TactCube: An Intelligent Device to 'converse' with Smart Environments.

Ambient Intelligence is a vision of daily life in which intelligent devices interact with humans to make their lives easier, and the technology is invisible. Artificial Intelligence (AI) governs this smart environment and must interact with humans to best meet their needs and demands. Although voice assistants are very popular and efficient as conversational AI, under some conditions they cannot be used. Therefore, this work proposed a complementary tactile and tangible interface to converse with AI, creating new Tactile Signs. A prototype of TactCube, a wireless cube-shaped device that can interact with AI using only the tactile sense, is presented. The hypothesis is that TactCube can be manipulated with one hand and generate a sequence of numbers that can be interpreted as a new tactile language by a neural network solution. The paper describes the initial research made to define how these sequences can be generated and demonstrates how TactCube is able to do it.

Interaction Design Patterns for Augmented Reality Fitting Rooms.

In this work, we explore the role of augmented reality as a meta-user interface, with particular reference to its applications for interactive fitting room systems and the impact on the related shopping experience. Starting from literature and existing systems, we synthesized a set of nine interaction design patterns to develop AR fitting rooms and to support the shopping experience. The patterns were evaluated through a focus group with possible stakeholders with the aim of evaluating and envisioning the effects on the shopping experience. The focus group analysis shows as a result that the shopping experience related to an AR fitting room based on the proposed patterns is influenced by three main factors, namely: the perception of the utility, the ability to generate interest and curiosity, and the perceived comfort of the interaction and environment in which the system is installed. As a further result, the study shows that the patterns can successfully support these factors, but some elements that emerged from the focus group should be more investigated and taken into consideration by the designers.

An Impedimetric Biosensor for Detection of Volatile Organic Compounds in Food.

The demand for a wide choice of food that is safe and palatable increases every day. Consumers do not accept off-flavors that have atypical odors resulting from internal deterioration or contamination by substances alien to the food. Odor response depends on the volatile organic compounds (VOCs), and their detection can provide information about food quality. Gas chromatography/mass spectrometry is the most powerful method available for the detection of VOC. However, it is laborious, costly, and requires the presence of a trained operator. To develop a faster analytic tool, we designed a non-Faradaic impedimetric biosensor for monitoring the presence of VOCs involved in food spoilage. The biosensor is based on the use of the pig odorant-binding protein (pOBP) as the molecular recognition element. We evaluated the affinity of pOBP for three different volatile organic compounds (1-octen-3-ol, trans-2-hexen-1-ol, and hexanal) related to food spoilage. We developed an electrochemical biosensor conducting impedimetric measurements in liquid and air samples. The impedance changes allowed us to detect each VOC sample at a minimum concentration of 0.1 µM.