Enhancing Government Initiatives: The Impact of Multimodal Artificial Intelligence in Revolutionizing Public Services

By: Vajratiya Vajrobol, International Center for AI and Cyber Security Research and Innovations (CCRI), Asia University, Taiwan, vvajratiya@gmail.com

In the rapidly evolving digital age, governments throughout the world are progressively using sophisticated technology to improve public services, optimize operations, and assure efficient governance. One revolutionary technology that is gaining attention is Multimodal Artificial Intelligence (AI), which combines several AI approaches to analyze and understand many forms of input. This article examines the possible uses and advantages of Multimodal AI in government sectors, which can lead to improved efficiency, transparency, and citizen-focused services.

1. Improving Public Safety and Security

Implementing multimodal AI can greatly improve public safety efforts. Governments may get comprehensive situational awareness by consolidating data from several sources, such as security cameras, social media, and sensor networks. The integration of advanced visual and textual analysis allows for the instant recognition of possible hazards, identification of irregular patterns, and swift response to various scenarios. This not only ensures the safeguarding of persons but also enables proactive measures to prevent potential security hazards [1].

2. Infrastructure and management of intelligent urban areas

Authorities are gradually assigning money to smart city initiatives in order to improve urban living conditions. The use of multimodal AI allows for the examination of many data sources, including traffic cameras, environmental sensors, and social media, in order to improve municipal infrastructure and services. Utilizing multimodal AI allows for the creation of urban environments that are data-driven, responsive, and encourage sustainability, thereby enhancing the overall quality of life for residents. It includes several applications such as smart traffic management and effective waste disposal [2-4].

3. Enhancing the efficiency of healthcare services

Healthcare providers can benefit from the use of Multimodal AI to improve patient care and efficiently allocate resources. The integration of data obtained from electronic health records, medical imaging, and patient interactions allows for more precise diagnosis and personalized treatment strategies. The utilization of natural language processing enables the examination of medical literature and patient data, therefore streamlining research and guaranteeing the use of evidence-based decision-making. Governments can utilize Multimodal AI to establish a healthcare system that exhibits greater resilience and adaptability [5-6].

4. Optimizing Administrative Procedures

Governments oversee huge amounts of data across several agencies. Implementing multimodal AI may automate and enhance administrative tasks, reducing the burden on government employees and enhancing overall efficiency. By integrating optical character recognition (OCR), speech recognition, and language comprehension, the processing of documents and interactions may be expedited, leading to faster decision-making and improved service delivery [7].

5. Involvement of Citizens and Ease of Access

Multi-modal AI technologies improve the accessibility and user-friendliness of government services. Virtual assistants and chatbots, utilizing natural language processing, provide individuals with instant access to information and assistance. Furthermore, Multimodal AI fosters inclusivity by allowing several modes of engagement, such as speech, text, and images, to cater to the varying needs of individuals. This approach enhances civic engagement and strengthens the bond between the government and its constituents [8].

In conclusion

As governments adopt the era of digital transformation, Multimodal AI arises as a fundamental technology, providing unparalleled possibilities to modernize public services. The applications of Multimodal AI in government are many and revolutionary, ranging from improving security and safety to optimizing healthcare and reducing administrative operations. Through the utilization of varied data sources and sophisticated artificial intelligence methods, governments may construct systems that are more adaptable, open, and focused on the needs of citizens. This will ultimately shape a future where public services are more intelligent, effective, and available to everyone.

References

  1. Mendonça, M., Moreira, B., Coelho, J., Cacho, N., Lopes, F., Cavalcante, E., … & Moura, B. (2016, September). Improving public safety at fingertips: A smart city experience. In 2016 IEEE International Smart Cities Conference (ISC2) (pp. 1-6). IEEE.
  2. Chen, Q., Wang, W., Wu, F., De, S., Wang, R., Zhang, B., & Huang, X. (2019). A survey on an emerging area: Deep learning for smart city data. IEEE Transactions on Emerging Topics in Computational Intelligence, 3(5), 392-410.
  3. Lemonde, C., Arsenio, E., & Henriques, R. (2021). Integrative analysis of multimodal traffic data: addressing open challenges using big data analytics in the city of Lisbon. European transport research review, 13, 1-22.
  4. Raich, K., Kathrein, R., Erharter, M., & Döller, M. (2020, December). Spatial extension model for multimodal traffic management. In Proceedings of the 2020 4th International Conference on Vision, Image and Signal Processing (pp. 1-6).
  5. Cai, Q., Wang, H., Li, Z., & Liu, X. (2019). A survey on multimodal data-driven smart healthcare systems: approaches and applications. IEEE Access, 7, 133583-133599.
  6. Shaik, T., Tao, X., Li, L., Xie, H., & Velásquez, J. D. (2023). A survey of multimodal information fusion for smart healthcare: Mapping the journey from data to wisdom. Information Fusion, 102040.
  7. Samonte, M. J. C., Bejar, A. M. L., Bien, H. C. L., & Cruz, A. M. D. (2019, October). Senior citizen social pension management system using optical character recognition. In 2019 International Conference on Information and Communication Technology Convergence (ICTC) (pp. 456-460). IEEE.
  8. Nirala, K. K., Singh, N. K., & Purani, V. S. (2022). A survey on providing customer and public administration based services using AI: chatbot. Multimedia Tools and Applications, 81(16), 22215-22246.
  9. Wang, L., Li, L., Li, J., Li, J., Gupta, B. B., & Liu, X. (2018). Compressive sensing of medical images with confidentially homomorphic aggregations. IEEE Internet of Things Journal, 6(2), 1402-1409.
  10. Stergiou, C. L., Psannis, K. E., & Gupta, B. B. (2021). InFeMo: flexible big data management through a federated cloud system. ACM Transactions on Internet Technology (TOIT), 22(2), 1-22.
  11. Gupta, B. B., Perez, G. M., Agrawal, D. P., & Gupta, D. (2020). Handbook of computer networks and cyber security. Springer, 10, 978-3.
  12. Bhushan, K., & Gupta, B. B. (2017). Security challenges in cloud computing: state-of-art. International Journal of Big Data Intelligence, 4(2), 81-107.

Cite As:

Vajrobol V. (2024) Enhancing Government Initiatives: The Impact of Multimodal Artificial Intelligence in Revolutionizing Public Services, Insights2Techinfo, pp.1

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