Real-time Outdoor Research Articles

HazARdSnap: Gazed-Based Augmentation Delivery for Safe Information Access While Cycling.

During cycling activities, cyclists often monitor a variety of information such as heart rate, distance, and navigation using a bike-mounted phone or cyclocomputer. In many cases, cyclists also ride on sidewalks or paths that contain pedestrians and other obstructions such as potholes, so monitoring information on a bike-mounted interface can slow the cyclist down or cause accidents and injury. In this article, we present HazARdSnap, an augmented reality-based information delivery approach that improves the ease of access to cycling information and at the same time preserves the user's awareness of hazards. To do so, we implemented real-time outdoor hazard detection using a combination of computer vision and motion and position data from a head mounted display (HMD). We then developed an algorithm that snaps information to detected hazards when they are also viewed so that users can simultaneously view both rendered virtual cycling information and the real-world cues such as depth, position, time to hazard, and speed that are needed to assess and avoid hazards. Results from a study with 24 participants that made use of real-world cycling and virtual hazards showed that both HazARdSnap and forward-fixed augmented reality (AR) user interfaces (UIs) can effectively help cyclists access virtual information without having to look down, which resulted in fewer collisions (51% and 43% reduction compared to baseline, respectively) with virtual hazards.

Virtual home staging and relighting from a single panorama under natural illumination

Virtual staging technique can digitally showcase a variety of real-world scenes. However, relighting indoor scenes from a single image is challenging due to unknown scene geometry, material properties, and outdoor spatially-varying lighting. In this study, we use the High Dynamic Range (HDR) technique to capture an indoor panorama and its paired outdoor hemispherical photograph, and we develop a novel inverse rendering approach for scene relighting and editing. Our method consists of four key components: (1) panoramic furniture detection and removal, (2) automatic floor layout design, (3) global rendering with scene geometry, new furniture objects, and the real-time outdoor photograph, and (4) virtual staging with new camera position, outdoor illumination, scene texture, and electrical light. The results demonstrate that a single indoor panorama can be used to generate high-quality virtual scenes under new environmental conditions. Additionally, we contribute a new calibrated HDR (Cali-HDR) dataset that consists of 137 paired indoor and outdoor photographs. The animation for virtual rendered scenes is available here.

Study of water-side free cooling technology for power lithium battery plant

Power lithium battery production process needs to consume a lot of energy. In this paper, an energy consumption analysis of a representative company was conducted, the energy consumption of the facilities that provide support for the process is higher than the energy consumption of the process equipment itself, which greatly affects the cost of battery manufacturing. Air-conditioning system as the most important energy-consuming system of the facilities, accounting for 25% to 45% of the total electricity consumption. The energy consumption of the cooling source system dominates, even in winter its energy consumption can reach 14% of the total energy consumption. On this basis, this paper analyzes the chilled-water-use characteristics of the air-conditioning terminal in winter through theoretical analysis, the chilled water temperature is therefore optimized according to the real-time outdoor humidity. The chilled water temperature is linearly increased after the humidity ratio fall below 7.5g/kg(a), reaching a maximum value of 12.1°C at 6g/kg(a). In addition, the cooling tower free cooling technology based on the optimized chilled water temperature is innovatively proposed to fully explore the energy-saving potential of the technology to achieve the energy saving of the cooling source system. TRNSYS simulation results show that after optimizing the chilled water temperature, the time period for cooling tower individual cooling under winter operating condition is extended by 60%, and cooling source system energy saving rate can reach 49.0% and the cost saving rate 48.0%, both of which are higher than 15% compared to the un-optimized chilled water temperature.

Conjugated Polymer-Based Hydrogel Film for a Fast and Sensitive Detection of Fe(Ⅲ) in Vegetables.

Fluorescent film sensors are ideal for the real-time outdoor detection of heavy metal ions of Fe3+, but they are limited because of their low sensitivity and long response time due to their special structure. In this work, we constructed a fluorescent hydrogel for the specific detection of Fe3+, utilizing poly(9-fluorenecarboxylic acid) (PFCA) as the sensing moiety and sodium alginate (SA) as the cross-linking substrate, which exhibited a rapid and selective recognition of Fe3+ among a panel of 16 anions and 21 cations. It can sense Fe3+ at 0.1 nM immediately owing to the porous network structure of the PFCA-SA film that provided enhanced ion transport channels and active sites, and the "molecular line effect" of polymer PFCA. Moreover, we successfully applied this platform to detect Fe3+ in four different vegetable samples. This work provides an innovative and effective strategy for fabricating green and sustainable fluorescent sensors.

Real-Time Outdoor Localization Using Radio Maps: A Deep Learning Approach

Real-Time Outdoor Localization Using Radio Maps: A Deep Learning Approach

Robust Consensus-based Formation Control of a Group of UAV

Consensus-based formation control (CFC) is one of the most phenomenal formation control methods designed to achieve consensus between any vehicles that using and sharing their position and/or linear velocity with each other in a swarm mission. In this paper, a robust CFC (R-CFC) has been designed and proposed to realize pre-defined formation shapes with a team of unmanned aerial vehicles (UAVs). First, the double integrator dynamics of an UAV is presented. Second, the graph theory is explained briefly to understand any adjacency between UAVs. Then, the proposed R-CFC algorithm has been derived and the stability analysis has been proven via algebraic Riccati stability theory based on Lyapunov stability theorem. After that, the effectiveness of the proposed controller has been tested in real time outdoor tests. The experimental results show that the UAVs have been able to create the desired formation shapes and are less affected by external disturbances such as wind thanks to the proposed control algorithm.

Demonstrating the most effective interventions to improve classroom air quality. What novel in situ tests of real-world conditions show is still missing in our guidance

Abstract Over 20 years ago a report commissioned by the European Commission identified air quality in schools as a public health priority. Despite this concern, little action was taken in the following two decades. Over the last two years as classrooms were increasingly recognised as hotspots for the transmission of SARS-CoV-2, renewed interest and resources have been made available in response to this issue. Questions remain, however, over how best to achieve safer classroom air. Our analysis assessed a range of in situ interventions to remove particulate matter (PM2.5) and carbon dioxide from inside a populated classroom. Our approach used saline spray and volunteers’ exhalations as our source of PM2.5 and carbon dioxide to explore the ability of high efficiency particulate air (HEPA) filters, natural ventilation and a recirculating A/C unit to remove these air pollutants which collectively provided a novel set of data. For a total window opening of 1.86 m2 for a 181.7 m3 classroom with a HEPA filter with a 703m3/hr clean air delivery rate, our results confirmed that outdoor air was needed to purge the room to reduce carbon dioxide levels that otherwise rose to >1000 ppm in 12 min. Cross and natural ventilation reduced levels of PM2.5 and carbon dioxide very effectively—in under 5 and 10 min respectively during low levels of outside PM2.5. We conclude that natural ventilation supplemented with the use of HEPA filters is the most effective way to reliably improve indoor air quality year-round, balancing the need to have easy to enact approaches to reduce the buildup of PM2.5, airborne viruses and carbon dioxide. These results highlight an important knowledge gap. Without having localised real-time outdoor air pollution sensing, evidence-based decisions cannot be made about how often, and for how long, windows can safely remain open to purge classrooms in times of poor quality outdoor air.

Experimental investigation of an asymmetric compound parabolic concentrator–based direct absorption solar collector using plasmonic nanofluids

Plasmonic nanofluid-based direct absorption solar collector (DASC) systems have shown a better perspective over surface-based solar thermalcollectors. These nanofluids demonstrated high thermal performance in photo-thermal conversion efficiency even at minute concentration compared to other testednanofluids. However, very few studies have been reported so farwith real-time outdoor experiments to show the opportunities and challenges in the practical applications of concentrating DASC systems. For the work presented here, an asymmetric compound parabolic concentrator (ACPC)-based DASC system has been designed, fabricated, and tested using mono-spherical gold and silver nanoparticle-based plasmonicnanofluids over several clear sky days at Jalandhar city (31.32° N, 75.57° E), India. The optical and morphological properties of synthesized nanoparticles were studied using UV-Vis spectrophotometry and High-resolution transmission electron microscopy (HR-TEM). Photo-thermal conversion tests were conducted using different working fluids and compared with a flat DASC system under similar operating conditions. The experimental results revealed that ACPC-based DASC system reached a maximum thermal efficiency of around 70% using plasmonic nanofluids which was approximately 28% higher than a flat DASC system with water as the working fluid. The stability analysis showed that plasmonic nanofluids are capable of retaining their optical properties even after several hours of sun exposure. The present study highlights the use of plasmonic nanostructures for achieving high photo-thermal conversion efficiency in concentrating DASC systems.

Robust and Real-Time Outdoor Localization Only With a Single 2-D LiDAR

Robust and real-time localization is an essential issue for autonomous driving. As a high-precision sensor, light detection and ranging (LiDAR) is widely used in autonomous driving. However, because LiDAR is vulnerable to environmental factors, such as fog, rain, and dynamic objects, robust localization based on LiDAR remains challenging. Moreover, the 3-D LiDAR is prohibitively expensive for consumer-grade applications. A robust and real-time outdoor localization method based solely on a single 2-D LiDAR is proposed to overcome these deficiencies. First, a grid matching algorithm based on data association is proposed to remove mismatches caused by great noises. Then, the Dempster–Shafer evidence theory-based strategy is proposed to fuse several frames of consecutive 2-D LiDAR data in a local window into a local map to eliminate dynamic objects. Finally, the generated local map is matched with the preconstructed global map to fulfill localization. Extensive experiments on the Karlsruhe Institute of Technology and Toyota Technological Institute at Chicago (KITTI) dataset validate the proposed method. It achieves high accuracy and real-time performance comparable and even superior to the 3-D LiDAR-based localization method.

Design and Performance Evaluation of Photovoltaic Systems with Automatic Dust Wiper in a Natural Dusty Environment

The accumulation of dust on solar panels affects the transmittance of solar panel glazing which leads to the degradation of its efficiency due to low levels of irradiance reaching the cells. In this work, the response of polycrystalline silicon solar panels toward dust in a natural dusty environment was experimentally investigated at a location in Calabar close to the Calabar river. The experimental measurements were carried out in real-time outdoor conditions where human activities take place. An automatic dust wiping/cleaning mechanism to ensure the panel surface was kept clean was deployed in the study. An intelligent maximum power point (MPP) trackers for tracking the maximum power points of the panels were also utilized for this work. Results obtained revealed that the accumulation of dust on polycrystalline solar panel adversely affects its power output and efficiency. From the results, it was also revealed that the average panel temperature of the photovoltaic system with the automatic dust wiping mechanism was 5.300C lower than the other system without the mechanism. This lower panel temperature led to an increase of 16%, 32.5%, 43.40% and 43.37% in average voltage, average current, average power and average efficiency respectively over the dusty panel. It was demonstrated that solar panel efficiency plummets as panel temperature rises due to heat dissipation caused by the accumulation of dust.

Performance Analysis of Solar Water Pumping System with Real-Time Outdoor Conditions and Validation with Matlab/Simulink

Performance Analysis of Solar Water Pumping System with Real-Time Outdoor Conditions and Validation with Matlab/Simulink

Research on Ultra-Wideband (UWB) Accurate Positioning under Signal Interference Based on Deep Learning

UWB (Ultra-Wideband) technology is also called "Ultra-Wideband", also known as pulse radio technology. UWB-based positioning technology has real-time indoor and outdoor accurate tracking capabilities, with high positioning accuracy, which can achieve centimeter-level or even millimeter-level positioning. Based on the provided anchor point ranging information, this paper analyzes normal and abnormal data and establishes an accurate positioning model. For task 1, preprocess the data, export the file, delete invalid data, and fill in missing values. For task 2, it is required to establish models for normal and abnormal data respectively. For task 3, it is consistent with the model obtained in task 2. The only difference is that the coordinates of the four anchor points used for the test data have changed. When the target coordinates are calculated, the anchor point coordinates can be replaced to obtain the model required by task 3. For task 4, use the processed data in task one to establish a mathematical model, and train the model through the integrated learning method to determine whether the collected signal is interference. For task 5, first use the integrated learning model in task four to eliminate the interference data in the data, import the eliminated data into the positioning model of task two for positioning, and add Kalman based on interference recognition to the static estimation algorithm.

Outdoor Environmental Radiation Monitoring and Estimation of Radiation Risk on Public in New Market Thana, Dhaka, Bangladesh

The Real-time outdoor environmental gamma radiation (RTOEGR) dose rates were monitored at New Market Thana in Dhaka city to generate a baseline database that would help to know any deviation after operation of Rooppur NPP. The RTOEGR monitoring was carried out using a digital portable radiation monitoring device (DPRMD). The RTOEGR dose rates at the area of New Market Thana were ranged from 0.103 ± 0.004 µSv/h to 0.168 ± 0.007 µSv/h with an average of 0.135 ± 0.004 µSv/h. The public's annual effective doses were calculated based on RTOEGR dose rates, and those were varied from 0.181 ± 0.007 mSv to 0.295 ± 0.007 mSv with an average of 0.238 ± 0.007 mSv. Excess Lifetime Cancer Risk (ELCR) on public health was estimated based on the annual effective dose. The Public's ELCR were from 0.720×10-3 to 1.174×10-3 with an average of 0.892×10-3, which is higher than the worldwide standard value of 0.29×10-3. The mean RTOEGR dose rate of the New Market Thana in Dhaka city is comparable to that of Sabzevar city (Iran), Kathmandu city of Tribhuvan University (Nepal), Baghdad city (Iraq), Kirikkale city (Turkey).

Real-Time Outdoor Illumination Estimation for Camera Tracking in Indoor Environments

Dynamic illumination is a challenging problem for visual robot localization and tracking. In indoor environments, the main source of light during the day is outdoor illumination. We propose a method that estimates the appearance of an indoor scene in real-time based on a reflectance map and the current outdoor lighting. Our outdoor illumination model consists of three components, namely sun, sky and ground, where the sun position is obtained from the scene geolocation and the current time of day. The scene illumination is pre-computed using radiosity transport for each of those components. To deal with dynamic illumination resulting from changing weather conditions, we estimate the outdoor light brightness in each input frame and scale the pre-computed illumination accordingly. We evaluate our approach on real-world data covering diverse outdoor illumination settings and show that our adaptable model is beneficial for direct camera tracking.

Visual Robot Relocalization Based on Multi-Task CNN and Image-Similarity Strategy.

The traditional CNN for 6D robot relocalization which outputs pose estimations does not interpret whether the model is making sensible predictions or just guessing at random. We found that convnet representations trained on classification problems generalize well to other tasks. Thus, we propose a multi-task CNN for robot relocalization, which can simultaneously perform pose regression and scene recognition. Scene recognition determines whether the input image belongs to the current scene in which the robot is located, not only reducing the error of relocalization but also making us understand with what confidence we can trust the prediction. Meanwhile, we found that when there is a large visual difference between testing images and training images, the pose precision becomes low. Based on this, we present the dual-level image-similarity strategy (DLISS), which consists of two levels: initial level and iteration-level. The initial level performs feature vector clustering in the training set and feature vector acquisition in testing images. The iteration level, namely, the PSO-based image-block selection algorithm, can select the testing images which are the most similar to training images based on the initial level, enabling us to gain higher pose accuracy in testing set. Our method considers both the accuracy and the robustness of relocalization, and it can operate indoors and outdoors in real time, taking at most 27 ms per frame to compute. Finally, we used the Microsoft 7Scenes dataset and the Cambridge Landmarks dataset to evaluate our method. It can obtain approximately 0.33 m and 7.51 accuracy on 7Scenes dataset, and get approximately 1.44 m and 4.83 accuracy on the Cambridge Landmarks dataset. Compared with PoseNet, our CNN reduced the average positional error by 25% and the average angular error by 27.79% on 7Scenes dataset, and reduced the average positional error by 40% and the average angular error by 28.55% on the Cambridge Landmarks dataset. We show that our multi-task CNN can localize from high-level features and is robust to images which are not in the current scene. Furthermore, we show that our multi-task CNN gets higher accuracy of relocalization by using testing images obtained by DLISS.

Full Spectrum Phosphors for White LEDs and Virtual Windows for Light and Health Applications

Light and health is a topic of significant importance and requires fundamental studies of human interactions with light. This talk will present a review of some of the on-going studies on light and health by holistically exposing the humans to the outdoor conditions, while they are confined in indoor spaces. The designs of a new lighting-display fusion system along with examples of emerging commercial products will be discussed. Full spectrum lighting is a critical component of such systems. Results of phosphor blends based on well known thiogallates and sulfide phosphors for designing full spectrum lighting that could replicate sunlight quality will be presented. The synchronous modulation of phosphor based full spectrum light sources with electronic display playing real time outdoor videos creates a new tool for systematically studying the cognitive psycho-physiological health of human beings under different environmental conditions.

From thermal sensation to thermal affect: A multi-dimensional semantic space to assess outdoor thermal comfort

The psychometric tool known as the thermal sensation scale has been extensively used in outdoor thermal comfort research. However, this one-dimensional descriptive scale was originally developed for indoor assessments and therefore has certain shortcomings in outdoor settings. The scale contains no affective information such as pleasure and it overlooks the dynamic wind and solar radiation fluxes outdoors. Accordingly, this study develops a six-dimensional semantic framework for outdoor thermal comfort assessments comprising four descriptive - ‘thermal sensation’, ‘humidity’, ‘wind’ and ‘solar radiation,’ plus two affective - ‘thermal pleasure’ and ‘thermal intensity’ dimensions. In Phase 1 an online questionnaire recruited 135 native English-speakers to place 76 climatic adjectives into this six-dimensional semantic space. Phase 2 launched a field study with another 22 subjects locating real-time outdoor thermal experiences in the same semantic space. They were then asked to select from a subset of the 76 climatic adjectives those that best described their right here-right-now thermal experience. Validation was then performed by comparing coordinates of the 31 most frequently chosen adjectives in Phase 2 with those assigned to them in Phase 1. Good correlations (R2 > 0.65) of adjectives' coordinates between the two research phases indicate consistency regarding which adjectives best describe specific scenarios, regardless of seasons, locations, or current exposures. The results emphasise that the thermal sensation scale inadequately characterises outdoor thermal comfort experiences. This study initiates the transition of biometeorological comfort research from crude unidimensional descriptive thermal sensation scale, towards a more nuanced, multi-dimensional descriptions of subjective thermal state.

Multi-sensor fusion localization algorithm for outdoor mobile robot

In this paper, the multi-sensor fusion positioning technology of outdoor mobile robot is studied, and a real-time outdoor positioning algorithm combining GPS and lidar odometry is proposed. Lidar odometry based on 3D lidar for point cloud feature matching is realized. At the same time, a covariance matrix reflecting the local positioning information of the lidar odometry is constructed in real time according to the matching distance and the absolute median difference, and the accuracy factor, the circular probability error, etc. are used as the standard GPS. The positioning effect is evaluated to measure the respective positioning effects of the lidar odometry and GPS. On this basis, the GPS is used as the global factor in the pose structure, and the lidar odometry is used as the local factor to construct the pose observation constraint, and the global nonlinear trajectory optimization is carried out to realize the outdoor real-time positioning of the mobile robot. Experimental results and data analysis verify the effectiveness and practicability of the proposed method.

Full Spectrum Phosphors for White LEDs and Virtual Windows for Light and Health Applications

Light and health is a topic of significant importance and requires fundamental studies of human interactions with light. This paper presents a review of some of the on-going studies on light and health by holistically exposing the humans to the outdoor conditions, while they are confined in indoor spaces. The designs of a new lighting-display fusion system along with examples of emerging commercial products have been presented. Full spectrum lighting is a critical component of such systems. A new simple approach for creating phosphor blends based on well known thiogallates and sulfide phosphors for designing full spectrum lighting that could replicate sunlight quality has been described. The synchronous modulation of phosphor based full spectrum light sources with electronic display playing real time outdoor videos creates a new tool for systematically studying the cognitive psycho-physiological health of human beings under different environmental conditions.

Shaping light to influence occupants’ experience of space: a kinetic shading system with composite materials

Adaptive kinetic façades are systems capable of modifying their shape to optimize their behavior regarding real time outdoor and indoor conditions. They are typically evaluated based on quantifiable physical parameters such as illuminance levels, with little attention – for lack of evaluation criteria – given to subjective appreciation of the façade and the resulting daylight patterns. The present study investigates the daylighting performance of a kinetic shading system based on simulations combined with physical mock-up testing, to assess its viability as an alternative shading solution that complements conventional functions by enhancing the occupants’ experience of the space. Based on performance assessment and perceptual studies, the shortcomings of traditional blinds are identified and a promising prototype design, controlling the blinds’ opening by means of torsional deformations, is proposed.