ePrints@IIScePrints@IISc Home | About | Browse | Latest Additions | Advanced Search | Contact | Help

An Intelligent ABM-based Framework for Developing Pandemic-Resilient Urban Spaces in Post-COVID Smart Cities

Prajapati, SP and Bhaumik, R and Kumar, T (2022) An Intelligent ABM-based Framework for Developing Pandemic-Resilient Urban Spaces in Post-COVID Smart Cities. In: 2022 International Conference on Machine Learning and Data Engineering, ICMLDE 2022, 7- 8 September 2022, Dehradun, pp. 2299-2308.

icmlde_2022.pdf - Published Version

Download (1MB) | Preview
Official URL: https://doi.org/10.1016/j.procs.2023.01.205


As of August 2022, the COVID-19 pandemic has accounted for over six million deaths globally. The urban population has been severely affected by this viral pandemic and the ensuing lockdowns, resulting in increased poverty and inequality, slowed economic growth, and a general decline in quality of life. This paper proposes a framework to evaluate the effects of the pandemic by combining agent-based simulations—based on Susceptible-Infectious-Recovered (SIR) model—with a hybrid neural network. A baseline agent-based model (ABM) incorporating various epidemiological parameters of a viral pandemic was developed, followed by an additional functional layer that integrates factors like agent mobility restrictions and isolation. It is inferred from the results that low population densities of agents and high restrictions on agent mobility could inhibit the rapid spread of the pandemic. This framework also envisages a hybrid neural network that combines the layers of convolutional neural network (CNN) and long-short-term memory (LSTM) architecture for predicting the spatiotemporal probability of infection spread using real-world pandemic data for future pandemics. This framework could aid designers, regulators, urban planners, and policymakers develop resilient, healthy, and sustainable urban spaces in post-COVID smart cities.

Item Type: Conference Paper
Publication: Procedia Computer Science
Publisher: Elsevier B.V.
Additional Information: The copyright for this article belongs to the Author.
Keywords: Agent-based modelling (ABM); COVID-19; Neural Networks; Pandemic modelling; Simulation; Smart Cities; Urban Planning
Department/Centre: Division of Electrical Sciences > Electronic Systems Engineering (Formerly Centre for Electronic Design & Technology)
Division of Mechanical Sciences > Centre for Product Design & Manufacturing
Date Deposited: 25 Jul 2023 10:34
Last Modified: 25 Jul 2023 10:34
URI: https://eprints.iisc.ac.in/id/eprint/82657

Actions (login required)

View Item View Item