Sensor-driven analysis of retrofit options for low energy buildings**

目前，对现有建筑物进行能源评估和提供翻新选择既昂贵又耗时。该项目旨在利用物联网和大数据提供一种更便宜的方式，为住宅建筑找到最佳的翻新方案。基于物联网技术的廉价传感器网络将通过监测一栋19世纪70年代的住宅楼的环境条件进行测试。从传感器获得的数据存储在一个数据库中，该数据库将由使用现有传感器数据训练的机器学习算法进行分析。目标是，当获得足够的数据时，可以预测受监测建筑的最佳翻新方案。为了验证这一新开发的途径，还将使用传统的基于物理的模型。这些方法为现有建筑提供了一种广为人知的分析方法，但需要大量的时间和专业知识来开发。如果这些模型没有得到适当的校准，能源消耗预测的误差可能在100%左右。提出的机器学习方法需要大量的传感器数据，但开发时间和专业知识较少。此外，它们还根据现有的历史数据提供了对建筑性能的准确预测。当这些方法完全开发出来后，来自住宅建筑的简单传感器数据可以用来提供量身定制的翻新选项，作为传统基于物理的建模方法的快速和廉价的替代方案。这将为现有建筑存量提供快速翻新解决方案。提高建筑效率将有助于加拿大实现其排放目标，并防止进一步的灾难性气候变化影响。

Energy assessment and providing retrofit options of existing buildings is currently costly and time consuming. This project aims to use the internet of things and big data to provide a cheaper way to find optimal retrofit options for residential buildings. A web of cheap sensors based on internet of things technology will be tested by monitoring environmental conditions in a 1870s era residential building. The data obtained from the sensors is stored in a database that will be analysed by machine learning algorithms trained using the available sensor data. The goal is that, when sufficient data is obtained, predictions can be made about optimal retrofit options for the monitored building. To validate this newly developed pathway traditional physics-based models will also be used. These provide a well-understood analysis method for existing buildings, but take significant time and expertise to develop. If these models are not properly calibrated, the error in energy consumption predictions may be in the order of 100%. The machine learning methods proposed require large amounts of sensor data but less time and expertise to develop. Furthermore, they provide accurate predictions of building performance based on available historical data. When these methods are fully developed, simple sensor data from residential buildings can be used to provide tailored retrofit options as a fast and inexpensive alternative to conventional physics-based modelling methods. This will provide quick retrofit solutions for the existing building stock. Improving building efficiency will help Canada meet its emissions goals and prevent further catastrophic climate change impacts.