Behavior-enabled IoT (BeT)

The project is designed to navigate the transition towards a digital society that places humans at its core, a transformation spurred by the pandemic and the concept of “people-centricity.” This approach acknowledges the deepening interaction between humans and the digital environment, leading to a mutual influence that shapes behaviors and experiences. In response to this evolving landscape, our initiative adopts the principles of the Internet of Behaviors (IoB) as identified by Gartner as a key strategic trend. The IoB framework aims to collect and analyze data on human behaviors through IoT and social networks, applying insights from behavioral psychology to influence and modify consumer behavior across various sectors.

The project’s core, the Behavior-enabled IoT (BeT), seeks to enhance the design and implementation of IoB systems through a structured and systematic methodology. Unlike traditional approaches that layer IoB applications on existing IoT frameworks, BeT proposes a dedicated reference architecture with validated methods and patterns for IoB engineering. This architecture is designed to integrate AI for the nuanced analysis and prediction of human behavior, incorporate comprehensive metrics for Quality of Service (QoS) and Quality of Experience (QoE) to improve both system functionality and user satisfaction and facilitate a dynamic interplay between humans and systems for optimized mutual outcomes.

General Goal

BeT sees a future where humans and computational elements work together through AI and machine learning algorithms to satisfy personalized and collective goals. In this vision, humans and cyber-physical entities can move in a shared environment, each impacting the behavior of the other. This implies a bi-causal connection between humans and software systems, where software and human behavior can be adapted to follow expectations and actions for optimal Quality of Service and Quality of Experience.

Vision

BeT envisions a network of humans and computational elements that give rise to a network of cooperating human-digital entities. Both humans and cyber-physical entities can move in a shared environment, each one impacting the behavior of the other. In this vision, human and system behaviors are inferred, modeled and validated with the help of AI-enabled components.