The Internet of Things (IoT) is transforming how devices and systems interact, enabling smart applications across healthcare, manufacturing, energy, transportation, and smart cities. This rapid growth generates vast, diverse, and real-time data — Big Data — which demands advanced techniques for analysis, storage, security, and intelligent decision-making.
The convergence of IoT, Big Data, Artificial Intelligence (AI), and Machine Learning creates new opportunities for actionable insights, autonomous systems, and enhanced user experiences. In particular, emerging technologies such as Generative AI offer unprecedented capabilities for smart, connected environments.
However, security, privacy, trust, and ethical AI remain critical challenges. The conference invites research contributions, practical solutions, and case studies addressing these concerns and advancing the state of the art in IoT and Big Data ecosystems.
IoTDBS brings together researchers, practitioners, and industry experts to explore innovations, trends, and challenges shaping the future of smart systems and data-driven applications. Maintaining a high level of security and privacy in IoT environments is crucial, and we welcome recommendations, solutions, demonstrations, and best practices addressing all aspects of security and privacy in IoT and Big Data.