Department of Cybernetics and Biomedical Engineering, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 70833 Ostrava-Poruba, Czech Republic.
Sensors (Basel). 2020 Aug 26;20(17):4829. doi: 10.3390/s20174829.
The work investigates the application of artificial neural networks and logistic regression for the recognition of activities performed by room occupants. KNX (Konnex) standard-based devices were selected for smart home automation and data collection. The obtained data from these devices (Humidity, CO, temperature) were used in combination with two wearable gadgets to classify specific activities performed by the room occupant. The obtained classifications can benefit the occupant by monitoring the wellbeing of elderly residents and providing optimal air quality and temperature by utilizing heating, ventilation, and air conditioning control. The obtained results yield accurate classification.
本工作研究了人工神经网络和逻辑回归在识别房间居住者活动方面的应用。选择基于 KNX(Konnex)标准的设备进行智能家居自动化和数据收集。这些设备(湿度、CO、温度)获得的数据与两个可穿戴小工具结合使用,以对居住者执行的特定活动进行分类。获得的分类结果可以通过监测老年人居民的健康状况并利用供暖、通风和空调控制来提供最佳空气质量和温度,从而使居住者受益。获得的结果产生了准确的分类。