Central monitoring system for ambient assisted living

Smart homes for aged care enable the elderly to stay in their own homes longer. By means of various types of ambient and wearable sensors information is gathered on people living in smart homes for aged care. This information is then processed to determine the activities of daily living (ADL) and provide vital information to carers. Many examples of smart homes for aged care can be found in literature, however, little or no evidence can be found with respect to interoperability of various sensors and devices along with associated functions. One key element with respect to interoperability is the central monitoring system in a smart home. This thesis analyses and presents key functions and requirements of a central monitoring system. The outcomes of this thesis may benefit developers of smart homes for aged care

Robotic ubiquitous cognitive ecology for smart homes

Robotic ecologies are networks of heterogeneous robotic devices pervasively embedded in everyday environments, where they cooperate to perform complex tasks. While their potential makes them increasingly popular, one fundamental problem is how to make them both autonomous and adaptive, so as to reduce the amount of preparation, pre-programming and human supervision that they require in real world applications. The project RUBICON develops learning solutions which yield cheaper, adaptive and efficient coordination of robotic ecologies. The approach we pursue builds upon a unique combination of methods from cognitive robotics, machine learning, planning and agent- based control, and wireless sensor networks. This paper illustrates the innovations advanced by RUBICON in each of these fronts before describing how the resulting techniques have been integrated and applied to a smart home scenario. The resulting system is able to provide useful services and pro-actively assist the users in their activities. RUBICON learns through an incremental and progressive approach driven by the feed- back received from its own activities and from the user, while also self-organizing the manner in which it uses available sensors, actuators and other functional components in the process. This paper summarises some of the lessons learned by adopting such an approach and outlines promising directions for future work

HIDE: User centred Domotic evolution toward Ambient Intelligence

Pervasive Computing and Ambient Intelligence (AmI) visions are still far from being achieved, especially with regard to Domotics and home applications. According to the vision of Ambient Intelligence (AmI), the most advanced technologies are those that disappear: at maturity, computer technology should become invisible. All the objects surrounding us must possess sufficient computing capacity to interact with users, the surroundings and each other. The entire physical environment in which users are immersed should thus be a hidden computer system equipped with the appropriate software in order to exhibit intelligent behavior. Even though many implementations have started to appear in several contexts, few applications have been made available for the home environment and the general public. This is mainly due to the segmentation of standards and proprietary solutions, which are currently confusing the market with a sparse offer of uninteroperable devices and systems. Although modern houses are equipped with smart technological appliances, still very few of these appliances can be seamlessly connected to each other. The objective of this research work is to take steps in these directions by proposing, on the one hand, a software system designed to make today’s heterogeneous, mostly incompatible domotic systems fully interoperable and, on the other hand, a feasible software application able to learn the behavior and habits of home inhabitants in order to actively contribute to anticipating user needs, and preventing emergency situations for his health. By applying machine learning techniques, the system offers a complete, ready-to-use practical application that learns through interaction with the user in order to improve life quality in a technological living environment, such as a house, a smart city and so on. The proposed solution, besides making life more comfortable for users without particular needs, represents an opportunity to provide greater autonomy and safety to disabled and elderly occupants, especially the critically ill ones. The prototype has been developed and is currently running at the Pisa CNR laboratory, where a home environment has been faithfully recreated

Framework for controlling automation devices based on gestures

Nowadays people's routine is becoming more and more fulfilled, when we are at home or in the office we have constant activities, appointments, and meetings. With the growth of technology, there are several ways it can help and even replace people in certain tasks. Nevertheless, many mundane tasks are not yet possible to be done only by a computer or a robot, and machines and people must work together to achieve the objective. Specifically, devices such as sensors or actuators have become very common in our daily life and they are a great help to have a more comfortable environment in our homes or our work, once they allow us to control the lighting, air conditioning, or multimedia, etc. With this in mind, it is important to develop adaptive interfaces that can instantly adjust to the needs and conditions of each user, making people’s activities more efficient. This dissertation presents a framework that performs the integration of human actions, being gestures and/or poses to activate and control devices that have the standard KNX protocol. A pose detection algorithm is used to detect different gestures/poses, where each gesture or group of gestures integrated with KNX allows easy and universal communication with various types of existing automation devices. The algorithm has standard gestures/poses which are obtained by making comparisons between the coordinates (key points) obtained by the pose estimation, comparing the key points, for example, of the wrist and shoulder for detection of a gesture where the user raises the arm vertically. In addition to standard gestures/poses, it is possible to carry out training so that the algorithm can learn new gestures and, in this way, being adaptive for each type of user. This way, with the detection of the user's gesture/pose, an interaction is then made with the home automation different types of equipment by KNX protocol, each user's gesture performs an interaction on the equipment, such as activating, deactivating, changing its intensity or its mode of operation. The results show that the framework is capable of effortlessly controlling different devices with different functionalities.Atualmente a rotina das pessoas está cada vez mais preenchida, quando estamos em casa ou no escritório cumprindo atividades, compromissos e reuniões constantemente. Com o crescimento da tecnologia, existem várias maneiras de auxiliar e até mesmo substituir as pessoas em certas tarefas. No entanto, muitas tarefas mundanas ainda não são possíveis de serem realizadas apenas por um computador ou um robô, e é necessário que a máquina e a pessoa trabalhem juntas para atingir o objetivo. Especificamente, dispositivos como sensores ou atuadores tornaram-se muito comuns no nosso dia a dia e são de grande ajuda para termos um ambiente mais confortável nas nossas casas ou no nosso trabalho, uma vez que nos permitem controlar diferentes sistemas e equipamentos como a iluminação, ar condicionado ou multimídia, etc. Com isso em mente, é importante desenvolver interfaces adaptativas que possam se ajustar instantaneamente às necessidades e condições de cada utilizador, tornando as atividades das pessoas mais simples e eficientes. Esta dissertação apresenta um framework que utiliza a integração de ações humanas, gestos e/ou poses para ativar e controlar dispositivos de automação que possuam o protocolo padrão KNX. O algortimo possui gestos/poses standard onde são obtidos realizando comparações entre as coordenadas (pontos chave - keypoints) obtidas pela pose estimation, comparando os keypoints, por exemplo, do pulso e do ombro para uma deteção de um gesto onde o utilizador levanta o braço verticalmente. Além de gestos/poses standard é possivel realizar o treinamento para que o algortimo aprenda novos gestos e, desta forma, sendo adaptativo para cada tipo de utilizador. Deste modo, com a detecção de gesto/pose do utilizador é então feita uma interação com os equipamentos de domotica por protocolo KNX, cada gesto do utilizador realiza uma interação nos equipamentos, como ativar, desativar, alterar sua intensidade ou seu modo de funcionamento. Os resultados mostram que o framework é capaz de controlar facilmente diferentes dispositivos com diferentes funcionalidades

A Mobile Healthcare Solution for Ambient Assisted Living Environments

Elderly people need regular healthcare services and, several times, are dependent of physicians’ personal attendance. This dependence raises several issues to elders, such as, the need to travel and mobility support. Ambient Assisted Living (AAL) and Mobile Health (m-Health) services and applications offer good healthcare solutions that can be used both on indoor and in mobility environments. This dissertation presents an ambient assisted living (AAL) solution for mobile environments. It includes elderly biofeedback monitoring using body sensors for data collection offering support for remote monitoring. The used sensors are attached to the human body (such as the electrocardiogram, blood pressure, and temperature). They collect data providing comfort, mobility, and guaranteeing efficiency and data confidentiality. Periodic collection of patients’ data is important to gather more accurate measurements and to avoid common risky situations, like a physical fall may be considered something natural in life span and it is more dangerous for senior people. One fall can out a life in extreme cases or cause fractures, injuries, but when it is early detected through an accelerometer, for example, it can avoid a tragic outcome. The presented proposal monitors elderly people, storing collected data in a personal computer, tablet, or smartphone through Bluetooth. This application allows an analysis of possible health condition warnings based on the input of supporting charts, and real-time bio-signals monitoring and is able to warn users and the caretakers. These mobile devices are also used to collect data, which allow data storage and its possible consultation in the future. The proposed system is evaluated, demonstrated and validated through a prototype and it is ready for use. The watch Texas ez430-Chronos, which is capable to store information for later analysis and the sensors Shimmer who allow the creation of a personalized application that it is capable of measuring biosignals of the patient in real time is described throughout this dissertation

A review of smart homes in healthcare

The technology of Smart Homes (SH), as an instance of ambient assisted living technologies, is designed to assist the homes’ residents accomplishing their daily-living activities and thus having a better quality of life while preserving their privacy. A SH system is usually equipped with a collection of inter-related software and hardware components to monitor the living space by capturing the behaviour of the resident and understanding his activities. By doing so the system can inform about risky situations and take actions on behalf of the resident to his satisfaction. The present survey will address technologies and analysis methods and bring examples of the state of the art research studies in order to provide background for the research community. In particular, the survey will expose infrastructure technologies such as sensors and communication platforms along with artificial intelligence techniques used for modeling and recognizing activities. A brief overview of approaches used to develop Human–Computer interfaces for SH systems is given. The survey also highlights the challenges and research trends in this area

On Distant Speech Recognition for Home Automation

The official version of this draft is available at Springer via http://dx.doi.org/10.1007/978-3-319-16226-3_7International audienceIn the framework of Ambient Assisted Living, home automation may be a solution for helping elderly people living alone at home. This study is part of the Sweet-Home project which aims at developing a new home automation system based on voice command to improve support and well-being of people in loss of autonomy. The goal of the study is vocal order recognition with a focus on two aspects: distance speech recognition and sentence spotting. Several ASR techniques were evaluated on a realistic corpus acquired in a 4-room flat equipped with microphones set in the ceiling. This distant speech French corpus was recorded with 21 speakers who acted scenarios of activities of daily living. Techniques acting at the decoding stage, such as our novel approach called Driven Decoding Algorithm (DDA), gave better speech recognition results than the baseline and other approaches. This solution which uses the two best SNR channels and a priori knowledge (voice commands and distress sentences) has demonstrated an increase in recognition rate without introducing false alarms

Distant speech recognition for home automation: Preliminary experimental results in a smart home

International audienceThis paper presents a study that is part of the Sweet-Home project which aims at developing a new home automation system based on voice command. The study focused on two tasks: distant speech recognition and sentence spotting (e.g., recognition of domotic orders). Regarding the first task, different combinations of ASR systems, language and acoustic models were tested. Fusion of ASR outputs by consensus and with a triggered language model (using a priori knowledge) were investigated. For the sentence spotting task, an algorithm based on distance evaluation between the current ASR hypotheses and the predefine set of keyword patterns was introduced in order to retrieve the correct sentences in spite of the ASR errors. The techniques were assessed on real daily living data collected in a 4-room smart home that was fully equipped with standard tactile commands and with 7 wireless microphones set in the ceiling. Thanks to Driven Decoding Algorithm techniques, a classical ASR system reached 7.9% WER against 35% WER in standard configuration and 15% with MLLR adaptation only. The best keyword pattern classification result obtained in distant speech conditions was 7.5% CER

State of the art of audio- and video based solutions for AAL

Working Group 3. Audio- and Video-based AAL ApplicationsIt is a matter of fact that Europe is facing more and more crucial challenges regarding health and social care due to the demographic change and the current economic context. The recent COVID-19 pandemic has stressed this situation even further, thus highlighting the need for taking action. Active and Assisted Living (AAL) technologies come as a viable approach to help facing these challenges, thanks to the high potential they have in enabling remote care and support. Broadly speaking, AAL can be referred to as the use of innovative and advanced Information and Communication Technologies to create supportive, inclusive and empowering applications and environments that enable older, impaired or frail people to live independently and stay active longer in society. AAL capitalizes on the growing pervasiveness and effectiveness of sensing and computing facilities to supply the persons in need with smart assistance, by responding to their necessities of autonomy, independence, comfort, security and safety. The application scenarios addressed by AAL are complex, due to the inherent heterogeneity of the end-user population, their living arrangements, and their physical conditions or impairment. Despite aiming at diverse goals, AAL systems should share some common characteristics. They are designed to provide support in daily life in an invisible, unobtrusive and user-friendly manner. Moreover, they are conceived to be intelligent, to be able to learn and adapt to the requirements and requests of the assisted people, and to synchronise with their specific needs. Nevertheless, to ensure the uptake of AAL in society, potential users must be willing to use AAL applications and to integrate them in their daily environments and lives. In this respect, video- and audio-based AAL applications have several advantages, in terms of unobtrusiveness and information richness. Indeed, cameras and microphones are far less obtrusive with respect to the hindrance other wearable sensors may cause to one’s activities. In addition, a single camera placed in a room can record most of the activities performed in the room, thus replacing many other non-visual sensors. Currently, video-based applications are effective in recognising and monitoring the activities, the movements, and the overall conditions of the assisted individuals as well as to assess their vital parameters (e.g., heart rate, respiratory rate). Similarly, audio sensors have the potential to become one of the most important modalities for interaction with AAL systems, as they can have a large range of sensing, do not require physical presence at a particular location and are physically intangible. Moreover, relevant information about individuals’ activities and health status can derive from processing audio signals (e.g., speech recordings). Nevertheless, as the other side of the coin, cameras and microphones are often perceived as the most intrusive technologies from the viewpoint of the privacy of the monitored individuals. This is due to the richness of the information these technologies convey and the intimate setting where they may be deployed. Solutions able to ensure privacy preservation by context and by design, as well as to ensure high legal and ethical standards are in high demand. After the review of the current state of play and the discussion in GoodBrother, we may claim that the first solutions in this direction are starting to appear in the literature. A multidisciplinary 4 debate among experts and stakeholders is paving the way towards AAL ensuring ergonomics, usability, acceptance and privacy preservation. The DIANA, PAAL, and VisuAAL projects are examples of this fresh approach. This report provides the reader with a review of the most recent advances in audio- and video-based monitoring technologies for AAL. It has been drafted as a collective effort of WG3 to supply an introduction to AAL, its evolution over time and its main functional and technological underpinnings. In this respect, the report contributes to the field with the outline of a new generation of ethical-aware AAL technologies and a proposal for a novel comprehensive taxonomy of AAL systems and applications. Moreover, the report allows non-technical readers to gather an overview of the main components of an AAL system and how these function and interact with the end-users. The report illustrates the state of the art of the most successful AAL applications and functions based on audio and video data, namely (i) lifelogging and self-monitoring, (ii) remote monitoring of vital signs, (iii) emotional state recognition, (iv) food intake monitoring, activity and behaviour recognition, (v) activity and personal assistance, (vi) gesture recognition, (vii) fall detection and prevention, (viii) mobility assessment and frailty recognition, and (ix) cognitive and motor rehabilitation. For these application scenarios, the report illustrates the state of play in terms of scientific advances, available products and research project. The open challenges are also highlighted. The report ends with an overview of the challenges, the hindrances and the opportunities posed by the uptake in real world settings of AAL technologies. In this respect, the report illustrates the current procedural and technological approaches to cope with acceptability, usability and trust in the AAL technology, by surveying strategies and approaches to co-design, to privacy preservation in video and audio data, to transparency and explainability in data processing, and to data transmission and communication. User acceptance and ethical considerations are also debated. Finally, the potentials coming from the silver economy are overviewed.publishedVersio