Performance of grassed swale as stormwater quantity control in lowland area

Grassed swale is a vegetated open channel designed to attenuate stormwater through infiltration and conveying runoff into nearby water bodies, thus reduces peak flows and minimizes the causes of flood. UTHM is a flood-prone area due to located in lowland area, has high groundwater level and low infiltration rates. The aim of this study is to assess the performance of grassed swale as a stormwater quantity control in UTHM. Flow depths and velocities of swales were measured according to Six-Tenths Depth Method shortly after a rainfall event. Flow discharges of swales (Qswale) were evaluated by Mean- Section Method to determine the variations of Manning’s roughness coefficients (ncalculate) that results between 0.075 – 0.122 due to tall grass and irregularity of channels. Based on the values of Qswale between sections of swales, the percentages of flow attenuation are up to 54%. As for the flow conveyance of swales, Qswale were determined by Manning’s equation that divided into Qcalculate, evaluated using ncalculate, and Qdesign, evaluated using roughness coefficient recommended by MSMA (ndesign), to compare with flow discharges of drainage areas (Qpeak), evaluated by Rational Method with 10-year ARI. Each site of study has shown Qdesign is greater than Qpeak up to 59%. However, Qcalculate is greater than Qpeak only at a certain site of study up to 14%. The values of Qdesign also greater than Qcalculate up to 52% where it shows that the roughness coefficients as considered in MSMA are providing a better performance of swale. This study also found that the characteristics of the studied swales are comparable to the design consideration by MSMA. Based on these findings, grassed swale has the potential in collecting, attenuating, and conveying stormwater, which suitable to be applied as one of the best management practices in preventing flash flood at UTHM campus

Canine Pose Estimation: A Computing for Public Safety Solution

In this paper we discuss determining canine pose in the context of common poses observed in Urban Search and Rescue dogs through the use a sensor network made up of accelerometers. We discuss the use of the Canine Pose Estimation System in a disaster environment, and propose techniques for determining canine pose. In addition we discuss the challenges with this approach in such environments. This paper presents the experimental results obtained from the Heavy Urban Search and Rescue disaster simulation, where experiments were conducted using multiple canines, which show that angles can be derived from acceleration readings. Our experiments show that similar angles were measured for each of the poses, even when measured on multiple USAR canines of varying size. We also developed an algorithm to determine poses and display the current canine pose to the screen of a laptop. The algorithm was successful in determining some poses and had difficulty with others. These results are presented and discussed in this paper

Effects of haptic feedback in dual-task teleoperation of a mobile robot

Teleoperation system usage is challenging to human operators, as this system has a predominantly visual interface that limits the ability to acquire situation awareness, (e.g. maintain a safe teleoperation). This limitation coupled with the dual-task problem of teleoperating a mobile robot, negatively affects the operators cognitive load and motor skills. Our motivation is to offload some of the visual information to a secondary perceptual channel (haptic), by proposing an assisted teleoperation system. This system uses haptic feedback to alert the operator of obstacle proximity, without directly influencing the operator’s command inputs. The objective of this paper, is to evaluate and validate the efficacy of our system’s haptic feedback, by providing the obstacle proximity information to the operator. The user experiment was conducted to emulate the dual-task problem, by having a concurrent task for cognitive distraction. Our results showed significant differences in time to complete the navigation task and the duration of collisions, between the haptic feedback condition and the control condition.info:eu-repo/semantics/acceptedVersio

A comparison of performance on a tele-robotic search task under different conditions of navigation

This study investigated the impact of the design of robotic navigation algorithms on human performance in a searching task. Participants searched for targets in a real-world environment using a tele-robot in the context of an urban search-and-rescue task. Participants were assigned to one of three conditions for the navigation of the tele-robot around the search area: tele-operation or automated navigation using one of two different algorithms. Participants in the left-wall algorithm condition found significantly more targets that were of medium-high difficulty to identify. In addition, participants in the tele-operation condition used two distinctly different approaches to navigate around the search area. This evidence suggests that the development of path planning algorithms needs to be tailored to the operator. The knowledge that there are differences in algorithms from the human perspective provides an additional metric for the robotics community to decide between algorithms that are otherwise equivalent. Acknowledging the effect of differences in these algorithms when making design choices is important for the success of the human-robot partnership

Improving Emergency Response and Human-Robotic Performance

Preparedness for chemical, biological, and radiological/nuclear incidents at nuclear power plants (NPPs) includes the deployment of well trained emergency response teams. While teams are expected to do well, data from other domains suggests that the timeliness and accuracy associated with incident response can be improved through collaborative human-robotic interaction. Many incident response scenarios call for multiple, complex procedure-based activities performed by personnel wearing cumbersome personal protective equipment (PPE) and operating under high levels of stress and workload. While robotic assistance is postulated to reduce workload and exposure, limitations associated with communications and the robot’s ability to act independently have served to limit reliability and reduce our potential to exploit human –robotic interaction and efficacy of response. Recent work at the Idaho National Laboratory (INL) on expanding robot capability has the potential to improve human-system response during disaster management and recovery. Specifically, increasing the range of higher level robot behaviors such as autonomous navigation and mapping, evolving new abstractions for sensor and control data, and developing metaphors for operator control have the potential to improve state-of-the-art in incident response. This paper discusses these issues and reports on experiments underway intelligence residing on the robot to enhance emergency response