Residents' Needs for Indoor Environments

2013 ◽  
Vol 361-363 ◽  
pp. 464-467
Author(s):  
Bing Wang ◽  
Pei Chao Chen ◽  
Xiao Liu
Keyword(s):  
Theoretical Basis ◽  
Indoor Environment ◽  
Space Environment ◽  
Indoor Environments ◽  
Environment Design ◽  
Indoor Space

Based on the indoor space environment as the theme, this paper illuminates the indoor environment design goals: meeting the psychological and physiological needs, and reveal all aspects involved in these two requirements. Providing a reliable theoretical basis for the design of indoor environment.

scholarly journals Indoor path visualization method based on the spatial characteristics of indoor environment

2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Jiafeng Shi ◽  
Jie Shen ◽  
Zdeněk Stachoň ◽  
Yawei Chen
Keyword(s):  
Indoor Environment ◽  
Design Method ◽  
Three Dimensional ◽  
Indoor Environments ◽  
Route Guidance ◽  
Visualization Method ◽  
Continuous Space ◽  
Indoor Location ◽  
Indoor Space ◽  
Map Design

<p><strong>Abstract.</strong> With the increasing number of large buildings and more frequent indoor activities, indoor location-based service has expanded. Due to the complicated internal passages of large public buildings and the three-dimensional interlacing, it is difficult for users to quickly reach the destination, the demand of indoor paths visualization increases. Isikdag (2013), Zhang Shaoping (2017), Huang Kejia (2018) provided navigation services for users based on path planning algorithm. In terms of indoor path visualization, Nossum (2011) proposed a “Tubes” map design method, which superimposed the channel information of different floors on the same plane by simplifying the indoor corridor and the room. Lorenz et al (2013) focused on map perspective (2D/3D) and landmarks, developed and investigated cartographic methods for effective route guidance in indoor environments. Holscher et al (2007) emphasized using the landmark objects at the important decision points of the route in indoor map design. The existing studies mainly focused on two-dimensional plane to visualize the indoor path, lacking the analysis of three-dimensional connectivity in indoor space, which makes the intuitiveness and interactivity of path visualization greatly compromised. Therefore, it is difficult to satisfy the wayfinding requirements of the indoor multi-layer continuous space. In order to solve this problem, this paper aims to study the characteristics of the indoor environment and propose a path visualization method. The following questions are addressed in this study: 1) What are the key characteristics of the indoor environment compared to the outdoor space? 2) How to visualize the indoor paths to satisfy the users’ wayfinding needs?</p>

scholarly journals Feel the way with a vibrotactile compass: Does a navigational aid aid navigation?

2017 ◽  
Author(s):  
Steven M. Weisberg ◽  
Daniel Badgio ◽  
Anjan Chatterjee
Keyword(s):  
Military Personnel ◽  
Indoor Environment ◽  
Reference Frames ◽  
University Hospital ◽  
Indoor Environments ◽  
Indoor Space ◽  
Navigational Cues ◽  
Navigational Aid ◽  
Improved Performance ◽  
Indoor Spaces

AbstractKnowing where north is provides a navigator with invaluable information for learning and recalling a space, particularly in places with limited navigational cues, like complex indoor environments. Although north is effectively used by orienteers, pilots, and military personnel, very little is known about whether non-expert populations can or will use north to create an accurate representation of an indoor space. In the current study, we taught people two non-overlapping routes through a complex indoor environment, with which they were not familiar – a university hospital with few windows and several turns. Along one route, they wore a vibrotactile compass on their arm, which vibrated continuously indicating the direction of north. Along the other route, they were only told where north was at the start of the route. At the beginning, the end, and back at the beginning of each route, participants pointed to well-known landmarks in the surrounding city and campus (external landmarks), and newly-learned landmarks in the hospital (internal landmarks). We found improved performance with the compass only for external landmarks, driven by people’s use of the availability of north to orient these judgments. No such improved orientation occurred for the internal landmarks. These findings reveal the utility of vibrotactile compasses for learning new indoor spaces. We speculate that such cues help users map new spaces onto familiar spaces or to familiar reference frames.

On the Interaction between Indoor Seat Design and Human Body

2013 ◽  
Vol 303-306 ◽  
pp. 2843-2846
Author(s):  
Yan Meng ◽  
Li Zhang ◽  
Yu Ma
Keyword(s):  
Information Technology ◽  
Human Body ◽  
Culture System ◽  
Indoor Environment ◽  
Space Environment ◽  
Environment Design ◽  
System Research ◽  
Technology And Culture ◽  
The Social ◽  
High Efficient

Abstract. In the highly developed stage of economy, information, technology and culture, system research has been conducted on human, furniture, space as well as environment by ergonomics to have the indoor environment adapt to people’s demands on life activities and to raise both the social materials and spiritual life to a new level, which has brought new value to the design world. Focusing on the main line “human-space-environment”, the analysis for a series of psychological and physiological activities produced when people sit on the seat indoors have been conducted on the basis of ergonomics and environment-related behavior theory. So that people can create a safe, healthy, cozy and high-efficient working and studying environment actively in the environment design.

scholarly journals Extracting Indoor Space Information in Complex Building Environments

2018 ◽  
Vol 7 (8) ◽  
pp. 321 ◽  
Author(s):  
Yueyong Pang ◽  
Chi Zhang ◽  
Liangchen Zhou ◽  
Bingxian Lin ◽  
Guonian Lv
Keyword(s):  
Indoor Environment ◽  
Information Modeling ◽  
Indoor Environments ◽  
Indoor Space ◽  
Floor Space ◽  
Grid Model ◽  
Building Information ◽  
Complex Building ◽  
Space Boundary ◽  
Indoor Spaces

Indoor space information extraction is an important aspect of reconstruction for building information modeling and a necessary process for geographic information system from outdoor to indoor. Entity model extracting methods provide advantages in terms of accuracy for building indoor spaces, as compared with network and grid model methods, and the extraction results can be converted into a network or grid model. However, existing entity model extracting methods based on a search loop do not consider the complex indoor environment of a building, such as isolated columns and walls or cross-floor spaces. In this study, such complex indoor environments are analyzed in detail, and a new approach for extracting buildings’ indoor space information is proposed. This approach is based on indoor space boundary calculation, the Boolean difference for single-floor space extraction, relationship reconstruction, and cross-floor space extraction. The experimental results showed that the proposed method can accurately extract indoor space information from the complex indoor environment of a building with geometric, semantic, and relationship information. This study is theoretically important for better understanding the complexity of indoor space extraction and practically important for improving the modeling accuracy of buildings.

scholarly journals Performance Evaluation of Particulate Matter and Indoor Microclimate Monitors in University Classrooms under COVID-19 Restrictions

2021 ◽  
Vol 18 (14) ◽  
pp. 7363
Author(s):  
Laurentiu Predescu ◽  
Daniel Dunea
Keyword(s):  
Performance Evaluation ◽  
Particulate Matter ◽  
Air Quality ◽  
Indoor Environment ◽  
Indoor Environments ◽  
University Campus ◽  
Particle Counter ◽  
Thermal Environments ◽  
University Classrooms ◽  
Academic Personnel

Optical monitors have proven their versatility into the studies of air quality in the workplace and indoor environments. The current study aimed to perform a screening of the indoor environment regarding the presence of various fractions of particulate matter (PM) and the specific thermal microclimate in a classroom occupied with students in March 2019 (before COVID-19 pandemic) and in March 2021 (during pandemic) at Valahia University Campus, Targoviste, Romania. The objectives were to assess the potential exposure of students and academic personnel to PM and to observe the performances of various sensors and monitors (particle counter, PM monitors, and indoor microclimate sensors). PM1 ranged between 29 and 41 μg m−3 and PM10 ranged between 30 and 42 μg m−3. It was observed that the particles belonged mostly to fine and submicrometric fractions in acceptable thermal environments according to the PPD and PMV indices. The particle counter recorded preponderantly 0.3, 0.5, and 1.0 micron categories. The average acute dose rate was estimated as 6.58 × 10−4 mg/kg-day (CV = 14.3%) for the 20–40 years range. Wearing masks may influence the indoor microclimate and PM levels but additional experiments should be performed at a finer scale.

scholarly journals A Non-Intrusive Approach for Indoor Occupancy Detection in Smart Environments

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3953 ◽  
Author(s):  
Bruno Abade ◽  
David Perez Abreu ◽  
Marilia Curado
Keyword(s):  
Machine Learning ◽  
Environmental Data ◽  
Machine Learning Techniques ◽  
Smart Environments ◽  
Prototype System ◽  
Indoor Environments ◽  
Process Data ◽  
Indoor Space ◽  
Occupancy Detection ◽  
Real Scenario

Smart Environments try to adapt their conditions focusing on the detection, localisation, and identification of people to improve their comfort. It is common to use different sensors, actuators, and analytic techniques in this kind of environments to process data from the surroundings and actuate accordingly. In this research, a solution to improve the user’s experience in Smart Environments based on information obtained from indoor areas, following a non-intrusive approach, is proposed. We used Machine Learning techniques to determine occupants and estimate the number of persons in a specific indoor space. The solution proposed was tested in a real scenario using a prototype system, integrated by nodes and sensors, specifically designed and developed to gather the environmental data of interest. The results obtained demonstrate that with the developed system it is possible to obtain, process, and store environmental information. Additionally, the analysis performed over the gathered data using Machine Learning and pattern recognition mechanisms shows that it is possible to determine the occupancy of indoor environments.

Sign in / Sign up

Export Citation Format

Share Document