The integration of Internet of Things (IoT) and Artificial Intelligence (AI) in public health represents a transformative force, that is already significantly reshaping health monitoring, disease prevention, decision-making, and healthcare delivery. IoT technologies enable real-time collection and sharing of health-related data through interconnected devices, such as wearables, sensors, and mobile healthcare applications. AI further supplements these technical advancements by providing robust analytical algorithms capable of interpreting vast amounts of data to support preventive strategies, rapid detection of disease outbreaks, improved surveillance capabilities, and personalized healthcare interventions. Despite their transformative promises, significant hurdles remain, including critical technical and infrastructural limitations, ongoing concerns about data security and confidentiality, ethical debates surrounding data handling, and uneven accessibility across diverse socioeconomic contexts. Existing studies have demonstrated both the vast potential and substantial challenges associated with the integration of IoT and AI in public health, underscoring the importance of targeted research to address knowledge gaps and effectively translate innovations into practice.

This Research Topic aims to comprehensively investigate current challenges and barriers hindering the broader adoption of IoT and AI in public health, while outlining innovative solutions, strategies, and opportunities for successfully harnessing these transformative technologies. Specifically, this Research Topic seeks to highlight experiences and evidence related to successful deployment examples, effective practices, ethical guidelines, and regulatory frameworks necessary to ensure responsible implementation of IoT and AI initiatives. It will address questions such as how these technologies can be safely and ethically integrated into public health frameworks, explore the practicalities of building equitable access, and identify pathways to overcoming existing adoption barriers.

Public health is a very comprehensive container, which cannot neglect the integration with more exquisitely clinical activities. Primary care and emergency consultations are some of them, very suitable to be facilitated by an expert approach with the use of AI and IoT.

To gather further insights within the domain of IoT and AI applications for public health, we welcome articles addressing, but not limited to, the following themes:

• Real-time and remote population health monitoring through integrated IoT and AI systems
• Security risks, data protection, and privacy challenges related to IoT and AI health applications
• Ethical considerations and regulatory frameworks necessary for implementing IoT and AI in health systems
• Case studies on successful implementation, scalability, and sustainability of integrated IoT-AI public health solutions
• Innovations in predictive modeling, early detection, and disease risk stratification using AI-driven IoT technologies
• Infrastructure readiness, resource allocation, and training required for successful integration of IoT and AI solutions
• Strategies for addressing and reducing disparities in access and utilization of IoT and AI health technologies.

This Research Topic will serve as a significant resource, fostering dialogue among interdisciplinary stakeholders to accelerate the responsible deployment of IoT and AI tools and ultimately enhance population health outcomes globally.

This Research Topic was launched in collaboration with the 10th Digital Public Health Conference, a world-leading annual interdisciplinary event on research and innovation in digital public health, organized by University College London. We welcome submissions from speakers, attendees and the broader research community.

Are you interested in contributing a manuscript to this Research Topic?

Internet of Things (IoT) and Artificial Intelligence in Public Health: Challenges, Barriers and Opportunities