Third Edition

History AI & Environment

[1] L. Fuller-Wright, Climate modeling at Princeton, Princeton University, July 2020. Accessed on: Sep. 4 2020. [Online]. Available:

[2] F. Sistler, “Robotics and intelligent machines in agriculture”, IEEE Journal of Robotics and Automation, vol. 3, no. 1, pp. 3–6, 1987.

[3] S. J. Key, “Productivity modelling and forecasting for automated shearing machinery,” in Proceedings of the Agri-mation Conference Exposition, 1985, pp. 200–209.

[4] A. W. Minns, and M. J. Hall, “Artificial neural networks as rainfall-runoff models”, Hydrological Sciences Journal, vol. 41, no. 3, pp. 399–417, 1996.

[5] R. Caponetto, L. Fortuna, G. Nunnari, L. Occhipinti, and M. G. Xibilia, “Soft computing for greenhouse climate control,” IEEE Transactions on Fuzzy Systems, Vol. 8, No. 6, pp. 753–760, 2000.

[6] I. Keramitsoglou, C. Cartalis, and C. Kiranoudis, “Automatic identification of oil spills on satellite images,” Environmental Modelling & Software, vol. 21, no. 5, pp. 640–652, 2006.

[7] L. Cooper, Air pollution in China and IBM green initiatives, IBM, August 2016. Accessed on: Sep. 4 2020. [Online]. Available:

[8] E. Strubell, A. Ganesh, and A. McCallum, “Energy and policy considerations for deep learning in NLP”, in Proceedings of ACL, 2019.

[9] E. Werner, The Problem of Charcoal Poaching and How Data Science Can Help to Stop It, Medium, June 2020. Accessed on: Sep. 4 2020. [Online]. Available:

[10] M. Costello. AI is a promising new tool for monitoring marine biodiversity, University of Aukland, July 2020. Accessed on: Sep. 8 2020. [Online]. Available:

[11] R. Vinuesa et al. “The role of artificial intelligence in achieving the Sustainable Development Goals”, Nature Communications, vol. 11, no. 1, pp. 1–10, 2020.


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