Valley International Journal Digital Library

VIJ Digital library
Articles

AI Hub: Idea to Innovative Service - An AI Service Hub for the Citizens of Bangladesh to Accelerate the Implementation of Smart Bangladesh

PDF
  • Rajib Mazumder,
  • Muhammad Anwar Hossain
Rajib Mazumder
Consultant, SDMGA Project, ICT Division,
Muhammad Anwar Hossain
Senior Maintenance Engineer, ICT Division,
Published in : International Journal of Scientific Research and Management (IJSRM) , Vol. 12 No. 05 (2024)

Published 2024-05-31

Keywords

  • AI Hub,
  • An AI Service

Copyright (c) 2024 Engr. Rajib Mazumber, Muhammad Anwar Hossain

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

In the contemporary digital era, the integration of Artificial Intelligence (AI) has become imperative for nations striving towards comprehensive development. Bangladesh, with its ambitious vision of achieving a Smart Bangladesh, stands at the forefront of leveraging AI technologies to enhance governance, improve public services, and foster economic growth. Recognizing the pivotal role of AI in this journey, the concept of an AI Service Hub emerges as a transformative initiative to empower citizens and expedite the realization of a technologically advanced society.

The AI Service Hub serves as a comprehensive ecosystem encompassing three key components: AI Repository, Capacity Building, and Collaborative Platform. The AI Repository acts as a centralized repository of AI models, algorithms, and applications tailored to address the specific challenges and opportunities prevalent in Bangladesh. It is continually updated with state-of-the-art innovations, ensuring accessibility to government agencies, businesses, academia, and civil society organizations.

Capacity Building programs offered by the AI Service Hub aim to upskill and reskill individuals across diverse domains. Through workshops, training sessions, and online resources, citizens are equipped with the requisite knowledge and skills to leverage AI effectively in their respective fields. The Collaborative Platform provided by the AI Service Hub serves as a space for stakeholders to converge, exchange ideas, and co-create AI-driven solutions. By fostering interdisciplinary collaboration and knowledge sharing, the platform catalyzes innovation and accelerates the implementation of AI initiatives across sectors.

The successful implementation of the AI Service Hub hinges on a multi-pronged strategy encompassing policy support, technological infrastructure, and stakeholder engagement. Policy support from the government is crucial for providing regulatory frameworks conducive to the proliferation of AI technologies. Technological infrastructure, including cloud computing resources and high-speed internet connectivity, ensures seamless access to AI tools and services. Stakeholder engagement, facilitated through collaborative partnerships, fosters innovation and collective problem-solving.

The AI Service Hub holds immense potential to catalyze socio-economic development and empower citizens across Bangladesh. By democratizing access to AI technologies and fostering collaboration, the hub accelerates the realization of a Smart Bangladesh, characterized by efficient governance, sustainable development, and enhanced quality of life for all citizens.

The vision of Smart Bangladesh 2041 aims to transform Bangladesh into a developed nation with a robust digital infrastructure, inclusive economic growth, and a high quality of life for its citizens. An AI Hub, designed as a centralized service platform, can significantly contribute to this transformation by accelerating the implementation of Smart Bangladesh initiatives. This paper explores the concept of the AI Hub, its potential impact, and strategic implementation to enhance citizen services, drive innovation, and foster economic development.

PDF

References

  1. Smart-Bangladesh-ICT-Master-Plan-2041-Draft-PDF-1 (1).pdf
  2. Babu, K. E. K. (2021). Artificial intelligence in Bangladesh, its applications in different sectors and relevant challenges for the government: An analysis. International Journal of Public Law and Policy, 7(4), 319-333.
  3. Babu, K. E. K. (2021). Artificial Intelligence, Its Applications in Different Sectors and Challenges: Bangladesh Context. Artificial Intelligence in Cyber Security: Impact and Implications: Security Challenges, Technical and Ethical Issues, Forensic Investigative Challenges, 103-119.
  4. Khan, M. S. U., Hasan, M. F., Islam, M. S., & Hassan, S. T. (2021). Artificial intelligenc e in the banking sector of Bangladesh: Applicability and the challenges. Roundtabl e discussion series-2021. Keynote Paper of Roundtable Discussion of BIBM, 6(2).
  5. Tushar, I. H. (2020). Industry revolution 4.0 and digital transformation-it’s implementation, opportunity and challenges in Bangladesh textile industry.
  6. Bokhari, S. A. A., & Myeong, S. (2022). Artificial Intelligence-Based Technological-Oriented Knowledge Management, Innovation, and E-Service Delivery in Smart Cities: Moderating Role of E-Governance. Applied Sciences, 12(17), 8732.
  7. Chanda, S. K., & Polly, A. Digitalization and Innovations in Health Care. DIGITALISATION & INNOVATIONS IN BUSINESS, 1.
  8. Shaikh, F. Z. (2023). Smart Rajshahi City: Challenges and Opportunities.
  9. Kuru, K., & Ansell, D. (2020). TCitySmartF: A comprehensive systematic framework for transforming cities into smart cities. IEEE Access, 8, 18615-18644.
  10. Bashir, M. O. I. (2022, February). Application Internet of Things (IoT) to calibrate with IMO 2050 Decarbonization Charters and Phase Out Greenhouse Gases from the Shipping Industry of Bangladesh. In OCEANS 2022-Chennai (pp. 1-5). IEEE.
  11. Bin Amin, S., Taghizadeh-Hesary, F., & Khan, F. (2022). Facilitating green digital finance in Bangladesh: Importance, prospects, and implications for meeting the SDGs. In Green Digital Finance and Sustainable Development Goals (pp. 143-165). Singapore: Springer Nature Singapore.
  12. Rahman, M., Kamal, M. M., Aydin, E., & Haque, A. U. (2022). Impact of Industry 4.0 drivers on the performance of the service sector: comparative study of cargo logistic firms in developed and developing regions. Production Planning & Control, 33(2-3), 228-243.
  13. Bashir, S., Dahlman, C., Kanehira, N., & Tilmes, K. (2021). The Converging Technology Revolution and Human Capital: Potential and Implications for South Asia. World Bank Publications.
  14. Syeed, M. M., Islam, M. A., & Fatema, K. (2020). Precision agriculture in Bangladesh: need and opportunities. Precis. Agric, 29, 6782-6800.
  15. Farzaneh, H., Malehmirchegini, L., Bejan, A., Afolabi, T., Mulumba, A., & Daka, P. P. (2021). Artificial intelligence evolution in smart buildings for energy efficiency. Applied Sciences, 11(2), 763.
  16. Amin, S. B., Taghizadeh-Hesary, F., Jannat, J., Khandaker, M. K., & Khan, F. (2022). Institutional and regulatory requirements for innovative Fintech market in Bangladesh: Why do they matter?. In Innovative Finance for Technological Progress (pp. 122-144). Routledge.
  17. Lv, Z., Chen, D., & Lv, H. (2022). Smart city construction and management by digital twins and BIM big data in COVID-19 scenario. ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 18(2s), 1-21.
  18. Hossain, I., Haque, A. K. M., & Ullah, S. M. (2024). Assessing sustainable waste management practices in Rajshahi City Corporation: an analysis for local government enhancement using IoT, AI, and Android technology. Environmental Science and Pollution Research, 1-19.
  19. ESCAP, U. (2022). Bangladesh startup ecosystem assessment report.
  20. Karim, M. R., & Hosen, S. (2023). Implementation Challenges of ICT in the Public Sector in Upazila Region of Bangladesh: An Empirical Study. Karim, Mohammad Rezaul, Hosen, Shamim, Implementation Challenges of ICT in the Public Sector in Upazila Region of Bangladesh: An Empirical Study (May 30, 2023).
  21. Nagesh, C., Chaganti, K. R., Chaganti, S., Khaleelullah, S., Naresh, P., & Hussan, M. (2023). Leveraging Machine Learning based Ensemble Time Series Prediction Model for Rainfall Using SVM, KNN and Advanced ARIMA+ E-GARCH. International Journal on Recent and Innovation Trends in Computing and Communication, 11(7s), 353-358.
  22. Jiang, B., Seif, M., Tandon, R., & Li, M. (2021). Context-aware local information privacy. IEEE Transactions on Information Forensics and Security, 16, 3694-3708.
  23. Surabhi, S. N. R. D., Mandala, V., & Shah, C. V. AI-Enabled Statistical Quality Control Techniques for Achieving Uniformity in Automobile Gap Control.
  24. Chaganti, K. R., Ramula, U. S., Sathyanarayana, C., Changala, R., Kirankumar, N., & Gupta, K. G. (2023, November). UI/UX Design for Online Learning Approach by Predictive Student Experience. In 2023 7th International Conference on Electronics, Communication and Aerospace Technology (ICECA) (pp. 794-799). IEEE.
  25. Jiang, B., Li, M., & Tandon, R. (2020). Local information privacy and its application to privacy-preserving data aggregation. IEEE Transactions on Dependable and Secure Computing, 19(3), 1918-1935.
  26. Mandala, V., & Surabhi, M. D. Intelligent Engines: Revolutionizing Manufacturing and Supply Chains with AI.
  27. Chaganti, K. R., & Chaganti, S. Deep Learning Based NLP and LSTM Models for Sentiment Classification of Consumer Tweets.
  28. Jiang, B., Li, M., & Tandon, R. (2018, May). Context-aware data aggregation with localized information privacy. In 2018 IEEE Conference on Communications and Network Security (CNS) (pp. 1-9). IEEE.
  29. Zhang, W., Jiang, B., Li, M., & Lin, X. (2022). Privacy-preserving aggregate mobility data release: An information-theoretic deep reinforcement learning approach. IEEE Transactions on Information Forensics and Security, 17, 849-864.
  30. Adeyeri, T. B. (2024). Enhancing Financial Analysis Through Artificial Intelligence: A Comprehensive Review. Journal of Science & Technology, 5(2), 102-120.
  31. Jiang, B., Li, M., & Tandon, R. (2019, May). Local information privacy with bounded prior. In ICC 2019-2019 IEEE International Conference on Communications (ICC) (pp. 1-7). IEEE.
  32. Adeyeri, T. B. (2024). Automating Accounting Processes: How AI is Streamlining Financial Reporting. Journal of Artificial Intelligence Research, 4(1), 72-90.
  33. Mandala, V., & Surabhi, S. N. R. D. Intelligent Systems for Vehicle Reliability and Safety: Exploring AI in Predictive Failure Analysis.
  34. Adeyeri, T. B. (2024). Blockchain and AI Synergy: Transforming Financial Transactions and Auditing. Blockchain Technology and Distributed Systems, 4(1), 24-44.
  35. Shah, C. V., Surabhi, S. N. R. D., & Mandala, V. ENHANCING DRIVER ALERTNESS USING COMPUTER VISION DETECTION IN AUTONOMOUS VEHICLE