Technology

Technology plays a central role in achieving the Sustainable Development Goals (SDGs), particularly SDG 9 (Industry, Innovation, and Infrastructure), SDG 4 (Quality Education), SDG 3 (Good Health and Well-being), and SDG 13 (Climate Action). The transformative power of technology can accelerate progress towards all the SDGs by driving economic growth, reducing inequalities, enhancing access to basic services, and promoting sustainability.

Under SDG 9, technology, particularly in terms of Information and Communication Technology (ICT), is a key enabler of industrial innovation and infrastructure development. ICT has the potential to drive economic growth by enhancing productivity, creating jobs, and fostering entrepreneurship. Moreover, it can contribute to making industries more sustainable by facilitating the transition towards smart manufacturing and circular economy models.

Regarding SDG 4, technology can greatly enhance access to quality education. Digital technologies, including e-learning platforms, can break down barriers to education, such as geographical distance, socio-economic status, and physical disabilities. They can also enrich the learning process by enabling personalized, student-centered learning experiences.

In the context of SDG 3, technology has a profound impact on health outcomes. Medical technologies, from simple devices like thermometers to complex systems like MRI machines, have revolutionized healthcare delivery. Furthermore, digital health technologies, such as telemedicine and mobile health apps, can enhance access to health services, improve patient outcomes, and reduce healthcare costs.

For SDG 13, technology offers powerful tools for mitigating and adapting to climate change. Renewable energy technologies can help to reduce greenhouse gas emissions, while climate information services can enhance resilience to climate impacts. Furthermore, digital technologies can facilitate the monitoring and reporting of climate actions, contributing to greater transparency and accountability.

However, the benefits of technology are not automatic, and there are significant challenges to overcome, including the digital divide, cybersecurity threats, and ethical issues related to privacy and data ownership. Thus, policy interventions and multi-stakeholder partnerships are needed to ensure that technology serves as a catalyst for sustainable development and does not exacerbate inequalities.

In the context of applying machine learning to solve problems for risk prediction, disease detection, and treatment evaluation, EHR pose many challenges– they do not have a consistent, standardized format across institutions particularly in US, can contain human errors and introduce collection biases. In addition, some institutions or geographic regions do not have access to the technology or financial resources necessary to implement EHR, thus resulting in vulnerable and disadvantaged communities not being electronically visible.
Results of ultrafiltration (UF) and reverse osmosis (RO) pilot plant on-site tests for wastewater reclamation are reported here with 90% and 65% water recovery achieved for UF and RO stages, respectively. RO achieved high quality requirements for industrial reuse supporting SDG 6.
Elsevier,

Measurement: Journal of the International Measurement Confederation, Volume 209, 15 March 2023

The research aims to assess the environmental sustainability of measurements, and the investigation is conducted through two case studies within the information and communication technology sector. The authors put forward recommendations for increasing a measurement's environmental sustainability.
Nuclear desalination is an important non-electric application of nuclear power and heat, having strong interlinkages and alignment with sustainable development, climate change management (both mitigation and adaptation), and water security.
Elsevier,

Engineering Applications of Artificial Intelligence, Volume 117, Part A, 2023, 105617

An examination of the challenges involved in water demand forecasting, with a particular focus on the impact of COVID-19 on the performance of various machine learning models designed for this purpose.
Evaluating the bias and fairness of ML models has drawn much attention in the machine learning and statistics community. Researchers have proposed methods to assess and mitigate the bias for various applications that could adversely affect underrepresented groups, like recidivism prediction, credit risk prediction, and income prediction.
An investigation supporting SDGs 7 and 13, based in Ghana, into the possibility of using slaughterhouse wastes as a source of renewable energy through biogas technology. The researchers concluded that 'Ghana generates significant amount of slaughterhouse waste each year that can be processed using AD [anaerobic digestion] for energy and electricity production to supplement the country's electricity needs, while reducing GHG emissions'.
This Article supports SDG7 and 13 by proposing a new model to identify the most critical features of energy storage system technologies to enhance renewable energy integration and achieve New York State's climate goals from 2025 to 2040.
This chapter advances UN SDG goal 7 by discussing the role of nanosized metal catalysts in CO2 reduction in fuels
Elsevier,

Trends in Biotechnology, Volume , 2023

This is an Opinion article by two highly accomplished synthetic biologists that explains how synthetic biology tools can benefit oceans.

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