SDG-13

SDG-13 Climate action

Main
SDG-13

Targets of this goal

By 2030, it is necessary to achieve the following targets:

Keep the temperature rise between 1.5 and 2.0 ^ºC
Strengthen resilience and adaptive capacity to climate-related risks and natural disasters in all countries
Incorporate climate change measures into national policies, strategies and plans
Improve education, awareness and human and institutional capacity regarding climate change mitigation, adaptation, reduction of its effects and early warning
Promote mechanisms to increase capacity for effective planning and management in relation to climate change

We can currently advance towards the attainment of this goal:

How does technology contribute to this SDG? See what we propose and tell us what you think

Lessons Learnt

We have analyzed the literature and extracted the following ideas on how technologies are favouring this SDG.
See also what we propose and tell us what you think

L.1

AI is crucial to improve the early detection of natural catastrophes, allowing to mitigate the problems due to climate change. This is important since climate change accentuates these catastrophes

The use of predictive AI techniques can be applied with regardless of in-situ physical operation, allowing it to be done remotely. This is especially important since many countries at risk may not have the necessary resources.

L.3

AI allows a better prediction of energy needs, which will allow energy-producing companies to better adjust their production, reducing the use of polluting energy to produce excess

L.4

Car pollution causes a very important percentage of polluting gas emissions, hence any reduction would have very beneficial effects. AI can help reduce traffic flow by improving traffic flow by reducing congestion and traffic jams. The main way to do this is by optimizing traffic signs

L.5

AI can be used to improve the efficiency of hybrid vehicles, reducing consumption

Recommendations

The proposed actions on which we introduce an opinion poll for this SDG, are described below:

Poll for SDG-13

The analyses of interrelationships between emerging technologies & AI, and the possibilities they offer to pursue the SDGs, led us to propose a series of actions and/or potential projects to develop.
Among these recommendations, which one is more important in your opinion?

Give my opinion

R13.1 - Improve Natural Disaster Prediction Using Advanced AI Models

Although the incorporation of AI has made it possible to improve predictive models, AI techniques have been often applied directly, without making improvements over the application of techniques to the predictive model. Therefore, there is room for improvement over the use of AI for predictions, through parameter adjustment or hybrid techniques. To promote such improvement, it would be convenient to use multidisciplinary teams with the combined efforts of meteorologists and AI experts. In addition, AI systems capable of processing images and their temporal treatment would make it possible to predict and study behaviors such as desertification without the need to deploy special sensors.

R13.2 - IoT sensor technologies to allow AI to make predictions of natural disasters in real time

A prompt monitoring of atmospheric changes involves the use of sensors to measure the different measurements necessary for prediction. We propose the use of smart sensors connected by wireless technologies such as 5G, to allow results to be transmitted in real time. Furthermore, given that the result of the prediction might be natural catastrophes that can affect communications, IoT technologies would allow a distributed model (for greater robustness) to ensure early communication to the different corresponding organisms, and thus allow the taking of decisions as quickly as possible.

R13.3 - Creation of predictive models worldwide, applying pre-learned models in different areas of the world

Many of the AI techniques have enabled better levels of prediction of natural disasters. However, most of these have been developed and tested in a circumscribed way to a specific region, and with a greater tendency in regions with greater economic capacity. Given the global nature of climate change, we propose to design prediction models that can be applied in other regions. This would imply global coordination: on the one hand, offering pre-learned models to global institutions that would allow them to be used in different countries; on the other hand, facilitating and allowing learning in new regions, to improve prediction in those areas. Additionally, it would be convenient to use AI to preprocess the data globally.

R13.4 - AI to optimize urban traffic, thereby reducing pollution, through improvements in traffic signs

R13.5 - Augmented Reality and Conversational Agents to improve Environmental education

A very important aspect for such a long-term objective as combating climate change requires the continuous effort across generations. That means making a significant educational effort. New technologies, in combination with techniques such as Augmented Reality or conversational agents, can provide a visual approach to the dangers of climate change that can be very well received. Likewise, AI can be used to analyze its acceptance through the use of social networks that are widely used by new generations.