ArticleSustainable cities and society2021
Towards the sustainable development of smart cities through mass video surveillance: A response to the COVID-19 pandemic.
Article in Sustainable cities and society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
33 citing papers in PubMed, 1 synthesis or guideline pooled it.
- IoT Adoption and Application for Smart Healthcare: A Systematic Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Video map: A realtime orthographic geo-image considering DEM and semantic information.PloS one · 2025Article
- Fog-based deep learning framework for real-time pandemic screening in smart cities from multi-site tomographies.BMC medical imaging · 2024Article
- Influences of obstacle factors on the transmission trends of respiratory infectious diseases in indoor public places.Journal of building engineering · 2023Article
- Computational decision-support tools for urban design to improve resilience against COVID-19 and other infectious diseases: A systematic review.Progress in planning · 2023Article
- Review on the Evaluation and Development of Artificial Intelligence for COVID-19 Containment.Sensors (Basel, Switzerland) · 2023Review
- A new YOLO-based method for social distancing from real-time videos.Neural computing & applications · 2023Article
- Human behavior in the time of COVID-19: Learning from big data.Frontiers in big data · 2023Review
- Popular deep learning algorithms for disease prediction: a review.Cluster computing · 2023Article
- Detection of COVID-19 Case from Chest CT Images Using Deformable Deep Convolutional Neural Network.Journal of healthcare engineering · 2023Article
- Medical image-based detection of COVID-19 using Deep Convolution Neural Networks.Multimedia systems · 2023Article
- The Impact of COVID-19 on the Sustainable Development Goals: Achievements and Expectations.International journal of environmental research and public health · 2022Review
- Deep visual social distancing monitoring to combat COVID-19: A comprehensive survey.Sustainable cities and society · 2022Review
- Links between the pandemic and urban green spaces, a perspective on spatial indices of landscape garden cities in China.Sustainable cities and society · 2022Article
- Study on the mechanism of public attention to a major event: The outbreak of COVID-19 in China.Sustainable cities and society · 2022Article
- Discovering spatial-temporal patterns via complex networks in investigating COVID-19 pandemic in the United States.Sustainable cities and society · 2022Article
- A Social Distance Estimation and Crowd Monitoring System for Surveillance Cameras.Sensors (Basel, Switzerland) · 2022Article
- From federal transfers and local investments to a potential convergence of COVID-19 and climate change: The case study of São Paulo city.Sustainable cities and society · 2022Article
- Virtual Healthcare Center for COVID-19 Patient Detection Based on Artificial Intelligence Approaches.The Canadian journal of infectious diseases & medical microbiology = Journal canadien des maladies infectieuses et de la microbiologie medicale · 2022Article
- Identification of sampling points for the detection of SARS-CoV-2 in the sewage system.Sustainable cities and society · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Sustainable smart city initiatives around the world have recently had great impact on the lives of citizens and brought significant changes to society. More precisely, data-driven smart applications that efficiently manage sparse resources are offering a futuristic vision of smart, efficient, and secure city operations. However, the ongoing COVID-19 pandemic has revealed the limitations of existing smart city deployment; hence; the development of systems and architectures capable of providing fast and effective mechanisms to limit further spread of the virus has become paramount. An active surveillance system capable of monitoring and enforcing social distancing between people can effectively slow the spread of this deadly virus. In this paper, we propose a data-driven deep learning-based framework for the sustainable development of a smart city, offering a timely response to combat the COVID-19 pandemic through mass video surveillance. To implementing social distancing monitoring, we used three deep learning-based real-time object detection models for the detection of people in videos captured with a monocular camera. We validated the performance of our system using a real-world video surveillance dataset for effective deployment.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.