期刊
SENSORS
卷 19, 期 16, 页码 -出版社
MDPI
DOI: 10.3390/s19163512
关键词
sensor data fusion; fuzzy logic; activity recognition; smart objects
资金
- REMIND project Marie Sklodowska-Curie EU Framework for Research and Innovation Horizon 2020 [734355]
- Spanish government [RTI2018-098979-A-I00, PI-0387-2018, CAS17/00292]
The IoT describes a development field where new approaches and trends are in constant change. In this scenario, new devices and sensors are offering higher precision in everyday life in an increasingly less invasive way. In this work, we propose the use of spatial-temporal features by means of fuzzy logic as a general descriptor for heterogeneous sensors. This fuzzy sensor representation is highly efficient and enables devices with low computing power to develop learning and evaluation tasks in activity recognition using light and efficient classifiers. To show the methodology's potential in real applications, we deploy an intelligent environment where new UWB location devices, inertial objects, wearable devices, and binary sensors are connected with each other and describe daily human activities. We then apply the proposed fuzzy logic-based methodology to obtain spatial-temporal features to fuse the data from the heterogeneous sensor devices. A case study developed in the UJAmISmart Lab of the University of Jaen (Jaen, Spain) shows the encouraging performance of the methodology when recognizing the activity of an inhabitant using efficient classifiers.
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