Cognitive Computing: Architecture, Technologies and Intelligent Applications
Open accessAbstract
With the development of network-enabled sensors and artificial intelligence algorithms, various human-centered smart systems are proposed to provide services with higher quality, such as smart healthcare, affective interaction, and autonomous driving. Considering cognitive computing is an indispensable technology to develop these smart systems, this paper proposes human-centered computing assisted by cognitive computing and cloud computing. First, we provide a comprehensive investigation of cognitive computing, including its evolution from knowledge discovery, cognitive science, and big data. Then, the system architecture of cognitive computing is proposed, which consists of three critical technologies, i.e., networking (e.g., Internet of Things), analytics (e.g., reinforcement learning and deep learning), and cloud computing. Finally, it describes the representative applications of human-centered cognitive computing, including robot technology, emotional communication system, and medical cognitive system.
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Cognitive AI combines insights from cognitive science and AI and studies processing and transmission of information within the human brain, addressing mental abilities such as language, perception, memory, and reasoning.
“Cognitive AI combines insights from cognitive science and AI. It is an interdisciplinary field that studies the processing and transmission of information within the human brain, addressing mental abilities of human beings such as language, perception, memory, and reasoning [10, 24].”
From CAIM: Development and Evaluation of a Cognitive AI Memory Framework for Long-Term Interaction with Intelligent Agents (2026) · cites this paper as [10]
According to Chen et al., the cognitive process of humans is divided into two stages: becoming aware of external information as input and transmitting and processing the input to the brain for storage, analysis, and learning.
“According to Chen et al. [10], the cognitive process of humans is divided into two stages: 1) becoming aware of external information as an input and 2) transmitting and processing the input to the brain for storage, analysis, and learning.”
From CAIM: Development and Evaluation of a Cognitive AI Memory Framework for Long-Term Interaction with Intelligent Agents (2026) · cites this paper as [10]
Cites
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Self-citationHuman-level concept learning through probabilistic program induction
Lake, B. M., Salakhutdinov, R., & Tenenbaum, J. B. (2015) · Science · doi:10.1126/science.aab3050 · Cited by 2,817 · see citing works
Building high-level features using large scale unsupervised learning
Le, Q. V. (2013) · 2013 IEEE International Conference on Acoustics, Speech and Signal Processing · doi:10.1109/icassp.2013.6639343 · Cited by 1,695 · see citing works
IBM Watson: How Cognitive Computing Can Be Applied to Big Data Challenges in Life Sciences Research
Chen, Y., Elenee Argentinis, J., & Weber, G. (2016) · Clinical Therapeutics · doi:10.1016/j.clinthera.2015.12.001 · Cited by 466 · see citing works
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The emerging role of cognitive computing in healthcare: a systematic literature review
Behera, R. K., Bala, P. K., & Dhir, A. (2019) · International Journal of Medical Informatics · doi:10.1016/j.ijmedinf.2019.04.024 · Cited by 193 · see citing works
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Privacy-aware service placement for mobile edge computing via federated learning
Qian, Y., Hu, L., Chen, J., Guan, X., Hassan, M. M., & Alelaiwi, A. (2019) · Information Sciences · doi:10.1016/j.ins.2019.07.069 · Cited by 122 · see citing works
CIoT-Net: a scalable cognitive IoT based smart city network architecture
Park, J.-H., Salim, M. M., Jo, J. H., Sicato, J. C. S., Rathore, S., & Park, J. H. (2019) · Human-centric Computing and Information Sciences · doi:10.1186/s13673-019-0190-9 · Cited by 121 · see citing works
Westhäußer, R., Minker, W., & Zepf, S. (2026) · Proceedings of the 31st International Conference on Intelligent User Interfaces · doi:10.1145/3742413.3789222 · Cited by 1 · see citing works
- Authors
- Chen, M., Herrera, F., & Hwang, K.
- Affiliations
- Wuhan National Laboratory for Optoelectronics (CN)
- Universidad de Granada (ES)
- University of Southern California (US)
- Venue
- IEEE Access
- Published
- 2018
- Volume
- 6
- Pages
- 19774-19783
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W2799126587
- Cited by
- 242
- References
- 4
- Citations by year
- 2026: 8 · 2025: 23 · 2024: 32 · 2023: 24 · 2022: 41 · 2021: 41 · 2020: 18 · 2019: 40 · 2018: 15
- FWCI
- 15.95
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion)
- Institutional Repository of the University of Granada (University of Granada) (submittedVersion, cc-by-nc-nd)
- LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) (submittedVersion, cc-by-nc-nd)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Natural Science Foundation of China (U1705261)
- Director Fund of WNLO
- FEDER Funds
- Spanish Ministry of Science and Technology (TIN2017-89517-P)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Cognitive Computing and Networks
- Physical Sciences › Computer Science › Information Systems › Internet of Things and AI
- Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
- Keywords
- cognitive computing, human-centered computing, Internet of Things, cloud computing, reinforcement learning, deep learning, smart healthcare, emotional interaction, autonomous driving, robotics, knowledge discovery, big data
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