As one of the most promising technologies for next-generation mobile platforms, Augmented Reality (AR) has the potential to radically change the way users interact with real environments enriched with various digital information. To achieve this potential, it is of fundamental importance to track and maintain accurate registration between real and computer-generated objects. Thus, it is crucially important to assess tracking capabilities. In this paper, we present a benchmark evaluation of the tracking performances of some of the most popular AR handheld devices, which can be regarded as a representative set of devices for sale in the global market. In particular, eight different next-gen devices including smartphones and tablets were considered. Experiments were conducted in a laboratory by adopting an external tracking system. The experimental methodology consisted of three main stages: calibration, data acquisition, and data evaluation. The results of the experimentation showed that the selected devices, in combination with the AR SDKs, have different tracking performances depending on the covered trajectory.

In the context of Industry 4.0, the Operator 4.0 paradigm plays a crucial role in seamlessly integrating new digital technologies into smart factories. These technologies are designed to accommodate workers with varying skills, capabilities, and preferences. To promote the adoption of these innovative digital tools and ensure high user acceptance, it is essential to prioritize human factors and place workers at the heart of the development process. This can be achieved through structured design strategies, such as those employed in user-centered design approaches. Within this framework, this paper introduces an innovative Augmented Reality tool designed to facilitate and streamline real-time inspection activities performed by operators on assembled products at the workplace. The development of this tool was based on a user-centered design approach, which actively engaged end-users at different stages of design and testing phases. User studies were conducted using a real case study to evaluate the usability and user acceptance of the proposed solution. The results are encouraging, indicating a promising path forward for the effective and valid implementation of this AR tool in an industrial setting.