Building a Large-Scale Distributed Live Video Analysis System for Movement of Pedestrians in Urban Areas

2016 ◽  
Author(s):  
Yuuichi Teranishi ◽  
Nozomu Nishinaga
Keyword(s):  
Video Analysis ◽  
Urban Areas ◽  
Large Scale ◽  
Live Video ◽  
Analysis System

A cloud-based large-scale distributed video analysis system

2016 ◽  
Author(s):  
Yongzhe Wang ◽  
Wei-Ta Chen ◽  
Huahui Wu ◽  
Anil Kokaram ◽  
Jaron Schaeffer
Keyword(s):  
Video Analysis ◽  
Large Scale ◽  
Analysis System

A unified framework for automated person re-indentification

2020 ◽  
Vol 71 (7) ◽  
pp. 868-880
Author(s):  
Nguyen Hong-Quan ◽  
Nguyen Thuy-Binh ◽  
Tran Duc-Long ◽  
Le Thi-Lan
Keyword(s):  
Deep Learning ◽  
Video Analysis ◽  
Camera Network ◽  
Unified Framework ◽  
Person Detection ◽  
Practical Applications ◽  
Detection And Tracking ◽  
Analysis System ◽  
Bounding Boxes

Along with the strong development of camera networks, a video analysis system has been become more and more popular and has been applied in various practical applications. In this paper, we focus on person re-identification (person ReID) task that is a crucial step of video analysis systems. The purpose of person ReID is to associate multiple images of a given person when moving in a non-overlapping camera network. Many efforts have been made to person ReID. However, most of studies on person ReID only deal with well-alignment bounding boxes which are detected manually and considered as the perfect inputs for person ReID. In fact, when building a fully automated person ReID system the quality of the two previous steps that are person detection and tracking may have a strong effect on the person ReID performance. The contribution of this paper are two-folds. First, a unified framework for person ReID based on deep learning models is proposed. In this framework, the coupling of a deep neural network for person detection and a deep-learning-based tracking method is used. Besides, features extracted from an improved ResNet architecture are proposed for person representation to achieve a higher ReID accuracy. Second, our self-built dataset is introduced and employed for evaluation of all three steps in the fully automated person ReID framework.

Engineering in the time of cholera: overcoming institutional and political challenges to rebuild Zimbabwe's water and sanitation infrastructure in the aftermath of the 2008 cholera epidemic

2013 ◽  
Vol 3 (2) ◽  
pp. 222-229 ◽  
Author(s):  
Clarissa Brocklehurst ◽  
Murtaza Malik ◽  
Kiwe Sebunya ◽  
Peter Salama
Keyword(s):  
Urban Areas ◽  
Large Scale ◽  
Humanitarian Aid ◽  
Urban Systems ◽  
Political Crisis ◽  
Rapid Improvement ◽  
Cholera Epidemic ◽  
Rapid Action ◽  
Water And Sanitation Infrastructure ◽  
Urban Rehabilitation

A devastating cholera epidemic swept Zimbabwe in 2008, causing over 90,000 cases, and leaving more than 4,000 dead. The epidemic raged predominantly in urban areas, and the cause could be traced to the slow deterioration of Zimbabwe's water and sewerage utilities during the economic and political crisis that had gripped the country since the late 1990s. Rapid improvement was needed if the country was to avoid another cholera outbreak. In this context, donors, development agencies and government departments joined forces to work in a unique partnership, and to implement a programme of swift improvements that went beyond emergency humanitarian aid but did not require the time or massive investment associated with full-scale urban rehabilitation. The interventions ranged from supply of water treatment chemicals and sewer rods to advocacy and policy advice. The authors analyse the factors that made the programme effective and the challenges that partners faced. The case of Zimbabwe offers valuable lessons for other countries transitioning from emergency to development, and particularly those that need to take rapid action to upgrade failing urban systems. It illustrates that there is a ‘middle path’ between short-term humanitarian aid delivered in urban areas and large-scale urban rehabilitation, which can provide timely and highly effective results.

scholarly journals Modeling Spatiotemporal Population Changes by Integrating DMSP-OLS and NPP-VIIRS Nighttime Light Data in Chongqing, China

2021 ◽  
Vol 13 (2) ◽  
pp. 284
Author(s):  
Dan Lu ◽  
Yahui Wang ◽  
Qingyuan Yang ◽  
Kangchuan Su ◽  
Haozhe Zhang ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Relative Error ◽  
Urban Areas ◽  
Large Scale ◽  
Population Distribution ◽  
Spatial Optimization ◽  
Distribution Data ◽  
Mountainous Areas ◽  
Mean Relative Error ◽  
Nighttime Light

The sustained growth of non-farm wages has led to large-scale migration of rural population to cities in China, especially in mountainous areas. It is of great significance to study the spatial and temporal pattern of population migration mentioned above for guiding population spatial optimization and the effective supply of public services in the mountainous areas. Here, we determined the spatiotemporal evolution of population in the Chongqing municipality of China from 2000–2018 by employing multi-period spatial distribution data, including nighttime light (NTL) data from the Defense Meteorological Satellite Program’s Operational Linescan System (DMSP-OLS) and the Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS). There was a power function relationship between the two datasets at the pixel scale, with a mean relative error of NTL integration of 8.19%, 4.78% less than achieved by a previous study at the provincial scale. The spatial simulations of population distribution achieved a mean relative error of 26.98%, improved the simulation accuracy for mountainous population by nearly 20% and confirmed the feasibility of this method in Chongqing. During the study period, the spatial distribution of Chongqing’s population has increased in the west and decreased in the east, while also increased in low-altitude areas and decreased in medium-high altitude areas. Population agglomeration was common in all of districts and counties and the population density of central urban areas and its surrounding areas significantly increased, while that of non-urban areas such as northeast Chongqing significantly decreased.

The Economic Imperative: Cities Need Migrants

2021 ◽  
pp. 001946622110132
Author(s):  
Astha Agarwalla ◽  
Errol D’Souza
Keyword(s):  
Rural Areas ◽  
Urban Areas ◽  
Large Scale ◽  
Market Failure ◽  
Jel Classification ◽  
Industry Concentration ◽  
Wage Curve ◽  
Economic Agents ◽  
Reverse Migration ◽  
Local Labour

The policy responses to Covid-19 have triggered large-scale reverse migration from cities to rural areas in developing countries, exposing the vulnerability of migrants living precarious lives in cities, giving rise to debates asserting to migration as undesirable and favouring policy options to discourage the process. However, the very basis of spatial concentration and formation of cities is presence of agglomeration economies, benefits accruing to economic agents operating in cities. Presence of these agglomeration benefits in local labour markets manifests themselves in the form of an upward sloping wage curve in urban areas. We estimate the upward sloping wage curve for various size classes of cities in Indian economy and establish the presence of positive returns to occupation and industry concentration at urban locations. Controlling for worker-specific characteristics influencing wages, we establish that higher the share of an industry or an occupation in local employment as compared to national economy, the desirability of firms to pay higher wages increases. For casual labourers, occupational concentration results in higher wages. However, impact of industry concentration varies across sectors. Results supporting presence of upward sloping urban wage curve, therefore, endorse policies to correct the market failure in cities and promote migration as a desirable process. JEL Classification Codes: J2, R2

scholarly journals Lighting System Modernization as a Source of Green Energy

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2771
Author(s):  
Leszek Kotulski ◽  
Artur Basiura ◽  
Igor Wojnicki ◽  
Sebastian Siuchta
Keyword(s):  
Renewable Energy ◽  
Urban Areas ◽  
Large Scale ◽  
Energy Savings ◽  
Renewable Energy Sources ◽  
Green Energy ◽  
Light Sources ◽  
Levelized Cost Of Electricity ◽  
Cost Of Electricity ◽  
Lighting Retrofit

The use of formal methods and artificial intelligence has made it possible to automatically design outdoor lighting. Quick design for large cities, in a matter of hours instead of weeks, and analysis of various optimization criteria enables to save energy and tune profit stream from lighting retrofit. Since outdoor lighting is of a large scale, having luminaires on every street in urban areas, and since it needs to be retrofitted every 10 to 15 years, choosing proper parameters and light sources leads to significant energy savings. This paper presents the concept and calculations of Levelized Cost of Electricity for outdoor lighting retrofit. It is understood as cost of energy savings, it is in the range from 23.06 to 54.64 EUR/MWh, based on real-world cases. This makes street and road lighting modernization process the best green “energy source” if compared with the 2018 Fraunhofer Institute cost of electricity renewable energy technologies ranking. This indicates that investment in lighting retrofit is more economically and ecologically viable than investment in new renewable energy sources.

scholarly journals GNSS RUMS: GNSS Realistic Urban Multiagent Simulator for Collaborative Positioning Research

2021 ◽  
Vol 13 (4) ◽  
pp. 544
Author(s):  
Guohao Zhang ◽  
Bing Xu ◽  
Hoi-Fung Ng ◽  
Li-Ta Hsu
Keyword(s):  
Urban Area ◽  
Intelligent Transportation Systems ◽  
Urban Areas ◽  
Large Scale ◽  
Transportation Systems ◽  
Accurate Localization ◽  
Gnss Receivers ◽  
Multipath Signal ◽  
Scale Test ◽  
Error Behavior

Accurate localization of road agents (GNSS receivers) is the basis of intelligent transportation systems, which is still difficult to achieve for GNSS positioning in urban areas due to the signal interferences from buildings. Various collaborative positioning techniques were recently developed to improve the positioning performance by the aid from neighboring agents. However, it is still challenging to study their performances comprehensively. The GNSS measurement error behavior is complicated in urban areas and unable to be represented by naive models. On the other hand, real experiments requiring numbers of devices are difficult to conduct, especially for a large-scale test. Therefore, a GNSS realistic urban measurement simulator is developed to provide measurements for collaborative positioning studies. The proposed simulator employs a ray-tracing technique searching for all possible interferences in the urban area. Then, it categorizes them into direct, reflected, diffracted, and multipath signal to simulate the pseudorange, C/N0, and Doppler shift measurements correspondingly. The performance of the proposed simulator is validated through real experimental comparisons with different scenarios based on commercial-grade receivers. The proposed simulator is also applied with different positioning algorithms, which verifies it is sophisticated enough for the collaborative positioning studies in the urban area.

scholarly journals Constrained Urban Airspace Design for Large-Scale Drone-Based Delivery Traffic

Aerospace ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 38
Author(s):  
Malik Doole ◽  
Joost Ellerbroek ◽  
Victor L. Knoop ◽  
Jacco M. Hoekstra
Keyword(s):  
Traffic Congestion ◽  
Urban Areas ◽  
Large Scale ◽  
Cost Savings ◽  
Future Research ◽  
Fast Time ◽  
Potential Cost ◽  
Horizontal Structure ◽  
Traffic Demand ◽  
Demand Patterns

Large-scale adoption of drone-based delivery in urban areas promise societal benefits with respect to emissions and on-ground traffic congestion, as well as potential cost savings for drone-based logistic companies. However, for this to materialise, the ability of accommodating high volumes of drone traffic in an urban airspace is one of the biggest challenges. For unconstrained airspace, it has been shown that traffic alignment and segmentation can be used to mitigate conflict probability. The current study investigates the application of these principles to a highly constrained airspace. We propose two urban airspace concepts, applying road-based analogies of two-way and one-way streets by imposing horizontal structure. Both of the airspace concepts employ heading-altitude rules to vertically segment cruising traffic according to their travel direction. These airspace configurations also feature transition altitudes to accommodate turning flights that need to decrease the flight speed in order to make safe turns at intersections. While using fast-time simulation experiments, the performance of these airspace concepts is compared and evaluated for multiple traffic demand densities in terms of safety, stability, and efficiency. The results reveal that an effective way to structure drone traffic in a constrained urban area is to have vertically segmented altitude layers with respect to travel direction as well as horizontal constraints imposed to the flow of traffic. The study also makes recommendations for areas of future research, which are aimed at supporting dynamic traffic demand patterns.

scholarly journals Complex Network Modelling of Origin–Destination Commuting Flows for the COVID-19 Epidemic Spread Analysis in Italian Lombardy Region

2021 ◽  
Vol 11 (10) ◽  
pp. 4381
Author(s):  
Angela Lombardi ◽  
Nicola Amoroso ◽  
Alfonso Monaco ◽  
Sabina Tangaro ◽  
Roberto Bellotti
Keyword(s):  
Urban Areas ◽  
Large Scale ◽  
Critical Role ◽  
Potential Contribution ◽  
Epidemic Spread ◽  
Network Modelling ◽  
Lombardy Region ◽  
Commuting Flows ◽  
Dynamic Growth ◽  
Spread Analysis

Currently the whole world is affected by the COVID-19 disease. Italy was the first country to be seriously affected in Europe, where the first COVID-19 outbreak was localized in the Lombardy region. The further spreading of the cases led to the lockdown of the most affected regions in northern Italy and then the entire country. In this work we investigated an epidemic spread scenario in the Lombardy region by using the origin–destination matrix with information about the commuting flows among 1450 urban areas within the region. We performed a large-scale simulation-based modeling of the epidemic spread over the networks related to three main motivations, i.e., work, study and occasional transfers to quantify the potential contribution of each category of travellers to the spread of the epidemic process. Our findings outline that the three networks are characterised by different weight dynamic growth rates and that the network “work” has a critical role in the diffusion phenomenon showing the greatest contribution to the epidemic spread.

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