<?xml version="1.1" encoding="utf-8"?>
<article xsi:noNamespaceSchemaLocation="http://jats.nlm.nih.gov/publishing/1.1/xsd/JATS-journalpublishing1-mathml3.xsd" dtd-version="1.1" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"><front><journal-meta><journal-id journal-id-type="publisher-id">EPTSM</journal-id><journal-title-group><journal-title>Electric Power Technology and Safety Management</journal-title></journal-title-group><issn>2997-3473</issn><eissn>2997-3503</eissn><publisher><publisher-name>Art and Technology</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.61369/EPTSM.8335</article-id><article-categories><subj-group subj-group-type="heading"><subject>Article</subject></subj-group></article-categories><title>基于人体感知的电梯外呼自动取消系统：设计与实现</title><url>https://artdesignp.com/journal/EPTSM/1/4/10.61369/EPTSM.8335</url><author>李保,王靖绚</author><pub-date pub-type="publication-year"><year>2024</year></pub-date><volume>1</volume><issue>4</issue><history><date date-type="pub"><published-time>2024-07-20</published-time></date></history><abstract>电梯系统作为现代建筑中不可或缺的垂直交通工具，其运行效率和能耗问题一直备受关注。无效停层，即电梯在接到外呼请求后乘梯人离开导致的无效停层，不仅浪费了大量的能量，还显著降低了电梯的运行效率。为了解决这一问题，本文提出了一种基于人体感知传感器的外呼自动取消技术。该技术旨在当乘梯人离开呼叫楼层后，自动取消对应的外呼请求，从而提高电梯运行效率、减少不必要的停层和能耗。通过文献检索了解当前电梯系统和外呼管理的现状与挑战，明确本研究的技术路线。设计了一个基于人体感知传感器的系统架构，详细介绍传感器的选择与布置、信号采集与处理、外呼自动取消逻辑算法等。</abstract><keywords>电梯外呼,自动取消,人体感知传感器,运行效率,能耗减少</keywords></article-meta></front><body/><back><ref-list><ref id="B1" content-type="article"><label>1</label><element-citation publication-type="journal"><p>[1]Wang, H., &amp;amp; Zhang, Y. (2019). A comprehensive review of elevator control strategies.Journal of Intelligent Transportation Systems, 23(4), 290-306.[2]Li, X., &amp;amp; Liu, J. (2020). Human motion detection and recognition for smart elevator control using deep learning.IEEE Transactions on Industrial Informatics, 16(4), 2342-2351.[3]Kim, S., &amp;amp; Park, J. (2018). An intelligent elevator group control system based on passenger traffic prediction.IEEE Transactions on Smart Buildings, 5(2), 123-135.[4]Chen, L., &amp;amp; Gao, Y. (2017). Real-time passenger detection and elevator dispatching system based on infrared sensors.Sensors, 17(9), 2034.[5]Luo, H., &amp;amp; Zhang, Q. (2018). Smart elevator group control systems based on artificial intelligence techniques.IEEE Access, 6, 123-136.[6]Xu, L., &amp;amp; Li, P. (2020). A novel approach to elevator control using human presence detection and dynamic scheduling.Journal of Building Engineering, 29, 101439.[7]Wang, M., &amp;amp; Chen, J. (2019). Enhanced elevator control using human presence and behavior recognition.IEEE Transactions on Automation Science and Engineering,16(4), 1573-1585.[8]Sun, Y., &amp;amp; Liu, Q. (2019). Human activity recognition for smart building applications using wearable sensors.IEEE Sensors Journal, 19(20), 9489-9499.[9]Kim, J., &amp;amp; Lee, K. (2018). Development of a context-aware smart elevator system using user behavior prediction.Journal of Ambient Intelligence and Humanized Computing, 9(6), 1895-1905.[10]Huang, R., &amp;amp; Wang, L. (2021). A survey of intelligent control systems for elevator group control.Journal of Control Science and Engineering, 2021, 1-10.</p><pub-id pub-id-type="doi"/></element-citation></ref></ref-list></back></article>
