A Sonification Method for Monitoring Chemical Sensor Data

Yutian Hu, Tony Stockman, Aleksandar Radu, Ernesto Saiz Val, Nick Bryan-Kinns

Research output: Contribution to conferencePaperpeer-review

Abstract

The calibration of chemical sensors is important for ensuring signal integrity. However, for some sensors this can be time-consuming, and without prompt and adequate feedback users may be unaware of calibration errors until post-session analysis is conducted. To address this challenge, we present a real-time sonification framework designed to facilitate efficient monitoring of chemical sensor performance during the calibration stage. The system displays batches of sensor calibration data, collected synchronously, and provides auditory feedback in a sequential time-based manner. To aid users in identifying noisy behaviors in sensor data and comprehending their values, the framework employs three auditory representations: musical note sequences, speech cues, and click sounds. The iterative design process followed a user-centered approach. We detail the iterations of the design, and subsequently evaluate the final approach through a user listening test, discuss benefits and drawbacks of the design, and incorporate user feedback. Our user listening tests conducted using real world data, demonstrate that our method enables efficient detection of abnormal sensor data behaviors.
Original languageEnglish
Number of pages8
Publication statusPublished - 2 Jul 2024
EventSound and Music Computing: Immersive - ESMAE, Porto, Portugal
Duration: 4 Jul 20246 Jul 2024
Conference number: 2024
https://smcnetwork.org/smc2024/

Conference

ConferenceSound and Music Computing
Abbreviated titleSMC
Country/TerritoryPortugal
CityPorto
Period4/07/246/07/24
Internet address

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