The integration of Artificial Intelligence (AI) and smart technologies into safety management is a pivotal aspect of the Fourth Industrial Revolution or Industry 4.0. This study conducts a systematic literature review to identify and analyze how AI and smart technologies enhance safety management across various sectors within the Safety 4.0 paradigm. Focusing on peer-reviewed journal articles that explicitly mention “Smart”, “AI”, or “Artificial Intelligence” in their titles, the research examines key safety management factors, such as accident prevention, risk management, real-time monitoring, and ethical implementation, across sectors, including construction, industrial safety, disaster and public safety, transport and logistics, energy and power, health, smart home and living, and other diverse industries. AI-driven solutions, such as predictive analytics, machine learning algorithms, IoT sensor integration, and digital twin models, are shown to proactively identify and mitigate potential hazards, optimize energy consumption, and enhance operational efficiency. For instance, in the energy and power sector, intelligent gas meters and automated fire suppression systems manage gas-related risks effectively, while in the health sector, AI-powered health monitoring devices and mental health support applications improve patient and worker safety. The analysis reveals a significant trend towards shifting from reactive to proactive safety management, facilitated by the convergence of AI with IoT and Big Data analytics. Additionally, ethical considerations and data privacy emerge as critical challenges in the adoption of AI technologies. The study highlights the transformative role of AI in enhancing safety protocols, reducing accident rates, and improving overall safety outcomes across industries. It underscores the need for standardized protocols, robust AI governance frameworks, and interdisciplinary research to address existing challenges and maximize the benefits of AI in safety management. Future research directions include developing explainable AI models, enhancing human–AI collaboration, and fostering global standardization to ensure the responsible and effective implementation of AI-driven safety solutions.

Objective: We investigated the changes in circulating irisin levels after community-based exercise and the association of these levels with improvements in muscle strength, cardiorespiratory endurance, and body composition in people with ischemic stroke.Methods: Twenty participants were randomly assigned to either a control or an exercise group. The community-based exercise program (CEP) consisted of 8 weeks of 1 h sessions for 3 days a week. Irisin levels, muscle strength, cardiorespiratory endurance, and body composition were assessed before and after the intervention.Results: Significant improvements were observed in the leg and trunk strength, peak oxygen consumption values, and body composition of the exercise group compared with the control group. In addition, circulating irisin levels were observed to have increased in the exercise group, positively correlated with muscle strength and cardiorespiratory endurance.Conclusion: CEP might be an effective intervention to increase irisin levels and prevent a stroke-related decline in muscle function.

Background: Respiratory disorders result in rehospitalization and premature death of patients with cervical spinal cord injuries (CSCI). Community game-based respiratory muscle training (RMT) programs could reduce secondary complications. Methods: We examined the feasibility and preliminary efficacy of RMT as a community-based exercise program. Among the 10 included participants (eight male and two female), four, one, one, and four reported C3, C4, C5, and C6 complete injuries, respectively (eight graded by American Spinal Injury Association impairment scale [ASIA] A and two by ASIA B). Their mean age was 43 ± 12.3 y. The time since injury was 10 ± 6.7 y. The participants completed an RMT program for 60 min/day, twice weekly, for 8 weeks. The participants were trained in the use of a newly developed game-based RMT device. The device provides consistent pressure for respiratory muscle strength and endurance training. Seven RMT devices were modified to allow 10 game-based RMT programs. Forced vital capacity (FVC), forced expiratory volume in 1 s (FEV₁), peak expiratory flow (PEF), vital capacity (VC), inspiratory capacity (IC), inspiratory reserve volume (IRV), expiratory reserve volume (ERV), maximum inspiratory pressure (MIP), maximum expiratory pressure (MEP), and peak cough flow (PCF) were measured. Results: There were improvements after RMT compared to pre-RMT in FVC (p = 0.027, 10.62%, 0.22 effect size [ES]), PEF (p = 0.006, 23.21%, 0.45 ES), VC (p = 0.002, 35.52%, 0.60 ES), IC (p = 0.001, 46.94%, 0.81 ES), IRV (p = 0.001, 90.53%, 1.22 ES), MIP (p = 0.002, 97.25%, 1.32 ES), MEP (p = 0.005, 141.12%, 1.07 ES), and PCF (p = 0.001, 35.60%, 0.74 ES). The participants reported a positive impact of the program. Conclusions: Community game-based RMT for individuals with CSCI appears to be safe and feasible. Community exercise with RMT use may have a positive impact on the respiratory measures for patients with CSCI who are vulnerable to respiratory compromise. Trial registration: KCT0005980.

It is essential for stroke patients to maintain their therapy even after discharging inpatient rehabilitation. This is because recovery is an ongoing process that requires consistent effort. Virtual reality exergame training (VRET) is becoming widely used in stroke rehabilitation to improve physical, social, and psychological outcomes. Home-based VRET may be a more convenient and accessible option for stroke rehabilitation. This study will aim to determine the effectiveness of home-based VRET for patients with stroke who have been discharged from the hospital. This trial will randomly assign 120 participants to 8 weeks of either a VRET (intervention group) or daily life (control group). The study will measure cardiopulmonary endurance, muscular strength, functional capacity, gait, activities of daily living, and quality of life. Our main objective is to determine whether it is safe for patients to undergo VRET at home after they have been discharged from the hospital with a doctor’s note. Additionally, we aim to examine whether stroke patients are capable of exercising at home after being discharged from the hospital. This study’s outcome could pave the way for developing more comprehensive exercise protocols for stroke patients. Our findings will provide valuable insights into the efficacy of VRET as a therapeutic tool for stroke patients.