An implementation of a distributed sound sensing system to visualize the noise pollution

The noise pollution is still a troubling problem for us, especial in hospital, library, baby-care center, etc. Although many decibel-meters are applied to those environment, which indeed must be kept quit, but the decibel-meters can only detect the noise pollution limited to nearest area around the device. We will face the incorrect measuring data from the decibel-meters in bigger space like library. According such problems mentioned above, maybe we use more decibel-meters around different areas to a better solution. We have such problems waiting to be solved like averaging the measuring data, inter-connecting the cross-data between the devices with the existing decibel-meters in the market. So our study wishes to implementation a portable, small-scale and internet-based sound-detective prototyping by using Internet of Thing (IoT) technology to offer a better solution mentioned above. So our approaches are that we use the cheaper materials and low-precision sensor and single-chip microcomputer (MCU) with WIFI connection ability to develop a dedicated sound-detective device. The devices can be developed under very low-cost without any display on it, but all sensor data will be sent into the clouding system and be displayed on mobile-devices by only using browsers. The proposed prototyping device maybe support the visualized-display like gauge chart supported by google clouding technology. The system architecture of our solutions will be scalable and distributed, so we call the device entitled to the distributed sound sensing system (DSSS). Finally, we will open our results to public (Open Source & Open Hardware) and DSSS can be used over-spread and enhanced rapidly in the future, that will be the best contribution of our research.