High stress levels and sleep deprivation may cause several mental or physical health issues, such as depression, impaired memory, decreased motivation, obesity, etc. The COVID-19 pandemic has produced unprecedented changes in our lives, generating significant stress, and worries about health, social isolation, employment, and finances. To this end, nowadays more than ever, it is crucial to deliver solutions that can help people to manage and control their stress, as well as to reduce sleep disturbances, so as to improve their health and overall quality of life. Technology, and in particular Ambient Intelligence Environments, can help towards that direction, when considering that they are able to understand the needs of their users, identify their behavior, learn their preferences, and act and react in their interest. This work presents two systems that have been designed and developed in the context of an Intelligent Home, namely CaLmi and HypnOS, which aim to assist users that struggle with stress and poor sleep quality, respectively. Both of the systems rely on real-time data collected by wearable devices, as well as contextual information retrieved from the ambient facilities of the Intelligent Home, so as to offer appropriate pervasive relaxation programs (CaLmi) or provide personalized insights regarding sleep hygiene (HypnOS) to the residents. This article will describe the design process that was followed, the functionality of both systems, the results of the user studies that were conducted for the evaluation of their end-user applications, and a discussion about future plans.

The emergence of the Ambient Intelligence (AmI) paradigm and the proliferation of Internet of Things (IoT) devices and services unveiled new potentials for the domain of domestic living, where the line between “the computer” and the (intelligent) environment becomes altogether invisible. Particularly, the residents of a house can use the living room not only as a traditional social and individual space where many activities take place, but also as a smart ecosystem that (a) enhances leisure activities by providing a rich suite of entertainment applications, (b) implements a home control middleware, (c) acts as an intervention host that is able to display appropriate content when the users need help or support, (d) behaves as an intelligent agent that communicates with the users in a natural manner and assists them throughout their daily activities, (e) presents a notification hub that provides personalized alerts according to contextual information, and (f) becomes an intermediary communication center for the family. This paper (i) describes how the “Intelligent Living Room” realizes these newly emerged roles, (ii) presents the process that was followed in order to design the living room environment, (iii) introduces the hardware and software facilities that were developed in order to improve quality of life, and (iv) reports the findings of various evaluation experiments conducted to assess the overall User Experience (UX).

The proliferation of Internet of Things (IoT) devices and services and their integration in intelligent environments creates the need for a simple yet effective way of controlling and communicating with them. Towards such a direction, this work presents ParlAmI, a conversational framework featuring a multimodal chatbot that permits users to create simple “if-then” rules to define the behavior of an intelligent environment. ParlAmI delivers a disembodied conversational agent in the form of a messaging application named MAI, and an embodied conversational agent named nAoMI employing the programmable humanoid robot NAO. This paper describes the requirements and architecture of ParlAmI, the infrastructure of the “Intelligent Home” in which ParlAmI is deployed, the characteristics and functionality of both MAI and nAoMI, and finally presents the findings of a user experience evaluation that was conducted with the participation of sixteen users.

This paper presents LECTOR, a system that helps educators in understanding when students have stopped paying attention to the educational process and assists them in reengaging the students to the current learning activity. LECTOR aims to take advantage of the ambient facilities that “smart classrooms” have to offer by (i) enabling educators to employ their preferred attention monitoring strategies (including any well-established activity recognition techniques) in order to identify inattentive behaviors and (ii) recommending interventions for motivating distracted students when deemed necessary. Furthermore, LECTOR offers an educator friendly design studio that enables teachers to create or modify the rules that trigger “inattention alarms”, as well as tailor the intervention mechanism to the needs of their course by modifying the respective rules. This paper presents the rationale behind the design of LECTOR and outlines its key features and facilities.

This work blends the domain of Precision Agriculture with the prevalent paradigm of Ambient Intelligence, so as to enhance the interaction between farmers and Intelligent Environments, and support their various daily agricultural activities, aspiring to improve the quality and quantity of cultivated plants. In this paper, two systems are presented, namely the Intelligent Greenhouse and the AmI seedbed, targeting a wide range of agricultural activities, starting from planting the seeds, caring for each individual sprouted plant up to their transplantation in the greenhouse, where the provision for the entire plantation lasts until the harvesting period.