Infrastructure-free, Deep Learned Urban Noise Monitoring at 100mW

Jihoon Yun, Sangeeta Srivastava, Dhrubojyoti Roy, Nathan Stohs, Charlie Mydlarz, Mahin Salman, Bea Steers, Juan Pablo Bello, Anish Arora

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The Sounds of New York City (SONYC) wireless sensor network (WSN) has been fielded in Manhattan and Brooklyn over the past five years, as part of a larger human-in-the-loop cyber-physical control system for monitoring, analyzing, and mitigating urban noise pollution. We describe the evolution of the 2-tier SONYC WSN from an acoustic data collection fabric into a 3-tier in situ noise complaint monitoring WSN, and its current evaluation. The added tier consists of long range (LoRa), multi-hop networks of a new low-power acoustic mote, MKII ('Mach 2'), that we have designed and fabricated. MKII motes are notable in three ways: First, they advance machine learning capability at mote-scale in this application domain by introducing a real-time Convolutional Neural Network (CNN) based embedding model that is competitive with alternatives while also requiring 10x lesser training data and 2 orders of magnitude fewer runtime resources. Second, they are conveniently deployed relatively far from higher-tier base station nodes without assuming power or network infrastructure support at operationally relevant sites (such as construction zones), yielding a relatively low-cost solution. And third, their networking is frequency agile, unlike conventional LoRa networks: it tolerates in a distributed, self-stabilizing way the variable external interfer-ence and link fading in the cluttered 902-928MHz ISM band urban environment by dynamically choosing good frequencies using an efficient new method that combines passive and active measure-ments.

Original languageEnglish (US)
Title of host publicationProceedings - 13th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages12
ISBN (Electronic)9781665409674
StatePublished - 2022
Event13th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2022 - Virtual, Online, Italy
Duration: May 4 2022May 6 2022

Publication series

NameProceedings - 13th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2022


Conference13th ACM/IEEE International Conference on Cyber-Physical Systems, ICCPS 2022
CityVirtual, Online


  • Audio representations
  • Convolutional Neural Networks
  • Infrastructure-free
  • LoRa external inter-ference
  • Low-power
  • Resource-efficient deep learning
  • Robustness
  • Smart cities

ASJC Scopus subject areas

  • Hardware and Architecture
  • Control and Optimization
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications


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