Acoustic traffic monitor for a smart city concept

Treball desenvolupat en el marc del programa "European Project Semester".Acoustic Traffic Monitor for a Smart City Concept aims to create a high-performance sensor that can accurately detect and analyse sound waves. The sensor is designed to have a compact form factor, low cost, and energy-efficient operation, making it a suitable solution for a broad range of applications such as security surveillance, environmental monitoring, and industrial automation. The sensor uses advanced signal processing algorithms, including machine learning, to classify and identify different types of sounds, making it versatile in its applications. The project team will use a combination of experimental and parnumerical techniques to optimise the sensor's performance and explore different ways of integrating the sensor into existing systems. In addition to the technical aspects of the project, the team will also focus on creating a viable business and marketing plan. The project will involve market research to identify potential customers and competitors, as well as determining the best pricing strategy for the sensor. The team will also explore different distribution channels and work on creating a strong brand identity for the sensor. By creating a high-performance, cost-effective sensor and implementing an effective business and marketing plan, the project aims to bring a new product to the market that can have a significant impact on various industries. The successful development of this acoustic sensor concept has the potential to revolutionise sound wave detection and analysis, making it an exciting project with significant commercial potential.Incomin

Active Self-Testing Noise Measurement Sensors for Large-Scale Environmental Sensor Networks

Large-scale noise pollution sensor networks consist of hundreds of spatially distributed microphones that measure environmental noise. These networks provide historical and real-time environmental data to citizens and decision makers and are therefore a key technology to steer environmental policy. However, the high cost of certified environmental microphone sensors render large-scale environmental networks prohibitively expensive. Several environmental network projects have started using off-the-shelf low-cost microphone sensors to reduce their costs, but these sensors have higher failure rates and produce lower quality data. To offset this disadvantage, we developed a low-cost noise sensor that actively checks its condition and indirectly the integrity of the data it produces. The main design concept is to embed a 13 mm speaker in the noise sensor casing and, by regularly scheduling a frequency sweep, estimate the evolution of the microphone’s frequency response over time. This paper presents our noise sensor’s hardware and software design together with the results of a test deployment in a large-scale environmental network in Belgium. Our middle-range-value sensor (around €50) effectively detected all experienced malfunctions, in laboratory tests and outdoor deployments, with a few false positives. Future improvements could further lower the cost of our sensor below €10.status: publishe

Active Self-Testing Noise Measurement Sensors for Large-Scale Environmental Sensor Networks

Large-scale noise pollution sensor networks consist of hundreds of spatially distributed microphones that measure environmental noise. These networks provide historical and real-time environmental data to citizens and decision makers and are therefore a key technology to steer environmental policy. However, the high cost of certified environmental microphone sensors render large-scale environmental networks prohibitively expensive. Several environmental network projects have started using off-the-shelf low-cost microphone sensors to reduce their costs, but these sensors have higher failure rates and produce lower quality data. To offset this disadvantage, we developed a low-cost noise sensor that actively checks its condition and indirectly the integrity of the data it produces. The main design concept is to embed a 13 mm speaker in the noise sensor casing and, by regularly scheduling a frequency sweep, estimate the evolution of the microphone’s frequency response over time. This paper presents our noise sensor’s hardware and software design together with the results of a test deployment in a large-scale environmental network in Belgium. Our middle-range-value sensor (around €50) effectively detected all experienced malfunctions, in laboratory tests and outdoor deployments, with a few false positives. Future improvements could further lower the cost of our sensor below €10