scholarly journals A Conceptual AI-System Model for Home Automation and Smart Monitoring Based On Vision

2019 ◽  
Vol 8 (10) ◽  
pp. 3099-3102
Keyword(s):  
Associate Degree ◽  
Serial Communication ◽  
Human Motion ◽  
System Model ◽  
Home Automation ◽  
The Status ◽  
Human Motion Recognition ◽  
Acquisition Device ◽  
Future Direction ◽  
The Ideal

Home automation is a rapidly increasing developmental area in the terribly present days attributable to the higher rate of affordability and ease. It provides the potential of controlling our homes and having the sides retort to events that are managed mechanically, it has become an extremely popular attribute due to its safety functions and reasons of value. We projected a model to introduce the whole automation of our house with a security system for our household. The ideal concept of this project is to ascertain an answer that can be achieved within a minimal budget. We got so used off shelf elements aspect that the amount reduced drastically. This study conjointly discusses the chosen literature, fashionable datasets, and concludes with the challenges within the domain at the side of a future direction. The main conceptual focus of this paper is to pose a system based design that demonstrates the interfacing between MATLAB with camera and Arduino board for observation and management of household instruments. In the projected system, Arduino board is interfaced with MATLAB victimization serial communication to regulate home appliances. Image acquisition device is interfaced to MATLAB which will ceaselessly show the status of the different type of household equipment on the Graphical computer program [GUI] designed in MATLAB. When the correct commands are dispatched from the MATLAB user interface, the corresponding household equipment is turned ON/OFF which are interfaced to Arduino through relay board. The system conjointly sends alert messages or signals if any abnormality is detected in the associate degree. The human motion recognition domain has been active for quite 20 years and has provided an oversized quantity of literature.

scholarly journals A Study of Vision based Human Motion Recognition and Analysis

2016 ◽  
Vol 7 (2) ◽  
pp. 75-92 ◽  
Author(s):  
Geetanjali Vinayak Kale ◽  
Varsha Hemant Patil
Keyword(s):  
Gesture Recognition ◽  
Surveillance System ◽  
General Framework ◽  
Human Motion ◽  
Motion Recognition ◽  
Motion Representation ◽  
Advantages And Disadvantages ◽  
Major Development ◽  
Human Motion Recognition ◽  
Future Direction

Vision based human motion recognition has fascinated many researchers due to its critical challenges and a variety of applications. The applications range from simple gesture recognition to complicated behaviour understanding in surveillance system. This leads to major development in the techniques related to human motion representation and recognition. This paper discusses applications, general framework of human motion recognition, and the details of each of its components. The paper emphasizes on human motion representation and the recognition methods along with their advantages and disadvantages. This study also discusses the selected literature, popular datasets, and concludes with the challenges in the domain along with a future direction. The human motion recognition domain has been active for more than two decades, and has provided a large amount of literature. A bird's eye view for new researchers in the domain is presented in the paper.

scholarly journals Human Motion Recognition of Knitted Flexible Sensor in Walking Cycle

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 35 ◽  
Author(s):  
Yutian Li ◽  
Xuhong Miao ◽  
Li Niu ◽  
Gaoming Jiang ◽  
Pibo Ma
Keyword(s):  
Human Body ◽  
Large Strain ◽  
Human Motion ◽  
Electrical Signal ◽  
Electrical Performance ◽  
Resistance Characteristic ◽  
Body Movements ◽  
The Status ◽  
Human Motion Recognition ◽  
Knitted Structure

Knitted fabric sensors have been widely used as strain sensors in the sports health field and its large strain performance and structure are suitable for human body movements. When a knitted structure is worn, different human body movements are reflected through the large strain deformation of fabric structure and consequently change the electrical signal. Here, the mechanical and electrical properties of highly elastic knitted sweatpants were tested under large strain. This sensor has good sensitivity and stability during movement. Compared with traditional motion monitoring, this technique divides the walking cycle into two stages, namely, stance and swing phases, which can be further subdivided into six stages. The corresponding resistance characteristic values can accurately distinguish the gait cycle. Analysis on hysteresis and repeatability revealed that the sensor exhibits a constant electrical performance. Four kinds of motion postures were predicted and judged by comparing the resistance characteristic range value, peak value calculation function and time axis. The measured sensor outputs were transferred to a computer via 4.0 Bluetooth. Matlab language was used to detect the status through a rule-based algorithm and the sensor outputs.

scholarly journals A Study of Vision Based Human Motion Recognition and Analysis

2018 ◽  
pp. 2269-2289
Author(s):  
Geetanjali Vinayak Kale ◽  
Varsha Hemant Patil
Keyword(s):  
Gesture Recognition ◽  
Surveillance System ◽  
General Framework ◽  
Human Motion ◽  
Motion Recognition ◽  
Motion Representation ◽  
Advantages And Disadvantages ◽  
Major Development ◽  
Human Motion Recognition ◽  
Future Direction

Vision based human motion recognition has fascinated many researchers due to its critical challenges and a variety of applications. The applications range from simple gesture recognition to complicated behaviour understanding in surveillance system. This leads to major development in the techniques related to human motion representation and recognition. This paper discusses applications, general framework of human motion recognition, and the details of each of its components. The paper emphasizes on human motion representation and the recognition methods along with their advantages and disadvantages. This study also discusses the selected literature, popular datasets, and concludes with the challenges in the domain along with a future direction. The human motion recognition domain has been active for more than two decades, and has provided a large amount of literature. A bird's eye view for new researchers in the domain is presented in the paper.

Conclusion: Rethinking Punishment

2018 ◽  
Author(s):  
Didier Fassin
Keyword(s):  
Social Inequality ◽  
Political Violence ◽  
Social Order ◽  
Social Groups ◽  
The Social ◽  
Ideal Language ◽  
The Status ◽  
The Ideal

If punishment is not what we say it is, if it is not justified by the reasons we invoke, if it facilitates repeat offenses instead of preventing them, if it punishes in excess of the seriousness of the act, if it sanctions according to the status of the offender rather than to the gravity of the offense, if it targets social groups defined beforehand as punishable, and if it contributes to producing and reproducing disparities, then does it not itself precisely undermine the social order? And must we not start to rethink punishment, not only in the ideal language of philosophy and law but also in the uncomfortable reality of social inequality and political violence?

scholarly journals Application of human motion recognition technology in extreme learning machine

2021 ◽  
Vol 18 (1) ◽  
pp. 172988142098321
Author(s):  
Anzhu Miao ◽  
Feiping Liu
Keyword(s):  
Extreme Learning Machine ◽  
Research Work ◽  
Human Motion ◽  
Feature Descriptor ◽  
Background Variable ◽  
Motion Recognition ◽  
Network Training ◽  
Other Information ◽  
Human Motion Recognition ◽  
Learning Machine

Human motion recognition is a branch of computer vision research and is widely used in fields like interactive entertainment. Most research work focuses on human motion recognition methods based on traditional video streams. Traditional RGB video contains rich colors, edges, and other information, but due to complex background, variable illumination, occlusion, viewing angle changes, and other factors, the accuracy of motion recognition algorithms is not high. For the problems, this article puts forward human motion recognition based on extreme learning machine (ELM). ELM uses the randomly calculated implicit network layer parameters for network training, which greatly reduces the time spent on network training and reduces computational complexity. In this article, the interframe difference method is used to detect the motion region, and then, the HOG3D feature descriptor is used for feature extraction. Finally, ELM is used for classification and recognition. The results imply that the method proposed here has achieved good results in human motion recognition.

scholarly journals A review of computer vision-based approaches for physical rehabilitation and assessment

2021 ◽  
Author(s):  
Bappaditya Debnath ◽  
Mary O’Brien ◽  
Motonori Yamaguchi ◽  
Ardhendu Behera
Keyword(s):  
Computer Vision ◽  
Human Motion ◽  
Physical Rehabilitation ◽  
Human Motion Analysis ◽  
Functional Rehabilitation ◽  
Physical Impairments ◽  
The Past ◽  
Future Direction ◽  
Assessment Research ◽  
Vision Application

AbstractThe computer vision community has extensively researched the area of human motion analysis, which primarily focuses on pose estimation, activity recognition, pose or gesture recognition and so on. However for many applications, like monitoring of functional rehabilitation of patients with musculo skeletal or physical impairments, the requirement is to comparatively evaluate human motion. In this survey, we capture important literature on vision-based monitoring and physical rehabilitation that focuses on comparative evaluation of human motion during the past two decades and discuss the state of current research in this area. Unlike other reviews in this area, which are written from a clinical objective, this article presents research in this area from a computer vision application perspective. We propose our own taxonomy of computer vision-based rehabilitation and assessment research which are further divided into sub-categories to capture novelties of each research. The review discusses the challenges of this domain due to the wide ranging human motion abnormalities and difficulty in automatically assessing those abnormalities. Finally, suggestions on the future direction of research are offered.

A Projection-based Human Motion Recognition Algorithm based on Depth Sensors

2021 ◽  
pp. 1-1
Author(s):  
Mu-Chun Su ◽  
Pang-Ti Tai ◽  
Jieh-Haur Chen ◽  
Yi-Zeng Hsieh ◽  
Shu-Fang Lee ◽  
...  
Keyword(s):  
Recognition Algorithm ◽  
Human Motion ◽  
Motion Recognition ◽  
Depth Sensors ◽  
Human Motion Recognition

Development and Application of API Risk Based Inspection Planning for Petroleum and Petrochemical Facilities

2000 ◽  
Author(s):  
John T. Reynolds
Keyword(s):  
Chemical Industry ◽  
Development Phase ◽  
Inspection Planning ◽  
User Experiences ◽  
The Future ◽  
The Status ◽  
Future Direction

Abstract This paper describes the status of the API project to develop and maintain Risk-Based Inspection (RBI) methodology for application within the petroleum and chemical industry. The original project has now moved from a “development” phase into an “implement and improve” phase. This paper describes the essential features of API RBI, the most recent enhancements, software features, the future direction for the project, and some user experiences. This paper also describes the acceptance of RBI by various API codes and standards, by jurisdictional authorities, and it also describes the development of an API recommended practice on RBI (API RP 580) as well as the development of an ASME standard on RBI.

Sign in / Sign up

Export Citation Format

Share Document