Climate Change & Computer Audition: A Call to Action and Overview on Audio Intelligence to Help Save the Planet

• URL: http://arxiv.org/abs/2203.06064v1
• Date: Thu, 10 Mar 2022 13:32:31 GMT
• Title: Climate Change & Computer Audition: A Call to Action and Overview on Audio Intelligence to Help Save the Planet
• Authors: Bj\"orn W. Schuller, Alican Akman, Yi Chang, Harry Coppock, Alexander Gebhard, Alexander Kathan, Esther Rituerto-Gonz\'alez, Andreas Triantafyllopoulos, and Florian B. Pokorny
• Abstract summary: This work provides an overview of areas in which audio intelligence can contribute to overcome climate-related challenges. We categorise potential computer audition applications according to the five elements of earth, water, air, fire, and aether.
• Score: 98.97255654573662
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Among the seventeen Sustainable Development Goals (SDGs) proposed within the 2030 Agenda and adopted by all the United Nations member states, the 13$^{th}$ SDG is a call for action to combat climate change for a better world. In this work, we provide an overview of areas in which audio intelligence -- a powerful but in this context so far hardly considered technology -- can contribute to overcome climate-related challenges. We categorise potential computer audition applications according to the five elements of earth, water, air, fire, and aether, proposed by the ancient Greeks in their five element theory; this categorisation serves as a framework to discuss computer audition in relation to different ecological aspects. Earth and water are concerned with the early detection of environmental changes and, thus, with the protection of humans and animals, as well as the monitoring of land and aquatic organisms. Aerial audio is used to monitor and obtain information about bird and insect populations. Furthermore, acoustic measures can deliver relevant information for the monitoring and forecasting of weather and other meteorological phenomena. The fourth considered element is fire. Due to the burning of fossil fuels, the resulting increase in CO$_2$ emissions and the associated rise in temperature, fire is used as a symbol for man-made climate change and in this context includes the monitoring of noise pollution, machines, as well as the early detection of wildfires. In all these areas, computer audition can help counteract climate change. Aether then corresponds to the technology itself that makes this possible. This work explores these areas and discusses potential applications, while positioning computer audition in relation to methodological alternatives.

Related papers

• A Synergistic Approach to Wildfire Prevention and Management Using AI, ML, and 5G Technology in the United States [44.99833362998488]
  This research investigates proactive methods for detecting and handling wildfires in the United States. The specific objective of this research covers proactive detection and prevention of wildfires using advanced technology. Various methods, such as AI-enabled remote sensing and 5G-based active monitoring, can enhance proactive wildfire detection and management.
  arXiv  Detail & Related papers  (2024-02-27T04:09:30Z)
• Human Motion Generation: A Survey [67.38982546213371]
  Human motion generation aims to generate natural human pose sequences and shows immense potential for real-world applications. Most research within this field focuses on generating human motions based on conditional signals, such as text, audio, and scene contexts. We present a comprehensive literature review of human motion generation, which is the first of its kind in this field.
  arXiv  Detail & Related papers  (2023-07-20T14:15:20Z)
• Multi-scale Digital Twin: Developing a fast and physics-informed surrogate model for groundwater contamination with uncertain climate models [53.44486283038738]
  Climate change exacerbates the long-term soil management problem of groundwater contamination. We develop a physics-informed machine learning surrogate model using U-Net enhanced Fourier Neural Contaminated (PDENO) In parallel, we develop a convolutional autoencoder combined with climate data to reduce the dimensionality of climatic region similarities across the United States.
  arXiv  Detail & Related papers  (2022-11-20T06:46:35Z)
• Participatory Action for Citizens' Engagement to Develop a Pro-Environmental Research Application [5.154521998635772]
  We conducted participatory research, art and design activities with the residents of one of the areas most affected by smog in Poland. The participatory research events centered around the theme of ecology and served to design an application that would allow us to conduct field research on pro-environmental behaviours. The application gathers air quality data from the densest network of air pollution sensors in Europe, thereby aligning the visible signs of pollution in the app with the local sensor data.
  arXiv  Detail & Related papers  (2022-07-08T12:20:45Z)
• ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods [89.61670857155173]
  We present our solution to simulate photo-realistic floods on authentic images. We propose ClimateGAN, a model that leverages both simulated and real data for unsupervised domain adaptation and conditional image generation.
  arXiv  Detail & Related papers  (2021-10-06T15:54:57Z)
• Computing Research for the Climate Crisis [2.162108369849964]
  This white paper highlights the role of computing research in addressing climate change-induced challenges. We outline six key impact areas in which these challenges will arise. We identify specific ways in which computing research can help address the associated problems.
  arXiv  Detail & Related papers  (2021-08-12T18:59:12Z)
• Remote sensing, AI and innovative prediction methods for adapting cities to the impacts of the climate change [0.0]
  I propose an AI-based framework which might be useful for extracting indicators from remote sensing images. I underline that this is an open field and an ongoing research for many scientists, therefore I offer an in depth discussion on the challenges and limitations of AI-based methods.
  arXiv  Detail & Related papers  (2021-07-06T15:55:26Z)
• Quantum technologies for climate change: Preliminary assessment [0.0]
  Climate change presents an existential threat to human societies and the Earth's ecosystems. Quantum technologies in computing, sensing, and communication could become useful tools to diagnose and help mitigate the effects of climate change. This report aims to identify potential high-impact use-cases of quantum technologies for climate change with a focus on four main areas.
  arXiv  Detail & Related papers  (2021-06-23T18:02:19Z)
• Analyzing Sustainability Reports Using Natural Language Processing [68.8204255655161]
  In recent years, companies have increasingly been aiming to both mitigate their environmental impact and adapt to the changing climate context. This is reported via increasingly exhaustive reports, which cover many types of climate risks and exposures under the umbrella of Environmental, Social, and Governance (ESG) We present this tool and the methodology that we used to develop it in the present article.
  arXiv  Detail & Related papers  (2020-11-03T21:22:42Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.