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Assessing the Impact of GeoAI in the World of Spatial Data and Energy Revolution

Assessing the Impact of GeoAI in the World of Spatial Data and Energy Revolution

Shradha Chavan, Preeti Mulay
Copyright: © 2023 |Pages: 24
ISBN13: 9781668493175|ISBN10: 1668493179|ISBN13 Softcover: 9781668493182|EISBN13: 9781668493199
DOI: 10.4018/978-1-6684-9317-5.ch008
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MLA

Chavan, Shradha, and Preeti Mulay. "Assessing the Impact of GeoAI in the World of Spatial Data and Energy Revolution." Risk Detection and Cyber Security for the Success of Contemporary Computing, edited by Raghvendra Kumar and Prasant Kumar Pattnaik, IGI Global, 2023, pp. 147-170. https://doi.org/10.4018/978-1-6684-9317-5.ch008

APA

Chavan, S. & Mulay, P. (2023). Assessing the Impact of GeoAI in the World of Spatial Data and Energy Revolution. In R. Kumar & P. Pattnaik (Eds.), Risk Detection and Cyber Security for the Success of Contemporary Computing (pp. 147-170). IGI Global. https://doi.org/10.4018/978-1-6684-9317-5.ch008

Chicago

Chavan, Shradha, and Preeti Mulay. "Assessing the Impact of GeoAI in the World of Spatial Data and Energy Revolution." In Risk Detection and Cyber Security for the Success of Contemporary Computing, edited by Raghvendra Kumar and Prasant Kumar Pattnaik, 147-170. Hershey, PA: IGI Global, 2023. https://doi.org/10.4018/978-1-6684-9317-5.ch008

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Abstract

Geospatial is going to be the absolute heart of making sense of trillions of bits of data that are going to be surveyed by big machines. The buzz word of the last 4-5 years has been artificial intelligence (AI) and is influencing every marketplace including GIS, healthcare, pollution, and the list is truly endless. It is the world of collaborative and multidisciplinary research where technology is applied in almost every domain and has proved extremely useful to end-users. The diversity of themes identified in this chapter can be grouped into the categories of renewable energy mapping: spatiotemporal analysis, and data mining. This chapter gives a comprehensive account of transformation from the classical ML clustering techniques with the potential of quantum clustering (QC) which can be applied or mapped to renewable energy solutions driven by use of GIS, or narrating the importance of GIS and quantum. This chapter highlights the relationship between GeoAI, cybersecurity, and quantum computing in the world of spatial data.

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