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The SENTIRE—DPI-uAI project aims to develop an intelligent active hearing protection device for workers in high-noise industrial environments. Combining Internet of Things (IoT) technologies, Machine Learning algorithms, and edge-cloud architectures, SENTIRE enables selective noise filtering to preserve safety-relevant sounds while suppressing harmful ones. At the core of the system are noise-canceling headphones connected via BLE to a wearable device that integrates a DSP module for acoustic signal pre-processing and an embedded CPU for contextual analysis and sound classification. Edge communication is handled via MQTT protocol, while a serverless infrastructure enables interaction with the smart factory. The system demonstrates robust latency and classification performance, confirming the feasibility of selective audio filtering and sub-meter localization accuracy in industrial scenarios [5, 6].

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SENTIRE: An Intelligent System for Hearing Protection and Human-Machine Interaction in Industrial Environments

  • 会议论文

  • 发表日期：

    2026年

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  • Rosaria Del Sorbo,
  • Gabriele Mongelli,
  • Maria Pia Di Palo,
  • Massimo Giordano,
  • Marianna Bartolomeo,
  • Elisa Anna Contursi,
  • Chiara Maria Ragusa,
  • Colomba Pessolano,
  • Andrea Marino,
  • Simona De Santis,
  • Giuseppe Del Sorbo

摘要

The SENTIRE—DPI-uAI project aims to develop an intelligent active hearing protection device for workers in high-noise industrial environments. Combining Internet of Things (IoT) technologies, Machine Learning algorithms, and edge-cloud architectures, SENTIRE enables selective noise filtering to preserve safety-relevant sounds while suppressing harmful ones. At the core of the system are noise-canceling headphones connected via BLE to a wearable device that integrates a DSP module for acoustic signal pre-processing and an embedded CPU for contextual analysis and sound classification. Edge communication is handled via MQTT protocol, while a serverless infrastructure enables interaction with the smart factory. The system demonstrates robust latency and classification performance, confirming the feasibility of selective audio filtering and sub-meter localization accuracy in industrial scenarios [5, 6].