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Demo listing. This page uses illustrative seed metadata to demonstrate the Atlas. Claims shown here are not verified product facts.

CivicEar

Low-cost smart-city noise classifier that labels urban sounds (jackhammer, gunshot, street music, horns) on Raspberry Pi–class nodes using…

A low-cost smart-city noise classifier that labels urban sounds (jackhammer, gunshot, street music, horns) on Raspberry Pi–class nodes using MFCC + SVM/KNN — going beyond dB maps to actionable noise type.

DemoDeployment-Ready FoundationfazeZERO VerifiedProprietaryInternet of Things & Edge

Last verified 15 Sept 2026 · Updated 23 Sept 2026 · Metadata v4

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Configuration + implementation engagement

Problem

Municipal environment and public-safety units that must refresh END-style noise maps and respond to complaints, but today only store SPL averages every few years.

Outcome

A deployment-ready foundation that teams can configure into production.

Who uses it

  • Operations Analyst
  • Solution Architect

Key capabilities

  • Core workflow

    AI-assistedIncluded

    Primary operating workflow for this foundation.

  • Document intelligence

    AI-assistedIncluded

    Extract and ground decisions from operating documents.

Typical workflow

Primary operating flow

Trigger: An operator starts the primary use case

  1. Task

    Stage 1: Capture inputs

    Operator

  2. AI-assisted

    Stage 2: Assist with draft

    System

  3. Human checkpoint

    Stage 3: Human approval

    Approver

Task Automated AI-assisted Human checkpoint Decision

About this foundation

On-node urban noise typing. WHO guidance cites bedroom <30 dB and classroom <35 dB; END 2002/49/EC demands multi-year noise maps, yet harmful events last minutes and same dB can be music or menace. CivicEar productizes MFCC features with SVM/KNN on Pi Zero W + mic HAT, ~3042 UrbanSound8K/Sound Events clips across eight classes, 85–100% accuracy, and sub-second KNN train/test on-device.

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