Heterogeneous Device Networking for an AmI Environment

Assisted living environments involve a wide range of different devices. Most of them are commercially available, but typically associated to standard domotics buses not compatible with each other. Besides, in many cases it is desirable to integrate new devices to a system that might not support the installed bus protocol. Interconnection between devices is far from simple, specially because domotic buses are often proprietary. The most popular solution to this problem is to export information to Ethernet as a system meeting point, but it is not always simple and accessibility in proprietary buses is limited. This paper proposes a method to integrate a variety of platforms through a shared memory interface, including a proprietary bus, commercial devices and ad hoc systems. Its main novelty is that compatibility between dif ferent standards is achieved without additional expensive hardware.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

The NFC tag structure in AmI Environment

The N ear Field Communications (NFC) enabled mobile phones are excellent devices to obtain services whit minimal effort: touching interaction. We propose the implementation of an Ambient Intelligence Environment with the single use of NFC technology (AmIE - NFC), which was developed in an environment with already existing computer infrastructure. In this environment, services from devices are controlled or requested simply by touching. We put a tag - NFC on each element or device. This work explains the tag - NFC structure to implement an AmIE - NFC and information flow when a user requests a service

Engineering ambient visual sensors

Visual sensors are an indispensable prerequisite for those AmI environments that require a surveillance component. One practical issue concerns maximizing the operational longevity of such sensors as the operational lifetime of an AmI environment itself is dependent on that of its constituent components. In this paper, the intelligent agent paradigm is considered as a basis for managing a camera collective such that the conflicting demands of power usage optimization and system performance are reconciled

A dynamic user profiling technique in a AmI environment

Marques V., Costa A., Novais P., A Dynamic User Profiling Technique in a AmI Environment, World Congress on Information and Communication Technologies, IEEE Computer Society, Mumbai, India, ISBN: 978-1-4673-0125-1, pp 1251-1256, 2011.Currently there are many services that can assist the human being in his decision making. Many of these services provide aid as consistent as possible attending the characteristics and preferences of a user, which compiled results in a person’s profile. Without profiles, systems could not provide a coherent aid to a user. In addition we can consider the profiles as the basis of recommendation systems. Paramount with cognitive helping systems, that provide decisions and recommendations these actions can more accu- rate and user driven. However, the profiles need to be updated over time, as a human being changes of preferences or beliefs, the profiles also need to adapt to dynamic environments. It is introduced a project that applies the Bayesian Networks and Case- Based Reasoning techniques to create and modulate user profiles in a coherent and dynamic way, using stochastic models and high-level event relations and characteristics to devise an accurate suggestion of activities the user can perform, being integrated in an Ambient Assisted Living Project.(undefined

AmIE: An Ambient Intelligent Environment for Assisted Living

In the modern world of technology Internet-of-things (IoT) systems strives to provide an extensive interconnected and automated solutions for almost every life aspect. This paper proposes an IoT context-aware system to present an Ambient Intelligence (AmI) environment; such as an apartment, house, or a building; to assist blind, visually-impaired, and elderly people. The proposed system aims at providing an easy-to-utilize voice-controlled system to locate, navigate and assist users indoors. The main purpose of the system is to provide indoor positioning, assisted navigation, outside weather information, room temperature, people availability, phone calls and emergency evacuation when needed. The system enhances the user's awareness of the surrounding environment by feeding them with relevant information through a wearable device to assist them. In addition, the system is voice-controlled in both English and Arabic languages and the information are displayed as audio messages in both languages. The system design, implementation, and evaluation consider the constraints in common types of premises in Kuwait and in challenges, such as the training needed by the users. This paper presents cost-effective implementation options by the adoption of a Raspberry Pi microcomputer, Bluetooth Low Energy devices and an Android smart watch.Comment: 6 pages, 8 figures, 1 tabl

Prediction of mobility entropy in an ambient intelligent environment

Ambient Intelligent (AmI) technology can be used to help older adults to live longer and independent lives in their own homes. Information collected from AmI environment can be used to detect and understanding human behaviour, allowing personalized care. The behaviour pattern can also be used to detect changes in behaviour and predict future trends, so that preventive action can be taken. However, due to the large number of sensors in the environment, sensor data are often complex and difficult to interpret, especially to capture behaviour trends and to detect changes over the long-term. In this paper, a model to predict the indoor mobility using binary sensors is proposed. The model utilizes weekly routine to predict the future trend. The proposed method is validated using data collected from a real home environment, and the results show that using weekly pattern helps improve indoor mobility prediction. Also, a new measurement, Mobility Entropy (ME), to measure indoor mobility based on entropy concept is proposed. The results indicate ME can be used to distinguish elders with different mobility and to see decline in mobility. The proposed work would allow detection of changes in mobility, and to foresee the future mobility trend if the current behaviour continues

Bringing Health Telemonitoring into IPTV Based AMI Environment

In this paper, we describe the development of a personalhealth telemonitoring application which is integrated into the Internet television based home communication environment. The application presently enables monitoring of blood pressure and body weight and supports on-line medical interviews. We present the functionality of this application. Its key feature is the user interface, manageable by a simple TV remote-control. The implementation results in a software widget, which is installed in a net-top-box. It builds the user interface, provides monitoring of measurement devices and communications with the backend systems. We conducted an evaluation of the overall user experience, which shows very encouraging scores. Beside this, the application enables personal-health service that is comparable to the one, provided by dedicated personalhealth systems. At the same time, its open architecture allows for future extensions and simple inclusion of other health monitoring areas

Eliciting user requirements for ambient intelligent systems: a case study

Ambient intelligent (AmI) systems are electronic environments that are responsive and sensitive to the presence of people (Weiser, 1991). Eliciting requirements for AmI systems, like for any novel technology, is hard because of high uncertainties, such as: 1) both the users and use context are unknown; 2) there is no identified problem that needs to be solved (people cannot state in advance what they want); 3) there is no product idea; 4) it is unclear what future technology can do. There are currently no requirements engineering method for novel AmI technologies. In this short note, we present the current state of our research, which aims at defining a method for identifying requirements for AmI systems

Ubiquitous Computing and Ambient Intelligence—UCAmI

The Ubiquitous Computing (UC) idea envisioned by Weiser in 1991 [1] has recently evolved to a more general paradigm known as Ambient Intelligence (AmI) that represents a new generation of user-centred computing environments and systems. These solutions aim to find new ways to better integrate information technology into everyday life devices and activities. AmI environments are integrated by several autonomous computational devices of modern life ranging from consumer electronics to mobile phones. Ideally, people in an AmI environment will not notice these devices, but will benefit from the services these solutions provide them. Such devices are aware of the people present in those environments by reacting to their gestures, actions, and context [2]. Recently the interest in AmI environments has grown considerably due to new challenges posed by society’s demand for highly innovative services, such as smart environments, Ambient Assisted Living (AAL), e-Health, Internet of Things, and intelligent systems, among others.The Ubiquitous Computing (UC) idea envisioned by Weiser in 1991 [1] has recently evolved to a more general paradigm known as Ambient Intelligence (AmI) that represents a new generation of user-centred computing environments and systems. These solutions aim to find new ways to better integrate information technology into everyday life devices and activities. AmI environments are integrated by several autonomous computational devices of modern life ranging from consumer electronics to mobile phones. Ideally, people in an AmI environment will not notice these devices, but will benefit from the services these solutions provide them. Such devices are aware of the people present in those environments by reacting to their gestures, actions, and context [2]. Recently the interest in AmI environments has grown considerably due to new challenges posed by society’s demand for highly innovative services, such as smart environments, Ambient Assisted Living (AAL), e-Health, Internet of Things, and intelligent systems, among others