Private Blockchain and Federated Learning-Based Edge-Iot Platform for Secure Urban Noise Monitoring

The Internet of Things (IoT) has enabled many services and applications that benefit the urban landscape. One of these services is urban noise monitoring. Noise pollution is an issue that can disrupt the lifestyle and well-being of the populace. An urban noise monitoring system can help analyze the noise levels around the different areas in the city to isolate and address disruptive locations. However, it is a service that heavily relies on its training data. It must remain secure to keep the monitoring system accurate and reliable. So, we propose a secure urban noise monitoring system using a private blockchain and Federated Learning (FL)-based edge-IoT platform. It combines the immutability of blockchain technology with the privacypreserving capabilities of FL, reinforcing the security of training data within an IoT network. Based on our tests, our proposed platform was able to preserve the security, privacy, and integrity of the urban noise monitoring system.