scholarly journals LOGISTIC REGRESSION BASED HUMAN ACTIVITIES RECOGNITION

2020 ◽  
Vol 15 (4) ◽  
Author(s):  
Zunash Zaki
Keyword(s):  
Logistic Regression ◽  
Human Activities ◽  
Human Activities Recognition

scholarly journals A Deep Learning Approach for Human Activities Recognition From Multimodal Sensing Devices

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 179028-179038
Author(s):  
Isibor Kennedy Ihianle ◽  
Augustine O. Nwajana ◽  
Solomon Henry Ebenuwa ◽  
Richard I. Otuka ◽  
Kayode Owa ◽  
...  
Keyword(s):  
Deep Learning ◽  
Human Activities ◽  
Learning Approach ◽  
Multimodal Sensing ◽  
Human Activities Recognition

scholarly journals Daily Human Activities Recognition Using Heterogeneous Sensors from Smartphones

2017 ◽  
Vol 111 ◽  
pp. 323-328 ◽  
Author(s):  
Minh-Son Dao ◽  
Tuan-Anh Nguyen-Gia ◽  
Van-Cuong Mai
Keyword(s):  
Human Activities ◽  
Heterogeneous Sensors ◽  
Human Activities Recognition

Critical Behavior Monitoring for Children with Special Needs in Preventing Physical Injury Using Kinect

2015 ◽  
pp. 211-249
Author(s):  
Ong Chin Ann ◽  
Lau Bee Theng ◽  
Henry Lee Seldon ◽  
Fernando Anddie Putra
Keyword(s):  
Special Needs ◽  
Critical Behavior ◽  
Human Activities ◽  
Autism Spectrum ◽  
Physical Injury ◽  
Children With Special Needs ◽  
Kinect Sensor ◽  
Monitoring Model ◽  
Behavior Monitoring ◽  
Human Activities Recognition

This research studies ways to prevent physical injury for children with special needs, or specifically children with Autism Spectrum Disorder (ASD). The prevention is achievable by monitoring child behavior in the classroom from time to time. A Critical Behavior Monitoring model was developed for this purpose. The model is integrated with a Kinect sensor (by Microsoft) to process the signal acquired for human activities recognition. Currently, the model manages to identify 17 different human activities and notify parents or teachers via SMS and/or email if any unusual or critical activities are detected (i.e. falling down or asking for help). This will ensure immediate action is taken to prevent injuries or the situation from getting worse.

scholarly journals Indirect Recognition of Predefined Human Activities

Sensors ◽  
2020 ◽  
Vol 20 (17) ◽  
pp. 4829
Author(s):  
Ojan Majidzadeh Gorjani ◽  
Antonino Proto ◽  
Jan Vanus ◽  
Petr Bilik
Keyword(s):  
Neural Networks ◽  
Logistic Regression ◽  
Artificial Neural Networks ◽  
Data Collection ◽  
Human Activities ◽  
Air Conditioning ◽  
Smart Home ◽  
Home Automation ◽  
Specific Activities ◽  
Conditioning Control

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, CO2, 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.

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