General Lighting Conditions Research Articles

Research on Six-Degree-of-Freedom Refueling Robotic Arm Positioning and Docking Based on RGB-D Visual Guidance

The main contribution of this paper is the proposal of a six-degree-of-freedom (6-DoF) refueling robotic arm positioning and docking technology guided by RGB-D camera visual guidance, as well as conducting in-depth research and experimental validation on the technology. We have integrated the YOLOv8 algorithm with the Perspective-n-Point (PnP) algorithm to achieve precise detection and pose estimation of the target refueling interface. The focus is on resolving the recognition and positioning challenges of a specialized refueling interface by the 6-DoF robotic arm during the automated refueling process. To capture the unique characteristics of the refueling interface, we developed a dedicated dataset for the specialized refueling connectors, ensuring the YOLO algorithm’s accurate identification of the target interfaces. Subsequently, the detected interface information is converted into precise 6-DoF pose data using the PnP algorithm. These data are used to determine the desired end-effector pose of the robotic arm. The robotic arm’s movements are controlled through a trajectory planning algorithm to complete the refueling gun docking process. An experimental setup was established in the laboratory to validate the accuracy of the visual recognition and the applicability of the robotic arm’s docking posture. The experimental results demonstrate that under general lighting conditions, the recognition accuracy of this docking interface method meets the docking requirements. Compared to traditional vision-guided methods based on OpenCV, this visual guidance algorithm exhibits better adaptability and effectively provides pose information for the robotic arm.

Real-time visualization of smoke for fire safety engineering applications

Visibility in smoke is a key aspect in terms of safe egress in various fire related situations. Due to the hazardous nature of fire induced smoke, it is hard to study human behaviour under such conditions, but recent development within the field of virtual reality (VR) has enabled exposure to many different hazardous conditions while remaining relatively safe. However, to obtain valid results from such studies a higher degree of visual realism is often required, therefore when studying effects of visibility, the rendering of smoke needs to be physically based and of high visual fidelity while still being computationally cheap in order to render the virtual environment at high framerates. This paper presents an approach for rendering smoke with a single in-scattering term which allows for smoke and light interaction over multiple wavelengths. The results highlight the importance of smoke characteristics as well as the influence the general lighting conditions can have on perceived visibility. The presented work intends to be of benefit for VR or similar applications where visibility is of key interest.

Status of Lighting Technology Application in Indonesia

In 2019, Indonesia’s electricity consumption exceeded 278 TWH, or about 1.08 MWh/capita. This value shows a considerable increase in electricity consumption which has doubled in just a decade. Previous studies have shown that the proportion of electricity consumption used for lighting needs is correlated to the country’s GDP. This is generally around 20 to 50% of electricity production but can go up to 86% in the case of Tanzania. Indonesia is the 4th country in the world in terms of population and its lighting market as well as its lighting-related energy consumption has a strong impact on several levels: societal, environmental but also economic and energy. Having a knowledge of the lamps used by the Indonesian people is therefore particularly interesting and important, in particular in the context which presents a great societal diversity but also in a context of energy saving. Indonesia is an archipelagic country made up of 5 large islands and over 17,000 small islands with widely varying levels of population density. This island geography leads Indonesia to face challenges in the distribution and production of electrical energy, which affects the use of lamps in various types of regions. The overview of this study was done by collecting data from various sources, especially BPS (Biro Pusat Statistik/Statistic Center Bureau of Indonesia), CLASP (an NGO for clean energy), the Ministry of Energy and Mineral Resources of Indonesia (ESDM), PLN (Indonesian Electrical Company), etc. The data obtained from these sources provides several descriptions of general lighting conditions in Indonesia viewed from several angles, such as growth of lamp market, use of lamp types, percentage of use of lamps with energy saving (ESL), etc. Considering that Indonesia has various regional characteristics, in this study, the survey of a total of 394 respondents was conducted on the use of lamps by creating regional categories based on electrical conditions, power consumption, and electricity per capita, among others. The categories of areas observed fall into 5 types based on their population and geography: large cities, small towns, rural/village areas, islands and remote areas. The results of compiling data from these various sources show that the types of lamps used by Indonesians follow the lighting trend in the world. The use of LED lamps has a utilization percentage of around 52%, much higher than other types of lamps such as CFL, fluorescent or incandescent. Based on the survey conducted, it is known that the widely used LED power is between 1 and 10 watts with a usage time of 8 to 12 h per day. In the next few years, it is estimated that the use of LEDs in Indonesia will increase as the government has prepared various regulations and policies related to energy saving, one of which relates to lighting.

WORKING CONDITIONS, HEALTH STATUS AND OCCUPATIONAL RISK OF EMPLOYEES OF THERMAL POWER PLANTS

Assessment of working conditions of employees in key occupations in Thermal Power plants (TP) was carried out. Working environment factors (noise, general vibration, harmful chemicals, microclimatic and lighting conditions) were measured and evaluated at workplaces. The analysis of occupational and general morbidity and assessment of occupational risks was performed in the study. At workplaces there were high noises levels exceeding the maximum permissible level in some cases by 12-16 dBA; the levels of occupational co-factors - general vibration, microclimate and lighting conditions, and chemical substance concentrations - match hygiene standards. The work process severity matches the third (harmful) class of the first and second degree, and the intensity of workload - the second (permissible) class. In terms of the hazard rate, severity and intensity of work process working conditions of employees in key occupations of the PT were established to fit the harmful class, and the noise is the leading affecting factor. Exceeding the permissible levels of occupational factors promotes the development of occupational diseases. An analysis of the dynamics of occupational morbidity in the production, transmission, and distribution of energy has shown a trend to have been towards its growth in the last decade. It has been established an extension of disease of the musculoskeletal, endocrine, and circulatory systems, the eye and adnexa, digestive organs, and respiratory organs among the employees in key occupations of TP. Calculations of relative risk indicate an almost complete production conditionality of the diseases of the musculoskeletal, nervous and endocrine systems in workers engaged in TP. Prevention of occupational and work-related morbidity should include, among other things, the assessment of occupational risks with the creation and implementation of a monitoring system for the dynamics of working conditions and the health status of workers.

Salient object detection and classification for stereoscopic images

Stereoscopic images have become more and more prevalent following the rapid advances in 3D capturing and display techniques. However, there has been little research on visual content analysis for stereoscopic images. In this paper, we address the challenging problem of object detection and classification for stereoscopic images. An iterative method that can mutually boost salient object detection and object classification is proposed for stereoscopic images. This method includes two steps. In the first step, a 3D saliency detection method, which includes the contrastive and occlusion cues contained in each stereoscopic image pair along with the discriminative features provided by the SVM classifier, is proposed to localize object of interest in the stereoscopic images. In the second step, the bag of word features of foreground and background is pooled by using the localization information, and then is applied to train the SVM classifier. Each of the two steps benefits from the gradual improvement result in the other, no matter in the training or the testing process. To evaluate the performance of our approach, a 6-object class dataset of stereoscopic images real objects viewed under general lighting conditions, poses and viewpoints is set up. Our experimental results on the dataset, for object localization and object classification, demonstrate the effectiveness of the method.

Light conditions in the nursing home

Purpose In the Netherlands, the prevalence of visual impairments is the highest among the subgroup of nursing home residents. Over 40 percent are estimated to have visual impairments1. Older adults experience visual problems due to biological aging or eye disease2. These problems can affect several visual functions as well as daily functions in general3,4. Providing appropriate lighting of sufficient intensity and color temperature (CT), and making use of capabilities of the visual environment in the nursing home4 is one of the tasks for professional carers.Light conditions were measured in order to find out to what extent older adults live with the proper lighting conditions. With these data, we wanted to enhance the awareness among care professionals of how light conditions affect the daily lives of the nursing home residents. Moreover, care professionals and technical staff could make the right improvements to the nursing home environment based on the outcomes. Method We assessed light conditions (Konica Minolta chromameter CL-200) in seven nursing homes in the Netherlands. Light conditions were measured in places where residents spend most of their time during the day. In total, 59 living rooms and corridors were assessed in this study. Horizontal and vertical illuminances as well as CT were measured and compared to the values given in a guideline by the Dutch Society for Illumination5. The study was performed between October 2009 and the end of March 2010 at daytime between 10:00 and 15:00 hours. By measuring in autumn, winter and early spring, the contribution of daylight to the indoor illuminance levels was kept at a minimum. Results & Discussion In general lighting conditions encountered in the nursing homes were poor. Four-fifths of the measured illuminances in the common rooms were below the 1,000 lx threshold. Illuminances in the corridors fell below the 200 lx threshold in at least three quarters of the measurements. This means that nursing home residents may have difficulty carrying out tasks and could fall during transfers. The CT of light to which nursing home residents were exposed, fell below the reference value for daylight of 5,000 K with median scores of 3,400 to 4,500 K. High CT of light, in combination with higher illuminances, may positively affect the biological clock, resulting in better sleep quantity and quality.Nursing home staff should be aware of these data in order to arrange better light conditions. Technical staff should be aware that lighting guidelines are not specifically developed for older adults. Special attention should be paid to the fact that older adults need more light than younger persons to perform Activities of Daily Living (ADL).

A Statistical Method for SVBRDF Approximation from Video Sequences in General Lighting Conditions

AbstractWe present a statistical method for the estimation of the Spatially Varying Bidirectional Reflectance Distribution Function (SVBRDF) of an object with complex geometry, starting from video sequences acquired with fixed but general lighting conditions. The aim of this work is to define a method that simplifies the acquisition phase of the object surface appearance and allows to reconstruct an approximated SVBRDF. The final output is suitable to be used with a 3D model of the object to obtain accurate and photo‐realistic renderings. The method is composed by three steps: the approximation of the environment map of the acquisition scene, using the same object as a probe; the estimation of the diffuse color of the object; the estimation of the specular components of the main materials of the object, by using a Phong model. All the steps are based on statistical analysis of the color samples projected by the video sequences on the surface of the object. Although the method presents some limitations, the trade‐off between the easiness of acquisition and the obtained results makes it useful for practical applications.

TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context

This paper details a new approach for learning a discriminative model of object classes, incorporating texture, layout, and context information efficiently. The learned model is used for automatic visual understanding and semantic segmentation of photographs. Our discriminative model exploits texture-layout filters, novel features based on textons, which jointly model patterns of texture and their spatial layout. Unary classification and feature selection is achieved using shared boosting to give an efficient classifier which can be applied to a large number of classes. Accurate image segmentation is achieved by incorporating the unary classifier in a conditional random field, which (i) captures the spatial interactions between class labels of neighboring pixels, and (ii) improves the segmentation of specific object instances. Efficient training of the model on large datasets is achieved by exploiting both random feature selection and piecewise training methods. High classification and segmentation accuracy is demonstrated on four varied databases: (i) the MSRC 21-class database containing photographs of real objects viewed under general lighting conditions, poses and viewpoints, (ii) the 7-class Corel subset and (iii) the 7-class Sowerby database used in He et al. (Proceeding of IEEE Conference on Computer Vision and Pattern Recognition, vol. 2, pp. 695---702, June 2004), and (iv) a set of video sequences of television shows. The proposed algorithm gives competitive and visually pleasing results for objects that are highly textured (grass, trees, etc.), highly structured (cars, faces, bicycles, airplanes, etc.), and even articulated (body, cow, etc.).

Modeling the effect of the atmosphere on light

The interaction of light with particles suspended in the air is the cause of some beautiful effects. Among these effects are the colors of the sunset, the blue of the sky, and the appearance of a scene in fog. A lighting model that takes into account the effects of scattering by suspended particles is presented. A method of computing the colors of the sun and sky, for any sun position above the horizon, is derived from the lighting model. The model is also suitable for rendering fog under general lighting conditions. As an example of the use of the model for rendering fog, the special case of fog lit by the sun, without shadows, is considered.