Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Call For Paper : Vol 11, Issue 03, March 2024

Call for Paper

Vol 11, Issue 03, March 2024

Indexing

Technological Intersection to the future of human life with Artificial Intelligence

Author : Shivaji Pawar 1 Dr Kamal Kr Sharma 2 Varsha Pawar 3

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Date of Publication :24th May 2019

Abstract: Artificial intelligence (AI) and machine learning are the two terms that are buzzing around the world and indeed make a significant impact on human life. It affects various aspects of human life attributes like healthcare, environmental, education, and E-commerce. Artificial intelligence is capable of doing things that were once impossible to imagine before the invention of computers. The basic motivation behind this paper is to study the impact of Artificial intelligence on human life in recent years. The first area where its impact is significant is the healthcare, in which we can satisfy all its attributes in terms of more responsive, cost-effective and fast in diagnosis. In order to empower education, equality is the major parameter but due to the economical and geographical barrier it is very difficult to provide equality in the education. But due to fast scientific development in AI and machine learning it has enabled to build great promise to the education sector in terms of digitally enabled classrooms, cloud-based content, EBooks etc. Today global environment condition is in bad shape due to the increase in population, pollution, and industrial waste, hence we require potential strategies and solution to tackle it. Artificial intelligence and sensor technology can provide a unique solution to the world environment in coming future. Area of E-commerce is almost covered by application of Artificial intelligence due to responsive, safe in use, , highly accurate and cost-effective techniques. Up to 2020, artificial intelligence can provide complete technical intersection to all the attributes of human life, but there are many issues that should be tackled by researcher and developer such as Bias, accuracy, and data transparency, legal and ethical issues.

Reference :

    1. Roll, I., & Wylie, R. (2016). Evolution and Revolution in Artificial Intelligence in Education. International Journal of Artificial Intelligence in Education, 26(2), 582–599. https://doi.org/10.1007/s40593-016-0110-
    2. Hastings, P., Hughes, S., & Britt, M. A. (2018). Active learning for improving machine learning of student explanatory essays. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10947 LNAI, pp. 140–153). Springer Verlag. https://doi.org/10.1007/978-3-319-93843-1_11
    3. Holstein, K., McLaren, B. M., & Aleven, V. (2018). Student learning benefits of a mixed-reality teacher awareness tool in AI-enhanced classrooms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10947 LNAI, pp. 154–168). Springer Verlag. https://doi.org/10.1007/978-3-319- 93843-1_12
    4. Holstein, K., Yu, Z., Sewall, J., Popescu, O., McLaren, B. M., & Aleven, V. (2018). Opening up an intelligent tutoring system development environment for extensible student modeling. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10947 LNAI, pp. 169–183). Springer Verlag. https://doi.org/10.1007/978-3-319- 93843-1_13.
    5. Thevenot, J., Lopez, M. B., & Hadid, A. (2018). A Survey on Computer Vision for Assistive Medical Diagnosis from Faces. IEEE Journal of Biomedical and Health Informatics, 22(5), 1497–1511. https://doi.org/10.1109/JBHI.2017.2754861
    6. Ram, S. Zhang, W., Williams, M., & Pengetnze, Y. (2015). Predicting Asthma-Related Emergency Department Visits Using Big Data. IEEE Journal of Biomedical and Health Informatics, 19(4), 1216–1223. https://doi.org/10.1109/JBHI.2015.2404829
    7. Pan, F., He, P., Liu, C., Li, T., Murray, A., & Zheng, D. (2017). Variation of the korotkoff stethoscope sounds during blood pressure measurement: Analysis using a convolutional neural network. IEEE Journal of Biomedical and Health Informatics, 21(6), 1593–1598. https://doi.org/10.1109/JBHI.2017.2703115
    8. Seol, K., Kim, Y. G., Lee, E., Seo, Y. D., & Baik, D. K. (2018). Privacy-preserving attribute-based access control model for the XML-based electronic health record system. IEEE Access, 6, 9114–9128. https://doi.org/10.1109/ACCESS.2018.2800288
    9. Anthimopoulos, M. M., Gianola, L., Scarnato, L., Diem, P., & Mougiakakou, S. G. (2014). A food recognition system for diabetic patients based on an optimized bag-of-features model. IEEE Journal of Biomedical and Health Informatics, 18(4), 1261–1271. https://doi.org/10.1109/JBHI.2014.2308928.
    10. Yap, M. H., Pons, G., Martí, J., Ganau, S., Sentís, M., Zwiggelaar, R., … Martí, R. (2018). Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks. IEEE Journal of Biomedical and Health Informatics, 22(4), 1218–1226. https://doi.org/10.1109/JBHI.2017.2731873
    11. Stern, D., Payer, C., Giuliani, N., & Urschler, M. (2018). Automatic Age Estimation and Majority Age Classification from Multi-Factorial MRI Data. IEEE Journal of Biomedical and Health Informatics. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/JBHI.2018.2869606
    12. Yap, M. H., Pons, G., Martí, J., Ganau, S., Sentís, M., Zwiggelaar, R., … Martí, R. (2018). Automated Breast Ultrasound Lesions Detection Using Convolutional Neural Networks. IEEE Journal of Biomedical and Health Informatics, 22(4), 1218–1226. https://doi.org/10.1109/JBHI.2017.2731873
    13. Stern, D., Payer, C., Giuliani, N., & Urschler, M. (2018). Automatic Age Estimation and Majority Age Classification from Multi-Factorial MRI Data. IEEE Journal of Biomedical and Health Informatics. Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/JBHI.2018.2869606
    14. Oktay, O., Bai, W., Guerrero, R., Rajchl, M., De Marvao, A., O’Regan, D. P., … Rueckert, D. (2017). Stratified Decision Forests for Accurate Anatomical Landmark Localization in Cardiac Images. IEEE Transactions on Medical Imaging, 36(1), 332–342. https://doi.org/10.1109/TMI.2016.2597270
    15. Miotto, R., Wang, F., Wang, S., Jiang, X., & Dudley, J. T. (2017). Deep learning for healthcare: review, opportunities, and challenges. Briefings in Bioinformatics. https://doi.org/10.1093/bib/bbx044
    16. You, C., Lu, J., Filev, Di., & Tsiotras, P. (2018). Highway Traffic Modeling and Decision Making for Autonomous Vehicle Using Reinforcement Learning. In IEEE Intelligent Vehicles Symposium, Proceedings (Vol. 2018-June, pp. 1227–1232). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/IVS.2018.8500675 Artificial intelligence for decision making in era of big data,evalution chanllenges and reseach agenda by yanging duan
    17. Cho, R. (2018). Artificial intelligence—A game changer for climate change and the environment. Retrieved from https://blogs.ei.columbia.edu/2018/06/05/artificialintelligence-climate-environment
    18. Quinn, J., Frias-Martinez, V., & Subramanian, L. (2017). Computational Sustainability and Artificial Intelligence in the Developing World. AI Magazine, 35(3), 36. https://doi.org/10.1609/aimag.v35i3.2529
    19. Buch, V. H., Ahmed, I., & Maruthappu, M. (2018). Artificial intelligence in medicine: current trends and future possibilities. British Journal of General Practice, 68(668), 143–144. https://doi.org/10.3399/bjgp18x695213
    20. Duan, Y., Edwards, J. S., & Dwivedi, Y. K. (2019). Artificial intelligence for decision making in the era of Big Data – evolution, challenges and research agenda. International Journal of Information Management, 48, 63–71. https://doi.org/10.1016/j.ijinfomgt.2019.01.021
    21. https://verily.com/projects/sensors/miniaturized-gcm
    22. https://www.medtronicdiabetes.com/products/sugar.iqdiabetes-assistant
    23. https://www.bigfootbiomedical.com/
    24. https://diabnext.com/
    25. http://dreamed-diabetes.com/
    26. http://hedia.dk/en/frontpage/
    27. http://typezero.com/
    28. http://www.xbird.io/

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