A design model for building occupancy detection using sensor fusion

机译：基于传感器融合的建筑物占用检测设计模型

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Building occupancy sensing is useful for control of building services such as lighting and ventilation, enabling energy savings, whilst maintaining a comfortable environment. However, a precise and reliable measurement of occupancy still remains difficult. Existing technologies are plagued with a number of issues ranging from unreliable data, maintaining privacy, sensor drift, change of use, and short-term financial pressures, including low quality parts and insufficient commissioning. A major performance barrier is currently the fitness to purpose, or otherwise of sensing technologies used. Sensor fusion techniques offer a way to make up for this, aiming to more reliably determine occupancy using a range of different indoor climatic variables. Over the last decade, artificial intelligence (AI) techniques have found some application for building controls, and can also be applied to occupancy estimation. We describe a novel methodology for building occupancy detection using a sensor fusion model based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm. The system monitors indoor climatic variables, indoor events and energy data obtained from a non-domestic building to infer occupancy patterns.

机译：建筑物占用感测对于控制建筑物的服务（例如照明和通风）非常有用，可以节省能源，同时保持舒适的环境。但是，精确和可靠的占用率测量仍然很困难。现有技术受到许多问题的困扰，这些问题包括不可靠的数据，维护隐私，传感器漂移，用途变更以及短期财务压力，包括零件质量低和调试不足。当前的主要性能障碍是是否适合目的，或者是否适合使用所使用的传感技术。传感器融合技术提供了一种弥补此问题的方法，旨在使用一系列不同的室内气候变量来更可靠地确定占用率。在过去的十年中，人工智能（AI）技术已经在建筑物控制中得到了一些应用，并且也可以用于占用估计。我们描述了一种新的方法，用于使用基于自适应神经模糊推理系统（ANFIS）算法的传感器融合模型进行建筑物占用检测。该系统监视从非住宅建筑获得的室内气候变量，室内事件和能源数据，以推断居住模式。

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来源
《Digital Ecosystems Technologies (DEST), 2012 6th IEEE International Conference on》|2012年|p.1- 6|共6页
会议地点 Campione dItalia(IT)
作者
Ekwevugbe Tobore; Brown Neil; Fan Denis;
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作者单位

Institute of Energy and Sustainable Development, De Montfort University, Leicester, United Kingdom;

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原文格式 PDF
正文语种 eng
中图分类计算技术、计算机技术;人工智能理论;
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1. On the application of wireless sensors and actuators network in existing buildings for occupancy detection and occupancy-driven lighting control [J] . Labeodan Timilehin, De Bakker Christel, Rosemann Alexander, Energy and Buildings . 2016,第sepa期

机译：关于无线传感器和执行器网络在现有建筑物中用于占用检测和占用驱动照明控制的应用
2. IoT-Based Sensor Data Fusion for Occupancy Sensing Using Dempster–Shafer Evidence Theory for Smart Buildings [J] . Nashreen Nesa, Indrajit Banerjee Internet of Things Journal, IEEE . 2017,第5期

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3. A fusion framework for occupancy estimation in office buildings based on environmental sensor data [J] . Chen Zhenghua, Masood Mustafa K., Soh Yeng Chai Energy and Buildings . 2016,第DECa期

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4. A design model for building occupancy detection using sensor fusion [C] . Ekwevugbe Tobore, Brown Neil, Fan Denis IEEE International Conference on Digital Ecosystems and Technologies . 2012

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7. On the application of wireless sensors and actuators network in existing buildings for occupancy detection and occupancy-driven lighting control [O] . Labeodan, TM Timilehin, de Bakker, C Christel, Rosemann, ALP Alexander, 2016

机译：关于无线传感器和执行器网络在现有建筑物中用于占用检测和占用驱动照明控制的应用

A design model for building occupancy detection using sensor fusion

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