Enhancing Aviation Safety through AI-Driven Mental Health Management for Pilots and Air Traffic Controllers
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Cited by 3 publications
References 94 publications
War, emotions, mental health, and artificial intelligence
During the war time dysregulation of negative emotions such as fear, anger, hatred, frustration, sadness, humiliation, and hopelessness can overrule normal societal values, culture, and endanger global peace and security, and mental health in affected societies. Therefore, it is understandable that the range and power of negative emotions may play important roles in consideration of human behavior in any armed conflict. The estimation and assessment of dominant negative emotions during war time are crucial but are challenged by the complexity of emotions’ neuro-psycho-physiology. Currently available natural language processing (NLP) tools have comprehensive computational methods to analyze and understand the emotional content of related textual data in war-inflicted societies. Innovative AI-driven technologies incorporating machine learning, neuro-linguistic programming, cloud infrastructure, and novel digital therapeutic tools and applications present an immense potential to enhance mental health care worldwide. This advancement could make mental health services more cost-effective and readily accessible. Due to the inadequate number of psychiatrists and limited psychiatric resources in coping with mental health consequences of war and traumas, new digital therapeutic wearable devices supported by AI tools and means might be promising approach in psychiatry of future. Transformation of negative dominant emotional maps might be undertaken by the simultaneous combination of online cognitive behavioral therapy (CBT) on individual level, as well as usage of emotionally based strategic communications (EBSC) on a public level. The proposed positive emotional transformation by means of CBT and EBSC may provide important leverage in efforts to protect mental health of civil population in war-inflicted societies. AI-based tools that can be applied in design of EBSC stimuli, like Open AI Chat GPT or Google Gemini may have great potential to significantly enhance emotionally based strategic communications by more comprehensive understanding of semantic and linguistic analysis of available text datasets of war-traumatized society. Human in the loop enhanced by Chat GPT and Gemini can aid in design and development of emotionally annotated messages that resonate among targeted population, amplifying the impact of strategic communications in shaping human dominant emotional maps into a more positive by CBT and EBCS.
War, emotions, mental health, and artificial intelligence
During the war time dysregulation of negative emotions such as fear, anger, hatred, frustration, sadness, humiliation, and hopelessness can overrule normal societal values, culture, and endanger global peace and security, and mental health in affected societies. Therefore, it is understandable that the range and power of negative emotions may play important roles in consideration of human behavior in any armed conflict. The estimation and assessment of dominant negative emotions during war time are crucial but are challenged by the complexity of emotions’ neuro-psycho-physiology. Currently available natural language processing (NLP) tools have comprehensive computational methods to analyze and understand the emotional content of related textual data in war-inflicted societies. Innovative AI-driven technologies incorporating machine learning, neuro-linguistic programming, cloud infrastructure, and novel digital therapeutic tools and applications present an immense potential to enhance mental health care worldwide. This advancement could make mental health services more cost-effective and readily accessible. Due to the inadequate number of psychiatrists and limited psychiatric resources in coping with mental health consequences of war and traumas, new digital therapeutic wearable devices supported by AI tools and means might be promising approach in psychiatry of future. Transformation of negative dominant emotional maps might be undertaken by the simultaneous combination of online cognitive behavioral therapy (CBT) on individual level, as well as usage of emotionally based strategic communications (EBSC) on a public level. The proposed positive emotional transformation by means of CBT and EBSC may provide important leverage in efforts to protect mental health of civil population in war-inflicted societies. AI-based tools that can be applied in design of EBSC stimuli, like Open AI Chat GPT or Google Gemini may have great potential to significantly enhance emotionally based strategic communications by more comprehensive understanding of semantic and linguistic analysis of available text datasets of war-traumatized society. Human in the loop enhanced by Chat GPT and Gemini can aid in design and development of emotionally annotated messages that resonate among targeted population, amplifying the impact of strategic communications in shaping human dominant emotional maps into a more positive by CBT and EBCS.
Artificial Intelligence and Smart Technologies in Safety Management: A Comprehensive Analysis Across Multiple Industries
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.
Psychosocial risks and occupational health: Fatigue and sleep disturbances among aviation professionals
This study investigates the relationship between exposure to psychosocial risk factors at work, fatigue, and sleep quality among civil aviation professionals. Psychosocial risk factors such as excessive workload, lack of control over tasks, job insecurity, and inadequate social support are prevalent in high-demand environments like civil aviation, where constant vigilance and rapid decision-making are crucial. The research involved 200 participants, including pilots and flight attendants, who completed questionnaires measuring psychosocial stressors, sleepiness, and fatigue. Results indicated significant associations between role conflict and ambiguity, lack of social support, work/family conflict, and the pressure of responsibility with increased fatigue and sleep disturbances. Gender differences were noted, with women experiencing higher levels of work/family conflict. The study emphasizes the need for organizational strategies to mitigate these psychosocial stressors by enhancing role clarity, providing social support, fostering work-life balance, and managing job responsibilities to improve health outcomes and operational safety in aviation. Future research should consider longitudinal and diverse studies to explore these dynamics further and test intervention efficacy.
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