Abstract
The structure of the Society 5.0 involves a methodology that would be more human-focused. The critical elements of the program incorporate adjusting the financial progression of the country with the global methodologies resolving the social issues with the advancement of a framework inside which the internet and actual space would be coordinated. This chapter discusses the use of smart Big Data analytics, Artificial Intelligence, and smart real-time analytics that will impact and resolve numerous challenges faced in sectors such as Healthcare, Education, Agriculture, and Smart city in Society 5.0. In this book chapter, the author has explained firstly about digitizing, joining, and adequately utilizing smart Big Data analytics, medical care associations going from single-doctor workplaces to online care and immediate self-care will improve the wellness of an individual. Secondly, During online examination, the activities such as question navigation, Internet Protocol (IP), answer responses, exam access login, and logout tracking can be noted and all these analyses will help to improve the overall quality of online examination. Consequently, explained the Artificial Intelligence and smart Big Data analytics for perspectives like meteorological information, crop-development information, economic situations, food patterns, and needs which will help in quality of agriculture produce and market rate of crop. Last but not the least brief explanation about Sensors, AI, and robots that will be utilized to assess and keep up with streets, extensions, passages, dams, and many more are used to minimize the accidents and maintain and improve the quality is mentioned.
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Siddesh, G.M., Kulkarni, A.S. (2022). Introduction to Smart Big Data Analytics and Smart Real-Time Analytics in Society 5.0. In: Srinivasa, K.G., Siddesh, G.M., Manisekhar, S.R. (eds) Society 5.0: Smart Future Towards Enhancing the Quality of Society. Advances in Sustainability Science and Technology. Springer, Singapore. https://doi.org/10.1007/978-981-19-2161-2_3
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DOI: https://doi.org/10.1007/978-981-19-2161-2_3
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