A pervasive multi-sensor data fusion for smart home healthcare monitoring

By Hamid Medjahed, Dan Istrate, Jérôme Boudy, Jean-Louis Baldinger, Bernadette Dorizzi. 2011

118 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Electrical and Electronic Engineering

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. M. Deen
2. Zheng Yan
3. Laurence Tianruo Yang
4. Wenxiu Ding
5. Xuyang Jing
6. Sumit Majumder

In Electrical and Electronic Engineering

1. Zheng Yan
2. Laurence Tianruo Yang
3. Wenxiu Ding
4. Xuyang Jing

Citations in the corpus

• A survey on data fusion in internet of things: Towards secure and privacy-preserving fusion (2019, methodology): “Real-time traffic system [37] Markov Models Accurate prediction Not suitable in long-term prediction Appliance control [38] Belief Propagat ion Can deal with large amount of data Easily lead to loopy graphs and difficult to converge when dealing with non-linear data State estimation [39] EBM D-S The”
• Smart Homes for Elderly Healthcare—Recent Advances and Research Challenges (2017, methodology): “[181] Health monitoring using data fusion techniques France (2011) - Microphones: acoustical monitoring of the elderly - Wearable device: detect posture (standing/sitting and laying), fall and activity rate - Infrared sensors: location, posture and movement detection Temperature sensors Wearable dev”