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Knowledge-driven Analytics and Sensor Signal Processing in Human-centric Applications
Type of publication: Proceedings
Citation:
Booktitle: The 27th ACM International Conference on Information and Knowledge Management (CIKM)
Year: 2019
Month: November
Pages: 6
Abstract: Technology disruption through knowledge driven intelligent systems is increasingly controlling human life. Management of the present and future knowledge-driven artificial intelligence- based technologies is of highest importance to maximize its progressive influence to human life and human society. Life style diseases, social network affinity, impulsive financial decision, technology-abuse negatively affect our physical, emotional, social and mental health. Conversely, intelligent systems can bring positive impact on human life. This paper brings forward those positive applications and technologies as well as the path towards transformation of intelligent systems through some exemplary analysis that minimizes the negative impact. The push is to promote the development of human-centric intelligent technologies like precise and personalized medication and treatment plan, drug discovery of untreatable diseases, improved elderly care, minimizing private data theft, big data analytics for prediction of macro or micro economic condition, effective and fair trading practices, retail decision management, knowledge-driven energy and resource management, deep learning and artificial intelligence based applications for risk prediction and augmented human capability generation. The main focus of this paper is to demonstrate the knowledge-driven technologies, developments, applications for ensuring improvement of human quality of life. The impact would be micro-level, where human life is impacted in daily basis and at macro-level where human life would be impacted in long term that human life would be impacted in long term that eventually influences the betterment to human society.
Keywords:
Authors Ukil, Ariji
Jara, Antonio J
Marin, Leandro
Farserotu, John
Added by: []
Total mark: 0
Attachments
  • paper_w6_2.pdf
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