Today, over half of the world’s population lives in urban areas and by the middle of this century 7 out of 10 people will live in a city. This increased urbanization has also lead to more and more people residing in informal settlements, generally known as slums. By the middle of the 21st century, it is estimated that the urban population of developing countries will more than double, increasing from 2.5 billion in 2009 to almost 5.2 billion in 2050. In India (2011) roughly 13.7 million households, or 17.4% of urban Indian households, were considered to be part of a slum. Each slum in a city suffers from varying degrees of depravity. This proposal aims to build high-resolution agent-based models that can describe the growth dynamics of slums in Bangalore. Such a model will create a virtual slum that decision-makers, and researchers, can use to explore how different policies would influence the growth, development or contraction of slums. The team plan to build on their existing work and develop a decision support system for slums in general, which will help guide experts when evaluating or designing policies to improve conditions within slums. This involves developing new computational methods for analyzing satellite images and new data visualization techniques for simulation steering. Through extending the existing decision support prototype, and applying it to a new domain of slum policy, the hope is to generalize the current software. Therefore, this proposal will aim to develop a reusable software framework for decision support and disseminate it to other users.
In the Kumbh Mela Experiment we plan to develop sophisticated methods and algorithms to aid planners and event managers in managing extremely large crowds. The project aims to deliver the core components of an entire crowd management solution, all the way from designing and building personnel devices for tracking movement, to developing advanced computational models to help predict how the crowd may evolve. This leads to a vision of a living simulation where various data sources (personal devices, video cameras, smart phones, monitoring drones) can be fused into models and executed on an advanced compute infrastructure capable of providing both planning, as well as real-time reactive decision-making. This proposal addresses three key research areas related to the understanding and management of huge human crowds: Data Collection; Data Analysis; Modelling and Prediction. The Kumbh Mela Experiment will happen in April-May 2016 and will present a once in a lifetime opportunity to do both extremely exciting new science and application.
By the middle of the 21st century, it is estimated that the urban population of developing counties will more than double, increasing from 2.5 billion in 2009 to almost 5.2 billion in 2050. The SIM-CITY examines urban processes within the India City of Bangalore. This includes simulation-based optimisation of fire station response, and agent-based models to understand the concept of living wage in Slums.
I worked as the NTU-PI of Research Package 5 (RP5) of the TUM-CREATE project. For more details of the project please visit http://tum-create.edu.sg/. I am still involved with the project as a collaborator
COSMOS – CROSIT
While I was working in Singapore I was involved in a number of projects related to Crowd Simulation. For details about all of this work please see http://crowds.sce.ntu.edu.sg
This is a project looking at developing data driven agent-based models to understand the development at identifying risk criteria for youth violence in Singapore. I am a collaborator on this project which will start officially in 2013.
I was also a member of the MAGIC research team at NTU: http://magic.ntu.edu.sg/
Validation through Human Computation
Agent-based modeling as a methodology for understanding natural phenomena is becoming increasingly popular in many disciplines of scientific research. Validation is still a significant problem for agent- based modelers and while various validation methodologies have been proposed, none have been widely adopted. Data plays a key role in the validation of any simulation system, typically large amounts of observable real world data are necessary to compare with model outputs. However, the complex nature of the studied natural systems will often make data collection difficult. This is certainly true for crowd and egress simulation, where data is limited and difficult to collect. In this project we attempt to develop a new technique for validation of agent-based models, particularly those which relate to human behavior. This methodology adopts ideas from the field of Human Computation as a means of collecting large amounts of contextual behavioral data. The key principle is to use games as a means of framing behavioral questions to try and capture people’s natural and instinctive decisions. We investigate some key design challenges for such games and plan to develop one example game in the form of Escape. Escape is an egress based game where people are tasked to escape from rooms inhabited by other people.
This project proposes to investigate the feasibility of using agent-based simulation and sensor technology to design an intelligent dynamic building or venue evacuation system. The system assumes an “intelligent” building, designed to have multiple static and dynamic sensors for: smoke intensity, temperature, crowd density (through image processing and CCTV), etc. During an emergency situation these sensors are used to dynamically gather information about the unfolding scenario. We consider a system that is equipped with electronic displays, which can be changed to indicate location specific directions (forward, back, left, right, down and up) by some control mechanism. With sensors and signs, it would be possible to dynamically adjust the exit directions depending on the environmental conditions and movement of the evacuees. Alone, these mechanisms (sensors and dynamic signs) would provide an effective method for a human safety controller to guide building inhabitants from the building. However, this rests on the assumption that the controller is able to make a fast and safe evacuation plan. In reality: fire spread, smoke spread, overcrowding and human panic make this planning process very complex. Moreover, the dynamic nature of the environment in emergency scenarios means events unfold in highly unpredictable ways (that would be very difficult for a fixed simulation, or prior planning to account for, e.g., bomb explosion) and effectively invalidate the effectiveness of any pre-chosen route.
DEPATHSS intends to develop a simulation system which, given sensory input from the environment, will automatically build a simulation model and then execute and evaluate a series of simulated evacuation plans to determine the safest egress plan. Once an appropriate plan is determined, the system will configure the exit signboards to direct the inhabitants to safety. The simulation will also be able to interact with the environment and effectively investigate and build its own understanding of the environment through the use of dynamic sensors.
The project is looking at various aspects of modeling, simulation and visualisation of large human crowds for military operations. The project aims to develop an entire framework for agent-based modelling of crowds under a variety of different scenarios. The application of crowd simulation to military scenarios is quite unique but is relevant to planning, training and operational decision making. The are five main areas of work being investigated by a team of 6 researchers.
GABARDINE – EU
I worked as a research fellow in the Department of Mechanical, Materials and Manufacturing Engineering at Nottingham University. This was as part of a European project GABARDINE. The aim of the project was the development of an integrative methodology for: 1) the evaluation of aquifer water budgets as a basis for the determination of hydrologic deficits; 2) mapping of areas according to groundwater quality and vulnerability to contamination factors; 3) areas potentially suitable for seasonal and long-term storage; 4) Delineation and characterisation of replenishment areas to groundwater aquifers, using state-of-the-art remote sensing, aerial and satellite imaging, incorporating them into a GIS system and for the identification of propitious areas for artificial replenishment. At Nottingham we were developing new numerical techniques for the simulation of groundwater flow. As part of this we developed CFD style software which allows experimenters to apply the newly developed numerical techniques to a variety of flow problems. We also investigated the application of parallel techniques and in particular GPGPUs to the problem of simulating flow in porous media. As a consequence of this work I am now a member of a commercial consultancy team which offer modelling and simulation services in the fields water resource management, pollution control, computational hydrology, R&D projects in hydrology, hydro-geology and other environmental issues and energy related problems (geothermal energy, energy storage in porous formations and CO2 sequestration).
I worked for a short period of 3 months as a research consultant at Birmingham University. In this time I was focused on development of a system for large scale simulation of p2p networks. This work was an adaptation of the PeerSim simulation tool developed as part of the BISON project. I was also involved with a team of people responsible for installation and promotion of the Blue-Bear cluster.
I was a Research Fellow at the University of Nottingham working on a BBSRC project, Agent-based Integrative Modelling of Bacterial Populations. The aim of this project is to explore the feasibility of using distributed Grid-based simulation techniques for studying complex agent-based models of cell populations. The project will investigate the computational efficiency of biological simulations built using HLA-compliant simulators instantiated and linked using Grid services and, more generally, assess the suitability of the HLA framework for biological modelling. This is a collaborative project with the Centre for Mathematical Medicine at the University of Nottingham.
I completed my PhD Adaptive Optimistic Simulation of Multi-Agent Systems at Nottingham University as part of pdes-mas a large EPSRC project with Birmingham University. My PhD developed two new synchronisation algorithms for PDES, with a particular focus on multi-agent simulation. I was also involved with the development of methods for dynamic load balancing and interest management and investigated how these areas relate to synchronisation. The project team developed a simulation kernel in C++ which is still currently being developed and adapted. Towards the beginning of my PhD work I adapted the SIM_AGENT toolkit and made it possible to write HLA compatible agent simulations. The resulting system is a collection of SIM_AGENT libraries which we have called HLA_AGENT.