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This study addresses battery failure in motorized wheelchairs, which are essential for the mobility of individuals with disabilities. The main objective was to concept a comprehensive Dataset comprising six attributes that directly impact battery life, consisting of 498 instances. Using the Random Forest algorithm, we demonstrate the ability to accurately predict battery failures. The results highlight the necessity for proactive measures to prevent battery degradation and extend its lifespan.

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A New Dataset for Analyzing Battery Failures in Wheelchairs

  • 会议论文

  • 发表日期：

    2025年

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  • William M. Manzolli,
  • Tiago B. Rickes,
  • Giancarlo Lucca,
  • Lizandro de Souza Oliveira,
  • Adenauer Correa Yamin

摘要

This study addresses battery failure in motorized wheelchairs, which are essential for the mobility of individuals with disabilities. The main objective was to concept a comprehensive Dataset comprising six attributes that directly impact battery life, consisting of 498 instances. Using the Random Forest algorithm, we demonstrate the ability to accurately predict battery failures. The results highlight the necessity for proactive measures to prevent battery degradation and extend its lifespan.