Computational Sustainability and Artificial Intelligence in the Developing World

@article{Quinn2014ComputationalSA,
  title={Computational Sustainability and Artificial Intelligence in the Developing World},
  author={John A. Quinn and Vanessa Fr{\'i}as-Mart{\'i}nez and Lakshminarayanan Subramanian},
  journal={AI Mag.},
  year={2014},
  volume={35},
  pages={36-47}
}
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. 

Figures from this paper

Sustainability and Artificial Intelligence: Necessary, Challenging, and Promising Intersections
  • H. LiaoZijia Wang
  • Business
    2020 Management Science Informatization and Economic Innovation Development Conference (MSIEID)
  • 2020
Both digital economy and digital technology researchers increasingly recognize the need to better address the role that artificial intelligence (AI) plays in shaping the evolution of the
Public Perception of Artificial Intelligence and Its Connections to the Sustainable Development Goals
Artificial Intelligence (AI) will not just change our lives but bring about revolutionary transformation. AI can augment efficiencies of good and bad things and thus has been considered both an
Tackling Climate Change with Machine Learning
TLDR
From smart grids to disaster management, high impact problems where existing gaps can be filled by ML are identified, in collaboration with other fields, to join the global effort against climate change.
Recent Advances and Challenges in AI for Sustainable Agricultural Systems
Agriculture is a booming market for several decades. Technological advances in this sector have produced promising results that can optimize profitability, productivity and sustainability. A
Societal Benefits and Risks of Artificial Intelligence : A Succinct Survey
TLDR
This work studied the major societal benefits of AI in the areas of health care, education, and agriculture, discussing the positive change that AI has brought to each and addressing the risks society faces when AI is practiced without proper care.
Key enablers for deploying artificial intelligence for circular economy embracing sustainable product design: Three case studies
TLDR
This research used qualitative research methodology as two stage process and framework on the key roles of AI in circular product design and the key enablers are proposed based on the findings of qualitative research and theoretical part of the study.
Making distributed edge machine learning for resource-constrained communities and environments smarter: contexts and challenges
TLDR
This paper analyzes representative real-world business scenarios for edge ML solutions and their contexts in resource-constrained communities and environments and identifies and map the key distinguished contexts of distributed edge ML.
Construction and Research of Internet+ Experimental Teaching Platform Based on Artificial Intelligence
  • Shuangyuan Li
  • Computer Science
    Proceedings of the 2019 3rd International Conference on Education, Management Science and Economics (ICEMSE 2019)
  • 2019
The research of Internet + experimental teaching platform based on artificial intelligence makes full use of artificial intelligence, WEB technology and Internet + to transform and improve the
Leveraging Data Science to Combat COVID-19: A Comprehensive Review
TLDR
This paper attempts to systematise the various COVID-19 research activities leveraging data science, where data science is defined broadly to encompass the various methods and tools that can be used to store, process, and extract insights from data.
A Hidden Markov Model-Based Acoustic Cicada Detector for Crowdsourced Smartphone Biodiversity Monitoring
TLDR
A novel insect detection algorithm based on a hidden Markov model to which the ratio of two key frequencies extracted through the Goertzel algorithm is fed, which is much more robust to noise while also reducing the computational cost.
...
...

References

SHOWING 1-10 OF 29 REFERENCES
Location specific summarization of climatic and agricultural trends
TLDR
The design of a system that mines disparate information sources on the Web to automatically summarize important climatic and agricultural trends for any specific location and construct a location-specific climaticand agricultural information portal is described.
Coupling Spatiotemporal Disease Modeling with Diagnosis
TLDR
A state space model of malaria spread and a computer vision based system for detecting plasmodium in microscopical blood smear images are introduced, and it is demonstrated the tractability of combining both elements and the improvement in accuracy this brings about.
Road traffic congestion in the developing world
TLDR
A local de-congestion protocol that coordinates traffic signal behavior within a small area and can locally prevent congestion collapse sustaining time variant traffic bursts is presented.
Increased-specificity famine prediction using satellite observation data
TLDR
The use of remote sensing satellite data to predict food shortages among different categories of households in famine-prone areas is examined and a method for clustering households in such a way that the cluster decision boundaries are both relevant for improved-specificity famine prediction and are easily communicated is described.
An Agent-Based Model of Epidemic Spread Using Human Mobility and Social Network Information
TLDR
An agent-based system that uses social interactions and individual mobility patterns extracted from call detail records to accurately model virus spreading is proposed and applied to study the 2009 H1N1 outbreak in Mexico and to evaluate the impact that government mandates had on the spreading of the virus.
Low cost video-based traffic congestion monitoring using phones as sensors
TLDR
By designing roadside monitoring units around camera phones, the prototype radically reduces costs compared to convential CCTV systems and hence makes it practical for deployment in this context and results are shown.
Forecasting socioeconomic trends with cell phone records
TLDR
A battery of different predictive approaches for time series are explored and it is shown that multivariate time-series models yield R-square values of up to 0.65 for certain socioeconomic indicators.
Computing Cost-Effective Census Maps From Cell Phone Traces
Census maps contain important socio-economic information regarding the population of a country. Computing these maps is crit ical given that policy makers often times make important decisions based
Gaussian Processes for Ordinal Regression
We present a probabilistic kernel approach to ordinal regression based on Gaussian processes. A threshold model that generalizes the probit function is used as the likelihood function for ordinal
Measuring the impact of epidemic alerts on human mobility using cell-phone network data
TLDR
The impact that the alerts issued by the Mexican government had on the mobility of the Mexican population during the H1N1 flu outbreak in April and May of 2009 is measured.
...
...