Generating Situational Awareness of Pedestrian and Vehicular Movement in Urban Areas Using IoT Data Streams

2020 ◽  
Vol 7 (5) ◽  
pp. 4395-4402
Author(s):  
Nishan Mills ◽  
Daswin de Silva ◽  
Damminda Alahakoon
Keyword(s):  
Data Streams ◽  
Urban Areas ◽  
Situational Awareness

scholarly journals Situation monitoring of urban areas using social media data streams

2016 ◽  
Vol 57 ◽  
pp. 129-141 ◽  
Author(s):  
Andreas Weiler ◽  
Michael Grossniklaus ◽  
Marc H. Scholl
Keyword(s):  
Social Media ◽  
Data Streams ◽  
Urban Areas ◽  
Social Media Data ◽  
Media Data

scholarly journals Trialing Innovative Technologies in Crisis Management—“Airborne and Terrestrial Situational Awareness” as Support Tool in Flood Response

2020 ◽  
Vol 10 (11) ◽  
pp. 3743 ◽  
Author(s):  
Elisa Schröter ◽  
Ralph Kiefl ◽  
Eric Neidhardt ◽  
Gaby Gurczik ◽  
Carsten Dalaff ◽  
...  
Keyword(s):  
Crisis Management ◽  
Urban Areas ◽  
Large Scale ◽  
New Technologies ◽  
Situational Awareness ◽  
Route Planning ◽  
Added Value ◽  
Aerial Image ◽  
Specific Response ◽  
Test Bed

Flooding represents the most-occurring and deadliest threats worldwide among natural disasters. Consequently, new technologies are constantly developed to improve response capacities in crisis management. The remaining challenge for practitioner organizations is not only to identify the best solution to their individual demands, but also to test and evaluate its benefit in a realistic environment before the disaster strikes. To bridge the gap between theoretic potential and actual integration into practice, the EU-funded project DRIVER+ has designed a methodical and technical environment to assess innovation in a realistic but non-operational setup through trials. The German Aerospace Center (DLR) interdisciplinary merged mature technical developments into the “Airborne and terrestrial situational awareness” system and applied it in a DRIVER+ Trial to promote a sustainable and demand-oriented R&D. Experienced practitioners assessed the added value of its modules “KeepOperational” and “ZKI” in the context of large-scale flooding in urban areas. The solution aimed at providing contextual route planning in police operations and extending situational awareness based on information derived through aerial image processing. The user feedback and systematically collected data through the DRIVER + Test-bed approved that DLR’s system could improve transport planning and situational awareness across organizations. However, the results show a special need to consider, for example, cross-domain data-fusion techniques to provide essential 3D geo-information to effectively support specific response tasks during flooding.

scholarly journals An Overview of the Performance and Operational Applications of the MRMS and FLASH Systems in Recent Significant Urban Flash Flood Events

2021 ◽  
pp. 1-29
Author(s):  
ALAN GERARD ◽  
STEVEN M. MARTINAITIS ◽  
JONATHAN J. GOURLEY ◽  
KENNETH W. HOWARD ◽  
JIAN ZHANG
Keyword(s):  
Urban Areas ◽  
Situational Awareness ◽  
Prediction Models ◽  
Flash Flood ◽  
Spatial Scales ◽  
Weather Prediction ◽  
Small Time ◽  
Severe Weather ◽  
Flood Events ◽  
The Public

AbstractThe Multi-Radar Multi-Sensor (MRMS) system is an operational, state-of-the-science hydrometeorological data analysis and nowcasting framework that combines data from multiple radar networks, satellites, surface observational systems, and numerical weather prediction models to produce a suite of real-time, decision-support products every two minutes over the contiguous United States and southern Canada. The Flooded Locations and Simulated Hydrograph (FLASH) component of the MRMS system was designed for the monitoring and prediction of flash floods across small time and spatial scales required for urban areas given their rapid hydrologic response to precipitation. Developed at the National Severe Storms Laboratory in collaboration with the Cooperative Institute for Mesoscale Meteorological Studies (CIMMS) and other research entities, the objective for MRMS and FLASH is to be the world’s most advanced system for severe weather and storm-scale hydrometeorology, leveraging the latest science and observation systems to produce the most accurate and reliable hydrometeorological and severe weather analyses. NWS forecasters, the public and the private sector utilize a variety of products from the MRMS and FLASH systems for hydrometeorological situational awareness and to provide warnings to the public and other users about potential impacts from flash flooding. This article will examine the performance of hydrometeorological products from MRMS and FLASH, and provide perspectives on how NWS forecasters use these products in the prediction of flash flood events with an emphasis on the urban environment.

scholarly journals Is Crowdsourcing a Reliable Method for Mass Data Acquisition? The Case of COVID-19 Spread in Greece During Spring 2020

2020 ◽  
Vol 9 (10) ◽  
pp. 605
Author(s):  
Varvara Antoniou ◽  
Emmanuel Vassilakis ◽  
Maria Hatzaki
Keyword(s):  
Data Acquisition ◽  
Urban Areas ◽  
Situational Awareness ◽  
Temporal Variations ◽  
Disease Spread ◽  
Time Interval ◽  
Short Time Interval ◽  
The Public ◽  
Short Time ◽  
Single Question

We present a GIS-based crowdsourcing application that was launched soon after the first COVID-19 cases had been recorded in Greece, motivated by the need for fast, location-wise data acquisition regarding COVID-19 disease spread during spring 2020, due to limited testing. A single question was posted through a web App, to which the anonymous participants subjectively answered whether or not they had experienced any COVID-19 disease symptoms. Our main goal was to locate geographical areas with increased number of people feeling the symptoms and to determine any temporal changes in the statistics of the survey entries. It was found that the application was rapidly disseminated to the entire Greek territory via social media, having, thus, a great public reception. The higher percentages of participants experiencing symptoms coincided geographically with the highly populated urban areas, having also increased numbers of confirmed cases, while temporal variations were detected that accorded with the restrictions of activities. This application demonstrates that health systems can use crowdsourcing applications that assure anonymity, as an alternative to tracing apps, to identify possible hot spots and to reach and warn the public within a short time interval, increasing at the same time their situational awareness. However, a continuous reminder for participation should be scheduled.

A Harmonized ENC Database as a Foundation of Electronic Navigation

2013 ◽  
pp. 185-192
Author(s):  
Michael Bergmann
Keyword(s):  
Data Streams ◽  
Situational Awareness ◽  
Shipping Industry ◽  
Positioning Systems ◽  
Support Teams ◽  
Data Layer ◽  
Reduce Risk ◽  
Data Layers ◽  
Integrate Data ◽  
Ship Movement

The development of ship navigation classically is based on paper charts, positioning systems like sextants, or nowadays GNSS. Lead by IMO and with support by organizations like IHO and IALA, the shipping industry moves towards the future of enhanced and electronic navigation to improve safety and efficiency of ship movement around the world. The basic data layers for this development are electronic vector charts. This data layer needs to be enhanced by a growing number of other data streams to create situational awareness during any voyage, but also allow for improved planning and efficient ship movement to increase safety and reduce pollution by reducing carbon footprint and reduce risk of environmental issues due to accidents. Given that, the aim of e-Navigation is to integrate data streams, leading to information for situational awareness, which enables wise decisions for mariners on ships and support teams on shore.

Community Water Watch: Measurements, Forecasts and Impacts

2020 ◽  
Author(s):  
Nick van de Giesen ◽  
Frank Annor ◽  
Rick Hagenaars ◽  
Petra Izeboud ◽  
Vivaoliva Shoo ◽  
...  
Keyword(s):  
Data Streams ◽  
Situational Awareness ◽  
Urban Expansion ◽  
Warning System ◽  
Dar Es Salaam ◽  
Exceptional Case ◽  
Red Cross ◽  
Urban Resilience ◽  
Flood Impacts ◽  
Community Water

<p>Dar es Salaam is subject to regular flooding, especially from the Msimbazi River, causing tens of deaths and over $100 million damages per year. Dar es Salaam is not an exceptional case, as many cities in the Global South face rapid urban expansion, which causes increased impermeable services, clogging of drains by sediment and solid waste, as well as encroachment of the floodplains. Although in the long term, structural measures are needed, much is to be gained short term by a flood early warning system that aims to increase situational awareness and optimise allocation of resources during and after floods. The Community Water Watch project, which contributes to the Tanzania Urban Resilience Program, addresses these aspects through a mixture of data streams.</p><p>In an online dashboard, these three data streams come together to create meaningful information. First, a dense network of TAHMO weather stations and two hydrological stations report in near-real time the atmospheric input and state of the system. Second, a hydraulic model uses this information to provide forecasts in terms of discharge, flood levels, and flood extents. Finally, social media platforms, such as Twitter, Telegram, WhatsApp, and JAMII Forums, are continuously searched for texts and photos concerning flooding to provide an overview of flood impacts and ways in which people are dealing with them. Tailor-made dashboards have been built to cater to different users such as the Tanzania Red Cross Society and the local transportation company DART. Due to the intense co-creation processes during the design of the system, these dashboards have already produced actionable information that has prevented damages and possibly has saved lives. The solution is very scalable to any city dealing with similar flood problems.</p>

Management of minor ailments in primary schoolchildren in rural and urban areas

1996 ◽  
Vol 22 (3) ◽  
pp. 167-174
Author(s):  
J A Cantrill ◽  
B Johannesson ◽  
M Nicholson ◽  
P R Noyce
Keyword(s):  
Urban Areas ◽  
Rural And Urban Areas ◽  
Rural And Urban ◽  
Primary Schoolchildren ◽  
Minor Ailments

Cannabis use in Switzerland: The role of attribution of drug use to friends, urbanization and repression 1The study was supported by the Swiss Federal Office of Public Health (Bundesamt für Gesundheit BAG) Grant 316.96.5980.

2001 ◽  
Vol 60 (2) ◽  
pp. 99-107 ◽  
Author(s):  
Holger Schmid
Keyword(s):  
Drug Use ◽  
Urban Areas ◽  
Hierarchical Linear Model ◽  
Cannabis Use ◽  
School Aged Children ◽  
Structural Variables ◽  
Hbsc Study ◽  
Nationally Representative ◽  
Highly Correlated ◽  
Individual Use

Cannabis use does not show homogeneous patterns in a country. In particular, urbanization appears to influence prevalence rates, with higher rates in urban areas. A hierarchical linear model (HLM) was employed to analyze these structural influences on individuals in Switzerland. Data for this analysis were taken from the Switzerland survey of Health Behavior in School-Aged Children (HBSC) Study, the most recent survey to assess drug use in a nationally representative sample of 3473 15-year-olds. A total of 1487 male and 1620 female students indicated their cannabis use and their attributions of drug use to friends. As second level variables we included address density in the 26 Swiss Cantons as an indicator of urbanization and officially recorded offences of cannabis use in the Cantons as an indicator of repressive policy. Attribution of drug use to friends is highly correlated with cannabis use. The correlation is even more pronounced in urban Cantons. However, no association between recorded offences and cannabis use was found. The results suggest that structural variables influence individuals. Living in an urban area effects the attribution of drug use to friends. On the other hand repressive policy does not affect individual use.

Sign in / Sign up

Export Citation Format

Share Document