Indoor space art design based on immersive VR and embedded system

2021 ◽  
Vol 83 ◽  
pp. 104001
Author(s):  
Fangli Li ◽  
Ying Cao
Keyword(s):  
Embedded System ◽  
Indoor Space ◽  
Art Design ◽  
Space Art

Study on the Advantages and Role of Soft Decoration Materials in Shaping the Indoor Environment Art Atmosphere

2014 ◽  
Vol 644-650 ◽  
pp. 4896-4899
Author(s):  
Wen Shi Mao
Keyword(s):  
Texture Analysis ◽  
Interior Design ◽  
Indoor Environment ◽  
Great Influence ◽  
Point Of View ◽  
Low Carbon ◽  
Indoor Space ◽  
New Material ◽  
Art Design

Modern decorative materials constantly updated and developed, and many of them are limited tube used for a time, and soon are replaced or eliminated. Soft adornment material can shape and express art atmosphere of indoor, having huge advantages and functions. In this paper, we research and analyze the soft adornment material from different point of view, and making catch-all category on the function of indoor soft adornment material that will be used in art design environmental. Soft adornment material has a great influence on the indoor space, such as people's sense of feel, smell, etc. Also from the angle of the color and design, as well as the texture analysis to analyze the utilization of soft decoration materials in interior design, and emphasized on low carbon green theme, highlighting the new idea of interior design, and also excusing the advantages of the new material.

scholarly journals Deep Neural Network Based Ambient Airflow Control through Spatial Learning

Electronics ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. 591
Author(s):  
Sunghak Kim ◽  
InChul Choi ◽  
Dohyeong Kim ◽  
Minho Lee
Keyword(s):  
Energy Efficiency ◽  
Deep Learning ◽  
Embedded System ◽  
Real Time ◽  
Learning Algorithm ◽  
Cost Effective ◽  
Target Temperature ◽  
Air Conditioner ◽  
Indoor Space ◽  
Living Area

As global energy regulations are strengthened, improving energy efficiency while maintaining performance of electronic appliances is becoming more important. Especially in air conditioning, energy efficiency can be maximized by adaptively controlling the airflow based on detected human locations; however, several limitations such as detection areas, the installation environment, and sensor quantity and real-time performance which come from the constraints in the embedded system make it a challenging problem. In this study, by using a low resolution cost effective vision sensor, the environmental information of living spaces and the real-time locations of humans are learned through a deep learning algorithm to identify the living area from the entire indoor space. Based on this information, we improve the performance and the energy efficiency of air conditioner by smartly controlling the airflow on the identified living area. In experiments, our deep learning based spatial classification algorithm shows error less than ± 5 ° . In addition, the target temperature can be reached 19.8% faster and the power consumption can be saved up to 20.5% by the time the target temperature is achieved.

Interior Decoration Materials’ Potentialities for Artistic Originality

2011 ◽  
Vol 71-78 ◽  
pp. 967-971
Author(s):  
Rui Yi
Keyword(s):  
Building Materials ◽  
Space Environment ◽  
Interior Decoration ◽  
Interior Space ◽  
Space Design ◽  
New Concepts ◽  
Art Design ◽  
Design Selection ◽  
Set Up ◽  
Space Art

Building materials for decoration are carriers for space art design to represent language, are material foundation for environment art design. Selection of materials is the basic matter for study of design. So, only by getting a full understanding of the properties of decoration materials, making good use of their advantages through reasonable selection and flexible collocation, and with respect to the available space environment, can materials perfectly perform their functions, thus fulfill the demand of interior space design. Art design and materials are interactional. The realization of art design depends upon materials and materials can get life with excellent design. By starting from the use of physical appearance of materials, we can dig out interior decoration materials’ potentialities for originality, and break through traditional way of design expression, and set up new concepts about how to use decoration materials.

Fault tolerant Automotive CAN Control Embedded System

2012 ◽  
Vol 2 (1) ◽  
pp. 57-59
Author(s):  
Balachandra Pattanaik ◽  
◽  
Dr S. Chandrasekaran Dr S. Chandrasekaran
Keyword(s):  
Embedded System ◽  
Fault Tolerant

Embedded System for Front Differential Drive of Rotational and Translational Vehicle Position Control

2017 ◽  
Vol 10 (4) ◽  
pp. 325
Author(s):  
Angie Julieth Valencia Castañeda ◽  
Mauricio Felipe Mauledoux Monroy ◽  
Oscar Fernando Avilés Sánchez ◽  
Paola Andrea Niño Suarez ◽  
Edgar Alfredo Portilla Flores
Keyword(s):  
Embedded System ◽  
Position Control ◽  
Differential Drive ◽  
Vehicle Position

Speaker Identity Recognition by Acoustic and Visual Data Fusion through Personal Privacy for Smart Care and Service Applications

2020 ◽  
Vol 64 (4) ◽  
pp. 40404-1-40404-16
Author(s):  
I.-J. Ding ◽  
C.-M. Ruan
Keyword(s):  
Face Detection ◽  
Speaker Recognition ◽  
Visual Information ◽  
Classification Tree ◽  
Gaussian Mixture ◽  
Recognition Method ◽  
Indoor Space ◽  
Identity Recognition ◽  
Visual Identity ◽  
Speaker Classification

Abstract With rapid developments in techniques related to the internet of things, smart service applications such as voice-command-based speech recognition and smart care applications such as context-aware-based emotion recognition will gain much attention and potentially be a requirement in smart home or office environments. In such intelligence applications, identity recognition of the specific member in indoor spaces will be a crucial issue. In this study, a combined audio-visual identity recognition approach was developed. In this approach, visual information obtained from face detection was incorporated into acoustic Gaussian likelihood calculations for constructing speaker classification trees to significantly enhance the Gaussian mixture model (GMM)-based speaker recognition method. This study considered the privacy of the monitored person and reduced the degree of surveillance. Moreover, the popular Kinect sensor device containing a microphone array was adopted to obtain acoustic voice data from the person. The proposed audio-visual identity recognition approach deploys only two cameras in a specific indoor space for conveniently performing face detection and quickly determining the total number of people in the specific space. Such information pertaining to the number of people in the indoor space obtained using face detection was utilized to effectively regulate the accurate GMM speaker classification tree design. Two face-detection-regulated speaker classification tree schemes are presented for the GMM speaker recognition method in this study—the binary speaker classification tree (GMM-BT) and the non-binary speaker classification tree (GMM-NBT). The proposed GMM-BT and GMM-NBT methods achieve excellent identity recognition rates of 84.28% and 83%, respectively; both values are higher than the rate of the conventional GMM approach (80.5%). Moreover, as the extremely complex calculations of face recognition in general audio-visual speaker recognition tasks are not required, the proposed approach is rapid and efficient with only a slight increment of 0.051 s in the average recognition time.

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