer to the regional stage sampling combined with simulation derived from the “noise map” can not achieve full coverage of real-time monitoring of noise data.
The ‘Noise Big Data Phase II Project’ will be able to fill the shortage of traditional noise monitoring means unable to achieve full-coverage real-time monitoring traceability, provide more comprehensive real-time noise data traceability to urban planning and environmental protection departments, and provide dynamic noise source data analysis and reference for the smart city sound environmental management system.
The importance of the project is to form the entire technical closed loop of environmental noise data collection, cleaning, analysis, storage, and application. Real-time noise big data will also provide consumers with objective foreknowledge of the sound environment. Our data will be accessed in major apps, and citizens can check the sound environment of their rooms online when they book rooms in hotels.