Special Issue on AI for Sustainability
IEEE Latin America Transactions
Special Issue on AI for Sustainability
We are at the cusp of two massive historic trends intimately intermingled. On the one hand, our technological revolutions have increased our standards of living quality, including a longer lifespan and larger wealth. On the other hand, we are amid sustainability threats, including climate change and loss of biodiversity. The way our generation responds to the latter challenge using our considerable accumulated level of understanding will have a significant impact in generations to come.
Artificial Intelligence (AI) for sustainability has emerged as a powerful tool with substantial groundbreaking advances. It has opened countless avenues to improve the understanding of the underlying problems while supporting effective sound solutions. However, to take full advantage of the available science and technology, we need to increase their visibility to stimulate its widespread adoption. AI refers to the development of machine capabilities such as learning, reasoning, knowledge representation, planning, perception, problem-solving, and pattern recognition. Due to the potential for broad impact of these capabilities, it is imperative to support sustainability efforts to extend their adoption and promote awareness about their potential. In particular, we call for participation through articles addressing issues along the following lines: a) Applications of AI tackling climate change, addressing biodiversity loss, and considering human vulnerability; b) research describing the construction, implementation, evaluation, and how-to-do capabilities supporting sustainability; and c) making sure AI leaves a small impact as possible on sustainability.
The purpose of this Special Issue is to provide a forum for the researchers and practitioners related to the rapidly developing field of AI for sustainability to share their novel and original research on the topic. Therefore, we encourage the submission of the practitioners’ latest unpublished work on AI for sustainability. Of our particular interest are the developments from research groups in Latin America and elsewhere. The areas of interest include both theory and applications of AI on the following topics (they are not limited to):
- Wild animal and plants identification and monitoring.
- Electric systems. Usage forecast, greenhouse gases leaking, models with small datasets
- Efficient transportation models, smart shipping routing, optimal bike-sharing distribution
- Buildings and cities. Cooling and heating control, lighting adaptation, vehicular traffic analysis
- Food waste, cement and ammonia reduction,
- Farms and forests. Gases, agriculture, pipelines leaking, carbon, deforestation remote sensing
- Carbon dioxide removal. Identification and monitoring of placement sites.
- Weather prediction. Improved weather prediction models, long-term and reliable climate monitoring, ocean reflectivity, and warming monitoring.
- Social impacts. Adaptation, interaction with the environment.
- Carbon offset pricing, sustainability risk assessment, biodiversity, and climate change impacts.
Call for papers: December 13, 2021
Submissions Deadline: March 21, 2022
Notification of Acceptance: May 23, 2022
Final Manuscript Due: July 4, 2022
Publication Date: September 2022
Authors must submit all original manuscripts electronically through the system at https://latamt.ieeer9.org.
Original submissions could be written in English, Portuguese or Spanish and must not be currently under consideration for publication in other Journals nor be part of Conference proceedings.
Authors accepted papers or conditionally accepted papers of this issue will be asked to share their code according to the area of the paper. Further information about codeshare options as well as guidelines and submission information can be found at
Climate Change AI
Universidade de Brasília
Guest Editorial Board
- Adolfo Bauchspiess, University of Brasilia
- Ana Carolina Lorena, Instituto Tecnológico de Aeronáutica
- Anamitra Saha, MIT
- Anesio Leles Ferreira Filho, University of Brasilia
- Bogdan Raducanu, CVC
- Bogdan Strimbu, Oregon State University
- Daniel Mauricio Muñoz Arboleda, University of Brasilia
- Edgar Roman-Rangel, ITAM
- Erik Zamora, IPN
- Flávio Elias Gomes de Deus, University of Brasilia
- Francisco Martinez, INAOEP
- Geraldo P. R. Filho, University of Brasilia
- Hugo Filipe Pinheiro Rodrigues, Universidade de Aveiro
- Hugo Jair Escalante, INAOEP
- Jayme Garcia Arnal Barbedo, Embrapa Brazil
- Jordi Vitria, Universidad de Barcelona
- Juan Ramon Terven, AiFi
- Li Weigang, University of Brasilia
- Luiz Antonio Celiberto Junior, University of ABC
- Maria João Sousa, U Lisboa, CCAI
- Mariano Rivera, CIMAT
- Michael Barbehenn, MIT
- Moacir Antonelli Ponti, University of São Paulo
- Paulo Barreto Cachim, Universidade de Aveiro
- Petia Radeva, Universidad de Barcelona
- Rafael Timóteo de Sousa Júnior, University of Brasilia
- Raquel Valente de Pinho Matos, Universidade de Aveiro
- Roberto Manduchi, University of California
- Sai Ravela, MIT
- Sara Beery, Caltech
- Saul Solorio, INAOEP
- Silvana Aciar, Universidad Nacional de San Juan
- Vinicius Ruela Pereira Borges, University of Brasilia
- Wilfrido Gómez-Flores, Cinvestav