Financial Technology and Innovation

Submit Your Paper

Volume 2 , Issue 2 , PP: 48-56, 2023 | Cite this article as | XML | Html | PDF | Full Length Article

Revolutionizing Workplace Practices in Human Resource Management with IoT-Enabled Solutions and Analytics

Vibha Tiwari 1 *

  • 1 Centre for Artificial Intelligence Madhav Institute of Science and Technology, Gwalior, India - (vibhatiwari19@gmail.com)
  • Doi: https://doi.org/10.54216/FinTech-I.020205

    Received: February 28, 2023 Accepted: July 19, 2023
    Abstract

    A new age of workplace practices is about to begin, and this research delves into how HRM is undergoing a paradigm change because of analytics and solutions offered by the Internet of Things (IoT). Smart recruiting, targeted employee engagement, and ongoing performance monitoring are the main points of the suggested strategy. By using IoT devices, data is collected in real-time, allowing workers to get quick feedback and creating a work environment that is dynamic and adaptable. Decisions based on data simplify recruitment procedures, which improves talent identification and onboarding. Internet of Things (IoT) devices track employees' levels of stress and physical activity, enabling focused wellness programs. Predictive HR analytics can help with workforce planning by revealing trends that may be used for proactive decision-making. This method's innovative influence reaches into smart workplace design, which adapts to workers' evolving demands. By providing better accuracy, performance, and responsiveness than conventional HRM techniques, the suggested approach fosters an adaptive workplace that meets the changing demands of both people and the company.

    Keywords :

    Analytics , Enabled , Human Resource Management , IoT , Practices , Revolutionizing , Solutions , Workplace.

    References

    [1]       D. Acemoglu and P. Restrepo, "Robots and Jobs: Evidence from US Labor Markets," NBER Working Paper, NBER, Cambridge, 2017.

    [2]       S. Akter, S. F. Wamba, A. Gunasekaran, R. Dubey, and S. J. Childe, "How to improve firm performance using big data analytics capability and business strategy alignment?" International Journal of Production Economics, vol. 182, pp. 113–131, 2016.

    [3]       R. Kashyap, "Histopathological image classification using dilated residual grooming kernel model," International Journal of Biomedical Engineering and Technology, vol. 41, no. 3, p. 272, 2023. [Online]. Available: https://doi.org/10.1504/ijbet.2023.129819

    [4]       J. Kotwal, Dr. R. Kashyap, and Dr. S. Pathan, "Agricultural plant diseases identification: From traditional approach to deep learning," Materials Today: Proceedings, vol. 80, pp. 344–356, 2023. [Online]. Available: https://doi.org/10.1016/j.matpr.2023.02.370

    [5]       Edwin Ramirez-Asis, Romel Percy Melgarejo Bolivar, Leonid Alemán Gonzales, Sushovan Chaudhury, Ramgopal Kashyap, Walaa F. Alsanie, G. K. Viju, "A Lightweight Hybrid Dilated Ghost Model-Based Approach for the Prognosis of Breast Cancer," Computational Intelligence and Neuroscience, vol. 2022, Article ID 9325452, 10 pages, 2022. [Online]. Available: https://doi.org/10.1155/2022/9325452

    [6]       J. Alegre and R. Chiva, "Assessing the impact of organizational learning capability on product innovation performance: an empirical test," Technovation, vol. 28, no. 6, pp. 315–326, 2008.

    [7]       D. B. Arnet and V. Badrinarayanan, "Enhancing customer-needs-driven CRM strategies: core selling teams, knowledge management competence, and relationship marketing competence," Journal of Personal Selling & Sales Management, vol. 25, no. 4, pp. 329–343, 2005.

    [8]       M. Basadur and G. A. Gelade, "The role of knowledge management in the innovation process," Journal Compilation, vol. 15, no. 1, pp. 45–62, 2006.

    [9]       V. Roy et al., “Detection of sleep apnea through heart rate signal using Convolutional Neural Network,” International Journal of Pharmaceutical Research, vol. 12, no. 4, pp. 4829-4836, Oct-Dec 2020.

    [10]     R. Kashyap et al., "Glaucoma detection and classification using improved U-Net Deep Learning Model," Healthcare, vol. 10, no. 12, p. 2497, 2022. [Online]. Available: https://doi.org/10.3390/healthcare10122497

    [11]     Vinodkumar Mohanakurup, Syam Machinathu Parambil Gangadharan, Pallavi Goel, Devvret Verma, Sameer Alshehri, Ramgopal Kashyap, Baitullah Malakhil, "Breast Cancer Detection on Histopathological Images Using a Composite Dilated Backbone Network," Computational Intelligence and Neuroscience, vol. 2022, Article ID 8517706, 10 pages, 2022. [Online]. Available: https://doi.org/10.1155/2022/8517706

    [12]     A. Steegen, "Technology innovation in an IoT era," in 2015 Symposium on VLSI Circuits (VLSI Circuits), pp. C170–C171, Kyoto, Japan, June 2015.

    [13]     M. B. Alazzam, F. Alassery, and A. Almulihi, "Development of a mobile application for interaction between patients and doctors in rural populations," Mobile Information Systems, vol. 2021, Article ID 5006151, 8 pages, 2021.

    [14]     L. Bassi, "Raging debates in HR analytics," People & Strategy, vol. 34, pp. 14–18, 2011.

    [15]     C. Beath, I. Becerra-Fernandez, J. Ross, and J. Short, "Finding value in the information explosion," MIT Sloan Management Review, vol. 53, pp. 18–20, 2012.

    [16]     R. Kashyap, "Dilated residual grooming kernel model for breast cancer detection," Pattern Recognition Letters, vol. 159, pp. 157–164, 2022. [Online]. Available: https://doi.org/10.1016/j.patrec.2022.04.037

    [17]     S. Stalin, V. Roy, P. K. Shukla, A. Zaguia, M. M. Khan, P. K. Shukla, A. Jain, "A Machine Learning-Based Big EEG Data Artiact Detection and Wavelet-Based Removal: An Empirical Approach," Mathematical Problems in Engineering, vol. 2021, Article ID 2942808, 11 pages, 2021. [Online]. Available: https://doi.org/10.1155/2021/2942808

    [18]     C. M. Christensen, M. E. Raynor, and S. D. Anthony, "Six keys to creating new growth business," Harvard Management Update, vol. 8, no. 1, 2003.

    Cite This Article As :
    Tiwari, Vibha. Revolutionizing Workplace Practices in Human Resource Management with IoT-Enabled Solutions and Analytics. Financial Technology and Innovation, vol. , no. , 2023, pp. 48-56. DOI: https://doi.org/10.54216/FinTech-I.020205
    Tiwari, V. (2023). Revolutionizing Workplace Practices in Human Resource Management with IoT-Enabled Solutions and Analytics. Financial Technology and Innovation, (), 48-56. DOI: https://doi.org/10.54216/FinTech-I.020205
    Tiwari, Vibha. Revolutionizing Workplace Practices in Human Resource Management with IoT-Enabled Solutions and Analytics. Financial Technology and Innovation , no. (2023): 48-56. DOI: https://doi.org/10.54216/FinTech-I.020205
    Tiwari, V. (2023) . Revolutionizing Workplace Practices in Human Resource Management with IoT-Enabled Solutions and Analytics. Financial Technology and Innovation , () , 48-56 . DOI: https://doi.org/10.54216/FinTech-I.020205
    Tiwari V. [2023]. Revolutionizing Workplace Practices in Human Resource Management with IoT-Enabled Solutions and Analytics. Financial Technology and Innovation. (): 48-56. DOI: https://doi.org/10.54216/FinTech-I.020205
    Tiwari, V. "Revolutionizing Workplace Practices in Human Resource Management with IoT-Enabled Solutions and Analytics," Financial Technology and Innovation, vol. , no. , pp. 48-56, 2023. DOI: https://doi.org/10.54216/FinTech-I.020205