From poverty alleviation to national security: Computational modelling enabling smart solutions that work

“By extending its applications, we can harness the power of computational modelling to tackle poverty, unemployment and national security and promote environmental, social and governance (ESG) practices.” –

Dr Regina Maphanga

ESG practices. As a thought leader in computational modelling, I firmly believe that leveraging its capabilities in these domains can reshape our society and create a more equitable and secure future.

Poverty alleviation and unemployment

Poverty alleviation and unemployment are pressing socioeconomic challenges that require comprehensive approaches to address them effectively. Computational modelling offers a powerful tool for understanding the intricate dynamics of these issues and developing targeted strategies for intervention.

Computer modelling refers to the process of creating virtual representations or simulations of real-world systems, allowing researchers and policymakers to study and analyse complex phenomena in a controlled environment or processes using computer software and algorithms. It entails the use of mathematical equations, data inputs and computational algorithms to mimic and simulate the behaviour, interactions and outcomes of the system being modelled.

Computer modelling offers several benefits and applications. It allows researchers, scientists, engineers and decision-makers to study complex systems, explore what-if scenarios, optimise designs, predict outcomes and make informed decisions without the need for costly or time-consuming physical experimentation. It bridges the gap between theoretical understanding and real-world complexity, enabling us to gain insights into systems that may be inaccessible, expensive or dangerous to study physically.

By extending its applications, we can harness the power of computational modelling to tackle poverty, unemployment and national security and promote

By applying computational models, researchers can simulate various scenarios to assess the impact of different policies and interventions on poverty reduction and employment creation. These models consider factors such as economic indicators, social conditions, educational attainment levels, access to resources and government initiatives, to cite a few.

Furthermore, computational modelling enables policymakers to identify potential bottlenecks or unintended consequences that may arise from certain interventions. By analysing various parameters within the model’s framework, decision-makers can optimise resource allocation by prioritising sectors with a high potential for job creation, while also targeting vulnerable populations that are most in need of support.

This understanding enables us to design targeted interventions such as skill-development programmes, job-creation initiatives and social-safety nets, with the aim of fostering inclusive economic growth and enhancing livelihoods.

National security

Ensuring the safety and security of nations in an increasingly digital and interconnected world demands advanced tools for risk assessment, intelligence analysis and strategic planning. Computational modelling plays a pivotal role in analysing complex geopolitical landscapes, simulating potential scenarios and assessing the impacts of various policies. By integrating diverse datasets and employing sophisticated algorithms we can enhance our ability to detect emerging threats, formulate effective defence strategies and safeguard national interests.

ESG practices

The integration of ESG principles is vital for organisations that are committed to long-term sustainability and responsible business practices. Computational modelling empowers decision-makers to evaluate the impact of their actions on environmental conservation, social wellbeing and corporate governance. By incorporating diverse variables and quantifying the potential outcomes, organisations can identify sustainable investment opportunities, optimise resource allocation and enhance transparency and accountability.

Manufacturing

Next-generation manufacturing industries can push the boundaries of innovation by adopting modelling tools. Computational modelling supports innovation in product and process design, reduces the need for physical testing and prototypes, defines complex process parameters and leads to quality products and robust manufacturing processes.

Smart infrastructure and sustainable urban planning

The efficient utilisation of resources, resilience to climate change and the development of smart cities are critical components of a sustainable future. Computational modelling enables us to design and optimise infrastructure systems, integrating renewable energy sources, transportation networks and waste management systems. By simulating the interactions between these components, we can identify strategies that minimise environmental impact, enhance energy efficiency and improve the quality of life for urban populations.

Crisis response and disaster

Management in the face of natural disasters, disease outbreaks or humanitarian crises, computational modelling offers crucial support for emergency response and resource allocation. By simulating different scenarios emergency planners can identify optimal strategies, assess the potential impacts and allocate resources effectively. Furthermore, modelling the spread of infectious diseases aids in understanding transmission dynamics, evaluating the effectiveness of interventions and formulating proactive healthcare strategies.

As computational modelling revolutionises our understanding of complex systems, it becomes a powerful tool for driving social impact. By leveraging its capabilities in poverty alleviation, unemployment mitigation, national security and ESG practices, we can foster a more inclusive, secure and sustainable future.

I am committed to pushing the boundaries of its application in various domains, working towards a world in which technology is harnessed for the betterment of society. Let us embrace computational modelling as a catalyst for transformative change, shaping a future that leaves no-one behind and prioritises the wellbeing of both people and the planet. ■

This thought leadership article was written by Dr Regina Maphanga. Dr Maphanga is the Research Group Leader for the Design and Optimisation research group at the Council for Scientific and Industrial Research (CSIR) in Pretoria. She has a PhD in physics from the University of Limpopo.

Email: RMaphangai@csir.co.za

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