Computational Sustainability and Artificial Intelligence in the Developing World
Open accessAbstract
The developing regions of the world contain most of the human population and the planet's natural resources, and hence are particularly important to the study of sustainability. Despite some difficult problems in such places, a period of enormous technology‐driven change has created new opportunities to address poor management of resources and improve human well‐being.
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Point-of-care diagnostics have enjoyed a renaissance, thanks in part to ML.
“Beyond surveillance, point-of-care diagnostics have enjoyed a renaissance, thanks in part to ML [598,648].”
From Tackling climate change with machine learning (2023) · cites this paper as [648]
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References 20 · Cited by 31
Research works printed but not linked: 4
- Aduwo, J.; Mwebaze, E.; and Quinn, J. 2010. Automated Vision-Based Diagnosis of Cassava Mosaic Disease. In Pro- ceedings of the Workshop on Data Mining in Agriculture (DMA). Berlin: Ibai Publishing.
- Frias-Martinez, V., and Virseda, J. 2012. On the Relationship Between Socio-Economic Actors and Cell Phone Usage. In Proceedings of the 3rd International IEEE Conference on Infor- mation and Communication Technologies and Development. Pis- cataway, NJ: Institute of Electrical and Electronics Engineers.
- Frias-Martinez, V.; Rubio, A.; and Frias-Martinez, E. 2012. Measuring the Impact of Epidemic Alerts on Human Mobil- ity Using Cell-Phone Network Data. Paper presented at the Second Workshop on Pervasive Urban Applications, New- castle, UK, June 19.
- Frias-Martinez, V.; Soto, V.; Virseda, J.; and Frias-Martinez, E., 2012. Computing Cost-Effective Census Maps from Cell Phone Traces. Paper presented at the Second Workshop on Pervasive Urban Applications, Newcastle, UK, June 19.
- Authors
- Quinn, J., Frias‐Martinez, V., & Subramanian, L.
- Affiliations
- Makerere University (UG)
- New York University (US)
- ORCID
- Quinn, John
- Venue
- AI Magazine
- Publisher
- Wiley
- Published
- 2014-09
- Volume
- 35
- Issue
- 3
- Pages
- 36-47
- ISSN
- 0738-4602 (ISSN-L)
- 2371-9621
- OpenAlex
- W1578091864
- Cited by
- 31
- References
- 20
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 1 · 2023: 1 · 2022: 8 · 2021: 2 · 2020: 8 · 2019: 3 · 2018: 2 · 2014: 1
- FWCI
- 1.09
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- AI Magazine (publishedVersion, cc-by)
- Topics
- Social Sciences › Sociology and Political Science › Innovation, Sustainability, Human-Machine Systems
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- computational sustainability, artificial intelligence, developing countries, natural resource management, technological change, human well-being, sustainability
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