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Design of Self Rescue Equipment for High Rise Building Fire Based on Integrated Innovation Theory

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Advances in Artificial Intelligence, Software and Systems Engineering (AHFE 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 271))

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Abstract

Research purposes This paper focuses on the difficulty of fire rescue - height problem, aiming to design an intelligent self rescue equipment. Research process (1) through the desktop research method to analyze the competitive products of the existing fire self rescue products, summarize the characteristics of the product. (2) Questionnaire survey and user interview were conducted to investigate the psychological status, behavioral response and real needs of disaster-affected users. (3) Based on the integrated innovation method, the innovative elements are optimized and integrated to design an intelligent self-help device. Conclusion This paper outputs an intelligent smoke prevention and drug storage robot, which provides a reference for the design of fire rescue products from the inside of buildings. It is committed to realizing the intelligent task of fire prevention and rescue and building a sustainable development direction.

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References

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Acknowledgement

Thanks for being sponsored by Shanghai Pujiang Program.

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Authors and Affiliations

  1. East China University of Science and Technology, Shanghai, 200237, People’s Republic of China

    Chang Zong & Zhang Zhang

Authors
  1. Chang Zong
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  2. Zhang Zhang
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Corresponding author

Correspondence to Zhang Zhang .

Editor information

Editors and Affiliations

  1. Institute for Advanced Systems Engineering, University of Central Florida, Orlando, FL, USA

    Tareq Z. Ahram

  2. University of Central Florida, Orlando, FL, USA

    Waldemar Karwowski

  3. Department of Pathology, College of Medicine, University of Saskatchewan Royal University Hospital, Saskatoon, SK, Canada

    Jay Kalra

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Zong, C., Zhang, Z. (2021). Design of Self Rescue Equipment for High Rise Building Fire Based on Integrated Innovation Theory. In: Ahram, T.Z., Karwowski, W., Kalra, J. (eds) Advances in Artificial Intelligence, Software and Systems Engineering. AHFE 2021. Lecture Notes in Networks and Systems, vol 271. Springer, Cham. https://doi.org/10.1007/978-3-030-80624-8_55

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