Computational sustainability

Computational sustainability is an emerging field that attempts to balance societal, economic, and environmental resources for the future well-being of humanity using methods from mathematics, computer science, and information science fields.[1][2] Sustainability in this context refers to the world's ability to sustain biological, social, and environmental systems in the long term. Using the power of computers to process large quantities of information, decision making algorithms allocate resources based on real-time information.[3] Applications advanced by this field are widespread across various areas. For example, artificial intelligence and machine learning techniques are created to promote long-term biodiversity conservation and species protection.[4][5] Smart grids implement renewable resources and storage capabilities to control the production and expenditure of energy.[6] Intelligent transportation system technologies can analyze road conditions and relay information to drivers so they can make smarter, more environmentally-beneficial decisions based on real-time traffic information.[7][8]

  1. ^ "www.computational-sustainability.org". www.computational-sustainability.org. Retrieved 2016-03-25.
  2. ^ Gomes, Carla; Dietterich, Thomas; Barrett, Christopher; Conrad, Jon; Dilkina, Bistra; Ermon, Stefano; Fang, Fei; Farnsworth, Andrew; Fern, Alan; Fern, Xiaoli; Fink, Daniel; Fisher, Douglas; Flecker, Alexander; Freund, Daniel; Fuller, Angela (2019-08-21). "Computational sustainability: computing for a better world and a sustainable future". Communications of the ACM. 62 (9): 56–65. doi:10.1145/3339399. ISSN 0001-0782.
  3. ^ Frenkel, Karen A. (1 September 2009). "Computer Science meets environmental science". Communications of the ACM. 52 (9): 23. doi:10.1145/1562164.1562174.
  4. ^ Cite error: The named reference :3 was invoked but never defined (see the help page).
  5. ^ Cite error: The named reference :4 was invoked but never defined (see the help page).
  6. ^ "CompSustNet: Home". www.compsust.net. Retrieved 2016-03-25.
  7. ^ Guerrero-ibanez, J. A.; Zeadally, S.; Contreras-Castillo, J. (2015-12-01). "Integration challenges of intelligent transportation systems with connected vehicle, cloud computing, and internet of things technologies". IEEE Wireless Communications. 22 (6): 122–128. doi:10.1109/MWC.2015.7368833. ISSN 1536-1284. S2CID 23948355.
  8. ^ Barth, Matthew J.; Wu, Guoyuan; Boriboonsomsin, Kanok (2015-09-01). "Intelligent Transportation Systems and Greenhouse Gas Reductions". Current Sustainable/Renewable Energy Reports. 2 (3): 90–97. doi:10.1007/s40518-015-0032-y. ISSN 2196-3010.