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通过建模入住率预测智能会议室使用信息。

Smart Meeting Room Usage Information and Prediction by Modelling Occupancy Profiles.

机构信息

Tecnalia Research & Innovation, Mikeletegi 2, Donostia 20009, Spain.

Faculty of Informatics, University of the Basque Country, UPV/EHU, Donostia 20018, Spain.

出版信息

Sensors (Basel). 2019 Jan 16;19(2):353. doi: 10.3390/s19020353.

Abstract

The monitoring of small houses and rooms has become possible due to the advances in IoT sensors, actuators and low power communication protocols in the last few years. As buildings are one of the biggest energy consuming entities, monitoring them has great interest for trying to avoid non-necessary energy waste. Moreover, human behaviour has been reported as being the main discrepancy source between energy usage simulations and real usage, so the ability to monitor and predict actions as opening windows, using rooms, etc. is gaining attention to develop stronger models which may lead to reduce the overall energy consumption of buildings, considering buildings thermal inertia and additional capabilities. In this paper, a case study is described in which four meeting rooms have been monitored to obtain information about the usage of the rooms and later use it to predict their future usage. The results show the possibility to deploy a simple and non-intrusive sensing system whose output could be used to develop advanced control strategies.

摘要

由于物联网传感器、执行器和低功耗通信协议在过去几年中的发展,小型房屋和房间的监测成为可能。由于建筑物是最大的能源消耗实体之一,因此对其进行监测对于避免不必要的能源浪费具有重要意义。此外,据报道,人类行为是能源使用模拟与实际使用之间存在差异的主要原因,因此,监测和预测如开窗、使用房间等行为的能力引起了人们的关注,以便开发更强有力的模型,从而减少建筑物的整体能源消耗,同时考虑建筑物的热惯性和附加功能。本文描述了一个案例研究,其中监测了四个会议室,以获取有关房间使用情况的信息,然后利用这些信息预测其未来的使用情况。结果表明,可以部署一个简单且非侵入式的传感系统,其输出可用于开发先进的控制策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0ae6/6359482/75b2cb06274e/sensors-19-00353-g001.jpg

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