performance in indoor environment Research Articles (Page 1)

The increasing recognition of acoustic comfort in indoor environment highlights the need for a deeper understanding of the impact of coloured noise as background sound. Coloured noise refers to different types of sound with distinct spectrograms and varying intensities. This study investigated the effects of coloured noise (represented by white, pink and brown noise) on brainwave activity in the temporal lobes, essential for auditory recognition, during rest and reading tasks. Twenty-nine participants were assessed in a controlled environment under quiet conditions and the three noise types. During rest, brainwave activity remained stable across noise conditions, except for a significant decrease in beta frequency at the T8 electrode when exposed to white noise, suggesting its potential to enhance relaxation. In reading tasks, pink noise produced significant changes in beta frequency at the T8 electrode, indicating a relaxation or reduced in effortful cognitive processing. In contrast, brown noise exhibited minimal effects on brainwave activity in both scenarios. Gender differences were observed, with female participants showing greater sensitivity to pink noise during reading tasks. These findings highlight the potential of white noise (a consistent hissing sound) for relaxation and pink noise (resembling steady rainfall) for enhancing cognitive performance and learning in indoor environments.

Abstract We propose a passive continuous-variable quantum key distribution (CVQKD) protocol based on simultaneous quantum and classical communication (SQCC) under indoor environments and in inter-satellite links within the terahertz band. In our PSQCC-CVQKD scheme, classical modulation is performed at the transmitter, followed by passive quantum modulation operations. At the receiver, an amplifier is utilized to amplify and demultiplex the received signal, and a homodyne or heterodyne detector is subsequently selected for decoding. We derive the security bounds of the protocol and evaluate its performance in both indoor environments and inter-satellite links. Furthermore, by considering finite-size effects, we achieve tighter agreement constraints, which are more practical than those obtained in the asymptotic limit. Simulation results indicate that this scheme exhibits a high secret key rate and strong jamming resistance in practical applications, providing a more efficient pathway for the construction of future quantum networks.

Abstract To address the limitations of traditional indoor localization techniques in indoor environments, the ARtag indoor localization technique is proposed to determine the optimal recognition distance to optimize the robot’s localization performance in indoor environments. The performance of the robot at different distances is evaluated by setting up an ARtag at different distances in an indoor environment, testing and comparing the robot’s recognition accuracy and response time at these distances. The experimental results show that at a distance of 25 cm, the robot has the fastest response speed and the highest stability, with a recognition accuracy of 100% and a response time of only 0.39 ms. The ARtag indoor localization technique can significantly improve the robot’s localization performance at specific distances, which can provide a basis for optimizing the performance of indoor robotic applications.

Effect of glass salt deposition on indoor environment and building energy performance in salt-fog climate

The early detection of handguns and knives from surveillance videos is crucial to enhance people’s safety. Despite the increasing development of Deep Learning (DL) methods for general object detection, weapon detection from surveillance videos still presents open challenges. Among these, the most significant are: (i) the very small size of the weapons with respect to the camera field of view and (ii) the need of a real-time feedback, even when using low-cost edge devices for computation. Complex and recently-developed DL architectures could mitigate the former challenge but do not satisfy the latter one. To tackle such limitation, the proposed work addresses the weapon-detection task from an edge perspective. A double-step DL approach was developed and evaluated against other state-of-the-art methods on a custom indoor surveillance dataset. The approach is based on a first Convolutional Neural Network (CNN) for people detection which guides a second CNN to identify handguns and knives. To evaluate the performance in a real-world indoor environment, the approach was deployed on a NVIDIA Jetson Nano edge device which was connected to an IP camera. The system achieved near real-time performance without relying on expensive hardware. The results in terms of both COCO Average Precision (AP = 79.30) and Frames per Second (FPS = 5.10) on the low-power NVIDIA Jetson Nano pointed out the goodness of the proposed approach compared with the others, encouraging the spread of automated video surveillance systems affordable to everyone.

Human activity recognition plays a significant role in smart building applications, healthcare services, and security monitoring. In particular, WiFi‐based indoor wireless sensing system becomes increasingly popular due to its noninvasiveness. This work presents the design and implementation of DARMS, a Device‐free human Activity Recognition and Monitoring System that can be deployed with low‐cost commodity WiFi devices. DARMS is a passive wireless sensing system, and it can accurately distinguish various daily activities without the user wearing any sensor. DARMS makes two key technical contributions. First, an effective signal processing methodology is designed to extract the CSI features both in the time domain and frequency domain. Second, a dual‐channel neural network that combines temporal and frequency information is proposed to achieve fine‐grained activity recognition. In our experiments, DARMS shows outstanding performance in different indoor environments, with an average accuracy of 96.9% for fall detection and 93.3% for human activity recognition.

Modelling platform for schools (MPS): The development of an automated One-By-One framework for the generation of dynamic thermal simulation models of schools

The compliance with the indoor environmental quality (IEQ) requirements should be considered when designing retrofit actions for the refurbishment of existing buildings. The research is aimed to reduce the imbalance between the visual and thermal domains through the improvement of different design parameters in compliance with the nearly zero-energy building (nZEB) requirements. The article proposes a novel approach based on the integrated lighting, thermal, and energy dynamic simulation, to evaluate the overall building performance according to energy saving, cost effectiveness, and IEQ multi-criteria. Different energy efficiency actions, in terms of insulation materials, glazing solutions, and control strategies of the solar shading devices, have been applied to an existing office building-type. The analysis shows the possibility to design the refurbishment of an existing building into a nZEB while ensuring visual and thermal comfort. However, the not negligible costs lead to an incompliance with the cost-effectiveness requirements.

A number of vision-based algorithms designed to detect and track unmanned aerial vehicles (UAVs) from on board a second UAV have been researched, implemented, and experimentally validated over the last decade. However, the successful methods have tended to rely on characteristics such as color or shape, meaning they require the target UAV to have particular markings or geometries. This paper uses the Viola–Jones cascade classifier, a computer vision algorithm originally designed to detect human faces in video streams, and demonstrates its capability for detecting and tracking an arbitrary type of UAV with excellent performance in either indoor or outdoor environments and with a variety of backgrounds. The Viola–Jones algorithm is applied to two specific quadrotor UAV models, the Solo from 3D Robotics and the AR.Drone 2.0 from Parrot. Experimental testing demonstrates that the resulting system achieves very good detection and tracking performance in real time on each UAV type for both indoor and outdoor flight tests.

Multi-criterion optimization of integrated photovoltaic facade with inter-building effects in diverse neighborhood densities

Dynamic Performance of Indoor Environment and Energy Consumption of Air Conditioning System under Intermittent Mode

Assessing the influence of repeated exposures and mental stress on human wayfinding performance in indoor environments using virtual reality technology

次世代都市型病院の室内環境・エネルギー性能の検証・評価研究 （第18報）竣工後3年間における熱源システムの性能評価と運用改善検討

High energy consumption is one of the most serious problems globally faced today. The building sector is known to be the largest energy consumer. Energy performance in school buildings is very significant, for ascertaining the health and productivity of students and teachers. Analysis of previous studies shows that school buildings present a poor indoor air quality due to the high occupant density of school buildings, especially in classrooms, with approximately four times the occupant density of office buildings, if compared. School buildings also consume a large amount of energy due to the lack of energy saving measures applied to the buildings in Kurdistan. The purpose of this study is to improve the indoor environment and energy performance of school buildings, through analysing, evaluating and improving the indoor environment and energy efficiency of a secondary school typology in Sulaimani city in northern Iraq. Based on the measurements in the school building and the simulation model (using Indoor Climate and Energy (IDA ICE) software 4.7.1) several improvement options were investigated, including window to wall ratio, thermal insulation, and infiltration. As a result an optimal solution model in terms of thermal comfort and energy efficiency was proposed. The optimum model was also simulated and the results were compared with the reference model. The results revealed that the optimum model performed better in both indoor environment and energy consumption than the existing school model.

次世代都市型病院の室内環境・エネルギー性能の検証・評価研究 （第2報）熱源システムの性能検証・評価（設計・施工（試運転調整）段階におけるLCEM検討）

次世代都市型病院の室内環境・エネルギー性能の検証・評価研究 （第8報）地中熱利用ヒートポンプシステムのシミュレーションモデル構築

次世代都市型病院の室内環境・エネルギー性能の検証・評価研究 （第12報）熱源システムの継続的性能評価

Visible light communication (VLC), have gain much interest in past decade in indoor communication. In particular, it is use for illumination and communication simultaneously. White light emitting diodes which are used as a transmitter for VLC are potential candidates for localization. Conventionally global positioning system (GPS) has very poor performance in indoor environments. Assisted global positioning system (AGPS) has positioning accuracy in few meter range. WLEDs can be used in small cell area inside the room hence indoor positioning can be measured accurately in centimeter. In this paper a WLEDs based indoor position system is investigated, the position was accurately confined in 11cm with low cost and on the shelf components.

This study primarily aims to investigate the improvement in indoor thermal conditions by passive cooling approaches without auxiliary cooling from air-conditioning equipment. A field study is carried out in The View apartments, Penang, Malaysia, to ascertain the environmental performance of these glazed residential buildings. This study explores the potential of using natural ventilation as a passive cooling system for residential buildings in Malaysia. The impact of natural ventilation strategy is investigated in selecting different rooms, days and orientations. The impact of daytime and nighttime natural ventilation as a passive cooling strategy is also investigated and compared with that of unventilated situations. Results show significant improvements in indoor environmental performance by 80% and 50% at daytime and night-time, respectively, in cases where natural ventilation is applied and considered in the building. Keywords: Hot–Humid Climate, Natural Ventilation, Residential Building, Sustainable Design, Thermal Performance

The investigation of the received signal strength indicator (RSSI) and throughput performance in indoor environments for a 2.4 GHz transparent antenna is presented in this paper. The monopole transparent antenna with bi-directional radiation pattern is used in the measurement as the receiver. The RSSI results are taken from a laptop that equipped with AirMagnet wireless PC Card. The antenna throughput is measured with different RSSI levels of the highest, medium and lowest values. Moreover, the measured performance of direct electrical and solar power sources in an indoor environment is compared. The aim is to test the reliability of WiFi systems with solar panel. The measurement results show that throughput performance is proportional to the RSSI values. The RSSI values are between -60 dBm to -90 dBm with average throughput values between 8 and 7 Mbps. Ultimately, it is discovered that the same performance was obtained by using either one of the two power sources. Therefore solar source can be applied to power up the WiFi transparent antenna in real environment that eventually moving towards the green energy and sustainable technology.