Real-time sound propagation and noise modeling in outdoor environments using Equivalent Source Formulation

2012 ◽  
Vol 132 (3) ◽  
pp. 1890-1890 ◽  
Author(s):  
Ravish Mehra ◽  
Dinesh Manocha ◽  
Lakulish Antani ◽  
Nikunj Raghuvanshi
Keyword(s):  
Real Time ◽  
Sound Propagation ◽  
Equivalent Source ◽  
Noise Modeling ◽  
Outdoor Environments

scholarly journals Monitoring Real-time Personal Locomotion Behaviors over Smart Indoor-outdoor Environments via Body-Worn Sensors

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Munkhjargal Gochoo ◽  
Sheikh Badar Ud Din Tahir ◽  
Ahmad Jalal ◽  
Kibum Kim
Keyword(s):  
Real Time ◽  
Outdoor Environments

scholarly journals Deep Reinforcement Learning for End-to-End Local Motion Planning of Autonomous Aerial Robots in Unknown Outdoor Environments: Real-Time Flight Experiments

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2534
Author(s):  
Oualid Doukhi ◽  
Deok-Jin Lee
Keyword(s):  
Reinforcement Learning ◽  
Real Time ◽  
Autonomous Navigation ◽  
Control Technique ◽  
Local Motion ◽  
Aerial Robots ◽  
Novel Approach ◽  
Outdoor Environments ◽  
Aerial Vehicle ◽  
High Level

Autonomous navigation and collision avoidance missions represent a significant challenge for robotics systems as they generally operate in dynamic environments that require a high level of autonomy and flexible decision-making capabilities. This challenge becomes more applicable in micro aerial vehicles (MAVs) due to their limited size and computational power. This paper presents a novel approach for enabling a micro aerial vehicle system equipped with a laser range finder to autonomously navigate among obstacles and achieve a user-specified goal location in a GPS-denied environment, without the need for mapping or path planning. The proposed system uses an actor–critic-based reinforcement learning technique to train the aerial robot in a Gazebo simulator to perform a point-goal navigation task by directly mapping the noisy MAV’s state and laser scan measurements to continuous motion control. The obtained policy can perform collision-free flight in the real world while being trained entirely on a 3D simulator. Intensive simulations and real-time experiments were conducted and compared with a nonlinear model predictive control technique to show the generalization capabilities to new unseen environments, and robustness against localization noise. The obtained results demonstrate our system’s effectiveness in flying safely and reaching the desired points by planning smooth forward linear velocity and heading rates.

scholarly journals Formaldehyde and Glyoxal Measurement Deploying a Selected Ion Flow Tube Mass Spectrometer (SIFT-MS)

2021 ◽  
Author(s):  
Antonia Zogka ◽  
Manolis N. Romanias ◽  
Frederic Thevenet
Keyword(s):  
Proton Transfer ◽  
Real Time ◽  
Mass Spectrometer ◽  
Sharp Decrease ◽  
Ionization Mass ◽  
Flow Tube ◽  
Experimental Conditions ◽  
Ion Flow ◽  
Outdoor Environments ◽  
Selected Ion Flow Tube

Abstract. Formaldehyde (FM) and glyoxal (GL) are important atmospheric species of indoor and outdoor environments. They are either directly emitted in the atmosphere or they are formed through the oxidation of organic compounds by indoor and/or outdoor atmospheric oxidants. Despite their importance, the real-time monitoring of these compounds with soft ionization mass spectrometric techniques, e.g. proton transfer mass spectrometry (PTR-MS), remains problematic and is accompanied by low sensitivity. In this study, we evaluate the performance of a multi-ion selected ion flow tube mass spectrometer (SIFT-MS) to monitor in real-time atmospherically relevant concentrations of FM and GL under controlled experimental conditions. The SIFT-MS used is operated under standard conditions (SC), as proposed by the supplier, and customized conditions (CC), to achieve higher sensitivity. In the case of FM, SIFT-MS sensitivity is marginally impacted by RH, and the detection limits achieved are below 200 ppt. Contrariwise, in the case of GL, a sharp decrease of instrument sensitivity is observed with increasing RH when the H3O+ ion is used. Nevertheless, the detection of GL using NO+ precursor ion is moderately impacted by moisture with an actual positive sensitivity response. Therefore, we recommend the use of NO+ precursor for reliable detection and quantitation of GL. This work evidences that SIFT-MS can be considered as an efficient tool to monitor the concentration of FM and GL using SIFT-MS in laboratory experiments and potentially in indoor or outdoor environments. Furthermore, SIFT-MS technology still allows great possibilities for sensitivity improvement and high potential for monitoring low proton transfer affinity compounds.

scholarly journals Combining VR Visualization and Sonification for Immersive Exploration of Urban Noise Standards

2019 ◽  
Vol 3 (2) ◽  
pp. 34 ◽  
Author(s):  
Markus Berger ◽  
Ralf Bill
Keyword(s):  
Real Time ◽  
Sound Propagation ◽  
Road Traffic ◽  
Expert Knowledge ◽  
Low Cost ◽  
Traffic Noise ◽  
Urban Traffic ◽  
Road Traffic Noise ◽  
Common Noise ◽  
Noise Assessment

Urban traffic noise situations are usually visualized as conventional 2D maps or 3D scenes. These representations are indispensable tools to inform decision makers and citizens about issues of health, safety, and quality of life but require expert knowledge in order to be properly understood and put into context. The subjectivity of how we perceive noise as well as the inaccuracies in common noise calculation standards are rarely represented. We present a virtual reality application that seeks to offer an audiovisual glimpse into the background workings of one of these standards, by employing a multisensory, immersive analytics approach that allows users to interactively explore and listen to an approximate rendering of the data in the same environment that the noise simulation occurs in. In order for this approach to be useful, it should manage complicated noise level calculations in a real time environment and run on commodity low-cost VR hardware. In a prototypical implementation, we utilized simple VR interactions common to current mobile VR headsets and combined them with techniques from data visualization and sonification to allow users to explore road traffic noise in an immersive real-time urban environment. The noise levels were calculated over CityGML LoD2 building geometries, in accordance with Common Noise Assessment Methods in Europe (CNOSSOS-EU) sound propagation methods.

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