Human behavior identification in elevator based on sensor data

2019 ◽  
Author(s):  
Minghui Geng ◽  
Bo Ai ◽  
Hang Li
Keyword(s):  
Human Behavior ◽  
Sensor Data

scholarly journals Wearable Sensor Data Based Human Behavior Recognition: a Method of Data Feature Extraction

2021 ◽  
Vol 33 (8) ◽  
pp. 1246-1253
Author(s):  
Yibo Guo ◽  
Wenhua Meng ◽  
Yiming Fan ◽  
Lishuo Hou ◽  
Yue Yuan ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Human Behavior ◽  
Sensor Data ◽  
Wearable Sensor ◽  
Behavior Recognition ◽  
Human Behavior Recognition

scholarly journals Multimodal Human and Environmental Sensing for Longitudinal Behavioral Studies in Naturalistic Settings: Framework for Sensor Selection, Deployment, and Management (Preprint)

2018 ◽  
Author(s):  
Brandon M Booth ◽  
Karel Mundnich ◽  
Tiantian Feng ◽  
Amrutha Nadarajan ◽  
Tiago H Falk ◽  
...  
Keyword(s):  
Data Collection ◽  
Human Behavior ◽  
Well Being ◽  
Sensor Selection ◽  
Sensor Data ◽  
Unexpected Events ◽  
Minimal Impact ◽  
In The Wild ◽  
Natural Settings

BACKGROUND Recent advances in mobile technologies for sensing human biosignals are empowering researchers to collect real-world data outside of the laboratory, in natural settings where participants can perform their daily activities with minimal disruption. These new sensing opportunities usher a host of challenges and constraints for both researchers and participants. OBJECTIVE This viewpoint paper aims to provide a comprehensive guide to aid research teams in the selection and management of sensors before beginning and while conducting human behavior studies in the wild. The guide aims to help researchers achieve satisfactory participant compliance and minimize the number of unexpected procedural outcomes. METHODS This paper presents a collection of challenges, consideration criteria, and potential solutions for enabling researchers to select and manage appropriate sensors for their research studies. It explains a general data collection framework suitable for use with modern consumer sensors, enabling researchers to address many of the described challenges. In addition, it provides a description of the criteria affecting sensor selection, management, and integration that researchers should consider before beginning human behavior studies involving sensors. On the basis of a survey conducted in mid-2018, this paper further illustrates an organized snapshot of consumer-grade human sensing technologies that can be used for human behavior research in natural settings. RESULTS The research team applied the collection of methods and criteria to a case study aimed at predicting the well-being of nurses and other staff in a hospital. Average daily compliance for sensor usage measured by the presence of data exceeding half the total possible hours each day was about 65%, yielding over 355,000 hours of usable sensor data across 212 participants. A total of 6 notable unexpected events occurred during the data collection period, all of which had minimal impact on the research project. CONCLUSIONS The satisfactory compliance rates and minimal impact of unexpected events during the case study suggest that the challenges, criteria, methods, and mitigation strategies presented as a guide for researchers are helpful for sensor selection and management in longitudinal human behavior studies in the wild.

scholarly journals Multimodal Human and Environmental Sensing for Longitudinal Behavioral Studies in Naturalistic Settings: Framework for Sensor Selection, Deployment, and Management

10.2196/12832 ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. e12832 ◽  
Author(s):  
Brandon M Booth ◽  
Karel Mundnich ◽  
Tiantian Feng ◽  
Amrutha Nadarajan ◽  
Tiago H Falk ◽  
...  
Keyword(s):  
Data Collection ◽  
Human Behavior ◽  
Well Being ◽  
Sensor Selection ◽  
Sensor Data ◽  
Unexpected Events ◽  
Minimal Impact ◽  
In The Wild ◽  
Natural Settings

Background Recent advances in mobile technologies for sensing human biosignals are empowering researchers to collect real-world data outside of the laboratory, in natural settings where participants can perform their daily activities with minimal disruption. These new sensing opportunities usher a host of challenges and constraints for both researchers and participants. Objective This viewpoint paper aims to provide a comprehensive guide to aid research teams in the selection and management of sensors before beginning and while conducting human behavior studies in the wild. The guide aims to help researchers achieve satisfactory participant compliance and minimize the number of unexpected procedural outcomes. Methods This paper presents a collection of challenges, consideration criteria, and potential solutions for enabling researchers to select and manage appropriate sensors for their research studies. It explains a general data collection framework suitable for use with modern consumer sensors, enabling researchers to address many of the described challenges. In addition, it provides a description of the criteria affecting sensor selection, management, and integration that researchers should consider before beginning human behavior studies involving sensors. On the basis of a survey conducted in mid-2018, this paper further illustrates an organized snapshot of consumer-grade human sensing technologies that can be used for human behavior research in natural settings. Results The research team applied the collection of methods and criteria to a case study aimed at predicting the well-being of nurses and other staff in a hospital. Average daily compliance for sensor usage measured by the presence of data exceeding half the total possible hours each day was about 65%, yielding over 355,000 hours of usable sensor data across 212 participants. A total of 6 notable unexpected events occurred during the data collection period, all of which had minimal impact on the research project. Conclusions The satisfactory compliance rates and minimal impact of unexpected events during the case study suggest that the challenges, criteria, methods, and mitigation strategies presented as a guide for researchers are helpful for sensor selection and management in longitudinal human behavior studies in the wild.

Review of Psychology: An introduction to human behavior.

1975 ◽  
Vol 20 (1) ◽  
pp. 75-75
Author(s):  
RALPH H. TURNER
Keyword(s):  
Human Behavior

Review of The growth of human behavior.

1975 ◽  
Vol 20 (2) ◽  
pp. 171-171
Author(s):  
SONIA F. OSLER
Keyword(s):  
Human Behavior

Review of Concepts in ethology: Animal and human behavior, Vol. 2.

1975 ◽  
Vol 20 (5) ◽  
pp. 432-432
Author(s):  
RICHARD F. THOMPSON
Keyword(s):  
Human Behavior
Sign in / Sign up

Export Citation Format

Share Document