Abera YB, Naudet Y, Panetto H. A new paradigm and meta-model for cyber-physical-social systems. IFAC-PapersOnLine. 2020;53(2):10949–54.
Alsamhi SH, Hawbani A, Kumar S, Gravina R, Fortino G, Curry E. Metaverse-driven drone edge intelligence in B5G: a conceptual framework for empowering CPSS. In: 2023 IEEE International conference on systems, man, and cybernetics (SMC). IEEE; 2023. pp. 1289–94.
Teichmann M, Motus L. Situation awareness, mental models and understanding. In: 2021 IEEE Conference on Cognitive and Computational Aspects of Situation Management (CogSIMA). IEEE. 2021, pp. 86–93.
Neshenko N, Bou-Harb E, Furht B. Smart Cities: Cyber Situational Awareness to Support Decision Making. Springer Nature. 2022.
Renz A, Vladova G. Reinvigorating the discourse on human-centered artificial intelligence in educational technologies. Technol Innov Manag Rev. 2021;11(5).
An D, Pan Z, Gao X, Li S, Yin L, Li T. stohmcharts: A modeling framework for quantitative performance evaluation of cyber-physical-social systems. IEEE Access. 2023.
Wang F-Y, Tang Y, Werbos PJ. Guest editorial: cyber-physical-social intelligence: toward metaverse-based smart societies of 6i and 6s. IEEE Trans Syst Man Cybern Syst. 2023;53(4):2018–24.
Yin L, He X. Artificial emotional deep q learning for real-time smart voltage control of cyber-physical social power systems. Energy. 2023;273: 127232.
Shaji B, Singh R, Nisha K. High-performance fuzzy optimized deep convolutional neural network model for big data classification based on the social internet of things. J Supercomput. 2023, pp. 1–29.
Assem HD, Nartey L, Appiah E, Aidoo JK. A review of students’ academic performance in physics: Attitude, instructional methods, misconceptions and teachers qualification. Eur J Educ Pedagogy. 2023;4(1):84–92.
Abdulgalimov D, Kirkham R, Nicholson J, Bartindale T, Olivier P. Ourstrategy: Employee voice in transnational strategy development. In: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 2023, pp. 1–17.
Rahwan I, Cebrian M, Obradovich N, Bongard J, Bonnefon J-F, Breazeal C, Crandall JW, Christakis NA, Couzin ID, Jackson MO, et al. Machine behaviour. Nature. 2019;568(7753):477–86.
Zhang M, Zhao H, Zheng R, Wu Q, Wei W. Cognitive internet of things: concepts and application example. Int J Comput Sci Issues (IJCSI). 2012;9(6):151.
Shneiderman B, Plaisant C, Cohen MS, Jacobs S, Elmqvist N, Diakopoulos N. Designing the user interface: strategies for effective human-computer interaction. Pearson. 2016.
Russell S. Human compatible: Artificial intelligence and the problem of control. Penguin. 2019.
Williams O. Towards human-centred explainable ai: A systematic literature review. Master’s Thesis. 2021.
Liu Z, Yang D-S, Wen D, Zhang W-M, Mao W. Cyber-physical-social systems for command and control. IEEE Intell Syst. 2011;26(4):92–6.
Nitti M, Atzori L, Cvijikj IP, Network navigability in the social internet of things. In: IEEE world forum on internet of things (WF-IoT). IEEE. 2014;2014:405–10.
Ning H, Liu H, et al. Cyber-physical-social based security architecture for future internet of things. Adv Internet Things. 2012;2(01):1.
Endsley MR. Situation awareness misconceptions and misunderstandings. J Cogn Eng Decis Mak. 2015;9(1):4–32.
Sarter NB, Woods DD. Situation awareness: A critical but ill-defined phenomenon. Int J Aviat Psychol. 1991;1(1):45–57.
Schmager S, Pappas I, Vassilakopoulou P. Defining human-centered AI: a comprehensive review of HCAI literature. Proceedings of the Mediterranean Conference on Information Systems; 2023. https://www.taylorfrancis.com/chapters/edit/10.4324/9781315087924-8/situational-awareness-rating-technique-sart-development-tool-aircrew-systems-design-taylor.
Powell A, Piccoli G, Ives B. Virtual teams: a review of current literature and directions for future research. ACM SIGMIS Database: DATABASE Adv Inf Syst. 2004;35(1):6–36.
Bicchieri C, Duffy J, Tolle G. Trust among strangers. Philos Sci. 2004;71(3):286–319.
Article MathSciNet Google Scholar
Margetis G, Ntoa S, Antona MC. Human-centered design of artificial intelligence. Handbook of human factors and ergonomics: Stephanidis; 2021. p. 1085–106.
Dumitrache I, Sacala IS, Moisescu MA, Caramihai SI. A conceptual framework for modeling and design of cyber-physical systems. Stud Inform Control. 2017;26(3):325–34.
Chen S, Jian Z, Huang Y, Chen Y, Zhou Z, Zheng N. Autonomous driving: cognitive construction and situation understanding. SCIENCE CHINA Inf Sci. 2019;62:1–27.
Dhirani LL, Mukhtiar N, Chowdhry BS, Newe T. Ethical dilemmas and privacy issues in emerging technologies: A review. Sensors. 2023;23(3):1151.
E. Puiutta and E. M. Veith, Explainable reinforcement learning: A survey, in Machine Learning and Knowledge Extraction: 4th IFIP TC 5, TC 12, WG 8.4, WG 8.9, WG 12.9 International Cross-Domain Conference, CD-MAKE. Dublin, Ireland, August 25–28. Proceedings 4. Springer. 2020;2020(2020):77–95.
Napoleone A, Macchi M, Pozzetti A. A review on the characteristics of cyber-physical systems for the future smart factories. J Manuf Syst. 2020;54:305–35.
Olowononi FO, Rawat DB, Liu C. Resilient machine learning for networked cyber physical systems: A survey for machine learning security to securing machine learning for cps. IEEE Commun Surv Tutor. 2020;23(1):524–52.
Bingley WJ, Curtis C, Lockey S, Bialkowski A, Gillespie N, Haslam SA, Ko RK, Steffens N, Wiles J, Worthy P. Where is the human in human-centered ai? insights from developer priorities and user experiences. Comput Hum Behav. 2023;141: 107617.
Russell S. Human-compatible artificial intelligence. Human-like machine intelligence, 2021, pp. 3–23.
Miller T. Explanation in artificial intelligence: Insights from the social sciences. Artif Intell. 2019;267:1–38.
Article MathSciNet Google Scholar
Doshi-Velez F, Kim B. Towards a rigorous science of interpretable machine learning, 2017. arXiv preprint arXiv:1702.08608.
D’Aniello G, Gravina R, Gaeta M, Fortino G. Situation-aware sensor-based wearable computing systems: A reference architecture-driven review. IEEE Sens J. 2022.
Grigsby S, Crossman J, Purman B, Frederiksen R, Schmorrow D. Dynamic task sharing within human-uxs teams: computational situation awareness, in Augmented Cognition. Enhancing Cognition and Behavior in Complex Human Environments: 11th International Conference, AC. Held as Part of HCI International. Vancouver, BC, Canada, July 9–14, 2017, Proceedings, Part II 11. Springer. 2017;2017(2017):443–60.
Rahwan I. Society-in-the-loop: programming the algorithmic social contract. Ethics Inf Technol. 2018;20(1):5–14.
Doshi-Velez F, Kim B. Towards a rigorous science of interpretable machine learning 2017. arXiv preprint arXiv:1702.08608.
Norman D. The design of everyday things: Revised and expanded edition. Basic books. 2013.
Endsley MR. Toward a theory of situation awareness in dynamic systems. Hum Factors. 1995;37(1):32–64.
Bisdikian C, Kaplan LM, Srivastava MB, Thornley DJ, Verma D, Young RI. Building principles for a quality of information specification for sensor information. In: 2009 12th International Conference on Information Fusion. IEEE. 2009, pp. 1370–1377.
Norman D. The design of everyday things: Revised and expanded edition. Basic books, 2013.
Amershi S, Cakmak M, Knox WB, Kulesza T. Power to the people: The role of humans in interactive machine learning. AI Mag. 2014;35(4):105–20.
Vainauskienė V, Vaitkienė R. Enablers of patient knowledge empowerment for self-management of chronic disease: an integrative review. Int J Environ Res Public Health. 2021;18(5):2247.
Colizzi M, Lasalvia A, Ruggeri M. Prevention and early intervention in youth mental health: is it time for a multidisciplinary and trans-diagnostic model for care? Int J Ment Heal Syst. 2020;14(1):1–14.
Roy S, LaFramboise WA, Nikiforov YE, Nikiforova MN, Routbort MJ, Pfeifer J, Nagarajan R, Carter AB, Pantanowitz L. Next-generation sequencing informatics: challenges and strategies for implementation in a clinical environment. Arch Path Lab Med. 2016;140(9):958–75.
Mostafa N, Ramadan HSM, Elfarouk O. Renewable energy management in smart grids by using big data analytics and machine learning. Mach Learn Appl. 2022;9: 100363.
Al-Shetwi AQ. Sustainable development of renewable energy integrated power sector: Trends, environmental impacts, and recent challenges. Sci Total Environ. 2022, p. 153645.
Kabeyi MJB, Olanrewaju OA. Sustainable energy transition for renewable and low carbon grid electricity generation and supply. Frontiers in Energy Research. 2022;9:1032.
Mousavi S, Gheibi M, Wacławek S, Smith NR, Hajiaghaei-Keshteli M, Behzadian K. Low-energy residential building optimisation for energy and comfort enhancement in semi-arid climate conditions. Energy Convers Manage. 2023;291: 117264.
Karimi H, Adibhesami MA, Bazazzadeh H, Movafagh S. Green buildings: Human-centered and energy efficiency optimization strategies. Energies. 2023;16(9):3681.
Steen R, Haakonsen G, Steiro TJ. Patterns of learning: A systemic analysis of emergency response operations in the north sea through the lens of resilience engineering. Infrastructures. 2023;8(2):16.
Damaševičius R, Bacanin N, Misra S. From sensors to safety: Internet of emergency services (ioes) for emergency response and disaster management. J Sens Actuator Netw. 2023;12(3):41.
Seppänen H, Mäkelä J, Luokkala P, Virrantaus K. Developing shared situational awareness for emergency management. Saf Sci. 2013;55:1–9.
Ross KL, Bing CM. Emergency management: expanding the disaster plan. Home Healthcare Now. 2007;25(6):370–7.
Munir A, Aved A, Blasch E. Situational awareness: techniques, challenges, and prospects. AI. 2022;3(1):55–77.
Wang J, Ma Y, Zhang L, Gao RX, Wu D. Deep learning for smart manufacturing: Methods and applications. J Manuf Syst. 2018;48:144–56.
Walter S. Ai impacts on supply chain performance: a manufacturing use case study. Discov Artif Intell. 2023;3(1):18.
Li S, Zheng P, Liu S, Wang Z, Wang XV, Zheng L, Wang L. Proactive human-robot collaboration: Mutual-cognitive, predictable, and self-organising perspectives. Robot Comput-Integr Manuf. 2023;81: 102510.
Mukherjee D, Gupta K, Chang LH, Najjaran H. A survey of robot learning strategies for human-robot collaboration in industrial settings. Robot Comput-Integr Manuf. 2022;73: 102231.
Alcaraz C, Cazorla L, Lopez J. Cyber-physical systems for wide-area situational awareness. In: Cyber-Physical Systems. Elsevier. 2017, pp. 305–317.
Ozmen Garibay O, Winslow B, Andolina S, Antona M, Bodenschatz A, Coursaris C, Falco G, Fiore SM, Garibay I, Grieman K, et al. Six human-centered artificial intelligence grand challenges. Int J Hum–Comput Interact, 2023, pp. 1–47.
Rahman S, Kim H, Zhang D, Hruschka E, Kandogan E. Towards multifaceted human-centered ai. 2023. arXiv preprint arXiv:2301.03656.
Joo H, Ahmed SH, Lim Y. Traffic signal control for smart cities using reinforcement learning. Comput Commun. 2020;154:324–30.
Nastjuk I, Herrenkind B, Marrone M, Brendel AB, Kolbe LM. What drives the acceptance of autonomous driving? an investigation of acceptance factors from an end-user’s perspective. Technol Forecast Soc Chang. 2020;161: 120319.
Lim HSM, Taeihagh A. Autonomous vehicles for smart and sustainable cities: An in-depth exploration of privacy and cybersecurity implications. Energies. 2018;11(5):1062.
Taylor RM. Situational awareness rating technique (sart): The development of a tool for aircrew systems design, in Situational awareness. Routledge, 2017, pp. 111–128.
Strater LD, Endsley MR, Pleban RJ, Matthews MD. Measures of platoon leader situation awareness in virtual decision-making exercises. US Army Research Institute for the Behavioral and Social Sciences, 2001.
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