Edge Video Analytics: A Survey on Applications, Systems and Enabling Techniques

Video, as a key driver in the global explosion of digital information, can create tremendous benefits for human society. Governments and enterprises are deploying innumerable cameras for a variety of applications, e.g., law enforcement, emergency management, traffic control, and security surveillance, all facilitated by video analytics (VA). This trend is spurred by the rapid advancement of deep learning (DL), which enables more precise models for object classification, detection, and tracking. Meanwhile, with the proliferation of Internet-connected devices, massive amounts of data are generated daily, overwhelming the cloud. Edge computing, an emerging paradigm that moves workloads and services from the network core to the network edge, has been widely recognized as a promising solution. The resulting new intersection, edge video analytics (EVA), begins to attract widespread attention. Nevertheless, only a few loosely-related surveys exist on this topic. The basic concepts of EVA (e.g., definition, architectures) were not fully elucidated due to the rapid development of this domain. To fill these gaps, we provide a comprehensive survey of the recent efforts on EVA. In this paper, we first review the fundamentals of edge computing, followed by an overview of VA. The EVA system and its enabling techniques are discussed next. In addition, we introduce prevalent frameworks and datasets to aid future researchers in the development of EVA systems. Finally, we discuss existing challenges and foresee future research directions. We believe this survey will help readers comprehend the relationship between VA and edge computing, and spark new ideas on EVA.Comment: 31 pages, 13 figure

Data Fusion for Materials Location Estimation in Construction

Effective automated tracking and locating of the thousands of materials on construction sites improves material distribution and project performance and thus has a significant positive impact on construction productivity. Many locating technologies and data sources have therefore been developed, and the deployment of a cost-effective, scalable, and easy-to-implement materials location sensing system at actual construction sites has very recently become both technically and economically feasible. However, considerable opportunity still exists to improve the accuracy, precision, and robustness of such systems. The quest for fundamental methods that can take advantage of the relative strengths of each individual technology and data source motivated this research, which has led to the development of new data fusion methods for improving materials location estimation. In this study a data fusion model is used to generate an integrated solution for the automated identification, location estimation, and relocation detection of construction materials. The developed model is a modified functional data fusion model. Particular attention is paid to noisy environments where low-cost RFID tags are attached to all materials, which are sometimes moved repeatedly around the site. A portion of the work focuses partly on relocation detection because it is closely coupled with location estimation and because it can be used to detect the multi-handling of materials, which is a key indicator of inefficiency. This research has successfully addressed the challenges of fusing data from multiple sources of information in a very noisy and dynamic environment. The results indicate potential for the proposed model to improve location estimation and movement detection as well as to automate the calculation of the incidence of multi-handling

How Does Platelet-Rich Plasma Injection in Ovaries of Poor Responders Affect the Retrieved Oocytes, and Anti Mullerian Hormone: A Clinical Trial

Objective: Platelet Rich Plasma (PRP) is proposed to have important role in cell division and proliferation, angiogenesis and health. This study evaluates the effect of a single injection of autologous PRP on ovarian response markers in women with poor ovarian response (POR). Materials and methods: This non-randomized clinical trial was conducted between August 2020 and September 2021. Fifty six women with Bologna criteria for POR willingly chose to participate in one of the following groups: PRP for one cycle in the time of oocyte pickup (OPU) (intervention group, n= 34) or control group (n=22).The primary outcomes were: number and quality of oocytes in coming 2 cycles of ICSI, and Anti Mullerian Hormone (AMH) level two months after PRP injection. The secondary outcomes were the number and quality of embryos and chemical pregnancy rate after embryo transfer. Results: A total of 45 participants continued the study, of which 23 were in the intervention group and 22 in control group. There were no demographic differences between two groups. At a two cycle follow up, PRP group experienced a significant improvement in AMH level and there was no respective change in control group. In one year follow up the overall pregnancy rates were same in both groups (3% Vs. 0, p=.60), while there was no difference in cumulative number and quality of embryos. Conclusion: PRP injection can improve ovarian reserve marker without adverse effects. Further evidence is required to evaluate the impact of PRP on assisted reproduction outcomes

Scheduling optimization of linear projects considering spatio-temporal constraints

Overall schedule optimization, considering all temporal, spatial and precedence constraints is a difficult task due to the complexity which is inherent in construction projects. The difficulties associated with modeling all aspects combined become more considerable when optimizing linear type of projects with high activities’ inter-relations. The progress of these projects highly depends on the productivity achieved from their resources which is directly dependent upon the space and time available to these resources. As a result, in order to practically optimize linear schedules, not only their achieved productivities need to be managed well, but also the spatio-temporal flexibilities and constraints are to be integrated into the optimization process. This paper aims to fill the gap in the current literature by proposing a practical approach for modeling and optimization of linear schedules while taking into account all the project-dependent constraints. For this purpose, the methodology is built on the new concept of Space-Time float for explicit consideration of spatio-temporal constraints of activities. The developed method uses constraint-satisfaction optimization approach to minimize duration of the generated schedules. As such, by having Space-Time floats for different activities’ resources and using such constraints, the schedule is optimized to get the minimum achievable duration for the total project. A numerical example is analyzed to present the proposed and developed method as well as its added benefits.Non UBCUnreviewedFacultyOthe

Optimizing linear schedule : congestion-minimization approach

Space is a strictly limited resource on a construction site. For linear type of construction projects, the importance of effectively managing space is crucial as their schedules is generated with due consideration to both time and space. As a result, spatio-temporal congestions between activities of these projects could substantially hinder the performance of interfering activities and cause deviations from planned schedules. The existence of such congestions decreases work productivity, and causes accidents to occur. The current literature focuses on minimizing the workspace conflicts in order to perform efficient work and increase productivity. However, the other side of this problem, i.e. the changes in productivities which give rise to such spatio-temporal congestions is overlooked. To tackle this limitation, this paper proposes a constraint satisfaction approach to quantify and minimize potential space-time congestions in the schedules of linear projects using space-time floats. The method is able to detect not only potential conflicts between each activity with its immediate successors, but also any possible conflict between resources of any activity with all other project activities’ throughout the life cycle of the project. In order to optimize the potentially congested schedules in the planning stage, either the range of productivities available to activities are narrowed down, or the overlapped activities are rescheduled to minimize the conflict. A numerical example is analyzed to demonstrate the added benefits of the proposed method.Non UBCUnreviewedFacultyOthe

Evaluation of connected vehicle impact on mobility and mode choice

Connected vehicle is emerging as a solution to exacerbating congestion problems in urban areas. It is important to understand the impacts of connected vehicle on network and travel behavior of road users. The main objective of this paper is to evaluate the impact of connected vehicle on the mode choice and mobility of transportation networks. An iterative methodology was used in this paper where demands for various modes were modified based on the changes in travel time between each origin-destination (OD) pair caused by introduction of connected vehicle. Then a traffic assignment was performed in a micro-simulation model, which was able to accurately simulate vehicle-to-vehicle communication. It is assumed that vehicles are equipped with a dynamic route guidance technology to choose their own route using real-time traffic information obtained through communication. The travel times obtained from the micro-simulation model were compared with a base scenario with no connected vehicle. The methodology was tested for a portion of Downtown Toronto, Ontario, Canada. In order to quantify changes in mode share with changes in travel time associated with each OD pair, mode choice models were developed for auto, transit, cycling and pedestrians using data mainly from the Transportation Tomorrow Survey. The impact of connected vehicle on mode choice was evaluated for different market penetrations of connected vehicle. The results of this study show that average travel times for the whole auto mode will generally increase, with the largest increase from connected vehicles. This causes an overall move away from the auto mode for high market penetrations if a dynamic route guidance algorithm is implemented

System Optimization of Shared Mobility in Suburban Contexts

Shared mobility is a viable choice to improve the connectivity of lower-density neighbourhoods or suburbs that lack high-frequency public transportation services. In addition, its integration with new forms of powertrain and autonomous technologies can achieve more sustainable and efficient transportation. This study compares four shared-mobility technologies in suburban areas: the Internal Combustion Engine, Battery Electric, and two Autonomous Electric Vehicle scenarios, for various passenger capacities ranging from three to fifteen. The study aims to provide policymakers, transportation planners, and transit providers with insights into the potential costs and benefits as well as system configurations of shared mobility in a suburban context. A vehicle routing problem with time windows was applied using the J-Horizon software to optimize the costs of serving existing intra-community demand. The results indicate a similar fleet composition for Battery Electric and Autonomous Electric fleets. Furthermore, the resulting fleet for all four technologies is dominated by larger vehicle capacities. Due to the large share of driver cost in the total cost, the savings using a fleet of Autonomous Electric Vehicles are predicted to be 68% and 70%, respectively, compared to Internal Combustion and Battery Electric fleets

An integrated framework to prevent unsafe proximity hazards in construction by optimizing spatio-temporal constraints

Hazardous proximity of construction resources, such as construction equipment, materials, and workers-on-foot has been identified as a distinct safety issue on construction jobsites. Spatial and temporal limits are practical constraints that coexist in movement of construction resources. Space and time conflicts could substantially hinder the productivity of ongoing activities as well as causing safety issues. Therefore, the spatial and temporal constraints and the state of construction resources need to be considered to prevent space-time conflicts and unsafe proximities. The state of a moving construction resource includes its position, moving direction/heading, speed, orientation, and other safety-related information. The area around each resource is divided into alert and warning areas which are quantified for them according to their corresponding spatial or proximity constraints. By integrating the states of resources, their warning/alert areas, and proximity constraints, as well as by visualizing them in time-integrated 2D space, a more precise understanding of potential hazardous situations can be achieved and therefore prevented. This paper presents a visual support tool aiming to reduce safety hazards in project planning stage by optimizing spatio-temporal proximities of resources. For this purpose, the developed method first optimizes potential movements of the resources by minimizing intersection of their warning areas and avoiding overlap of their alert areas. Thereafter, it visualizes the optimized locations of resources in time-integrated 2D space throughout the duration of their corresponding activities. In this way, the integrated visualization framework enables managers to make more judicious decisions and take corrective actions pertinent to safety hazards prevention. A numerical example with different scenarios and proximity measures is analyzed to test and validate the proposed framework.Non UBCUnreviewedFacultyOthe