RFID-Based Personalized Behavior Modeling

[[abstract]]In this research, we aim at building an intelligent system that can detect abnormal behavior for the elderly at home. Deployment of RFID tags at home helps us collect the daily movement data of the elderly. The clustering technique is then used to build a personalized model of normal behavior based on these RFID data. After the model is built, any incoming datum outside the model can be seen as abnormal. In this paper, we present the design of the system architecture and show the preliminary results for data collection and preprocessing.[[conferencetype]]國際[[conferencedate]]20090707~20090709[[iscallforpapers]]Y[[conferencelocation]]Brisbane, Australi

Integrating Features of Islamic Traditional Home and Smart Home

Architecture is a mirror that reflects the various elements of its environment and surroundings, such as climate, geographical characteristics, standard architectural principles, and social, cultural and scientific developments. Muslims of different regions were able, through architecture, to portray their temperaments and environments, free of external influence and guarantee life goals for users. Every day, building owners and occupants experience the constant challenges of comfort, convenience, cost, productivity, performance and sustainability. Owners, designers, builders, and operators are continuously faced with new processes, technologies and offerings to help them achieve better building performance. Since an intelligent building is run by a “system of systems” that is integrated to deliver a higher level of operational efficiency and an improved set of user-interface tools than are usually found in traditional building automation; at the other hand Arab homes with Islamic Identity guarantee all life goals for use.. Hence, this research focus on the smart environmental treatments of Islamic features for traditional architecture in Arabs homes, features of smart home and life goals for resident users.Trying to achieve a methodology combining them for enriching Arab experience of traditional architecture and its architectural results, with the modern trends of smart architecture. This combination aims at creating a residential model combining the benefits and features of Arab Islamic identity and intelligent design

HalleyAssist: A Personalised Internet of Things Technology to Assist the Elderly in Daily Living

Ambient Assisted Living (AAL) research has received extensive attention in recent years. AAL applications combine aspects of Internet of Things (IoT), smart platform design and machine learning to produce an intelligent system. In this paper we describe a personalised IoT-based AAL system that enables an independent and safe life for elderly people within their own home via real-time monitoring and intervention. The system, HalleyAssist underpinned by smart home automation functions includes a novel approach for monitoring the wellbeing and detecting abnormal changes in behavioral patterns of an elderly person. The significance of the approach is in the use of machine learning models to automatically learn normal behavioral pattern for the person from IoT sensor data and using the models derived to detect significant changes in behavioral pattern should they occur. The architecture and developed proof of concept of the proposed system is presented along with discussion of how privacy and security concerns are addressed. We also report on outcomes of real-world in-home trials of an early version of the system where it was installed in four older people\u27s home for a period of six weeks. The response from the older people to the deployed system was very positive. Finally, the paper presents a discussion and an analysis of the results using the data collected during the in-home trials

A Service-oriented Architecture for Ambient-Assisted Living

Ambient-Assisted Living (AAL) is currently an important research and development area, mainly due to the rapidly aging society, the increasing cost of health care, and the growing importance that individuals place on living independently. The general goal of AAL solutions is to apply ambient-assisted intelligence to enable people with specific demands (e.g. handicapped or elderly) to live in their preferred environment longer by tools (i.e. smart objects, mobile and wearable sensors, intelligent devices) being sensitive and responsive to the presence of people and their actions. The research describes the design and development of a novel service-oriented system architecture where different smart objects and sensors are combined to offer ambient-assisted living intelligence to older people. The design stage is driven by a user-centred approach to define an interoperable architecture and human-oriented principles to create usable products and well-accepted services. Such architecture has been realized in the context of an Italian research project funded by the Marche Region and promoted by INRCA (National Institute on Health and Science of Aging) in the framework of smart home for active ageing and ambient assisted living. The result is an interoperable and flexible platform that allows creating user-centred services for independent living

Voice-Activated Smart Home Controller Using Machine Learning

UIDB/00066/2020The emergence of the Internet of Things concept has provided a great vision for the technological future, intending to enable the extraction and comprehension of information from the environment around us, making use of the interaction and cooperation between several technological devices. The example of Smart Homes, in particular, aims to integrate these devices into households, enabling the automation of tasks previously performed by humans, to simplify their daily lives and create a more comfortable environment. However, many of these devices fail to keep their promise, since they were not developed taking into account the frequent change of habits and tastes of the user, being necessary reprogramming of the device to follow the new behaviors. Taking this problem into account, this article presents the design and end-to-end implementation of a voice-activated smart home controller for intelligent devices, deployed in a real environment and validated in an experimental setup of motorized blinds. The architecture of the proposed solution integrates evolvable intelligence with the use of an Online Learning framework, enabling it to automatically adapt to the user's habits and behavioral patterns. The results obtained from the various evaluation tests provide a validation of the operation and usefulness of the developed system. The main contributions of this work are: I) design of a smart home controller's architecture; II) end-to-end implementation of a smart home controller and respective guidelines; III) open-source dataset of user behavior from the smart blinds scenario; IV) comparison between Online and Offline Learning approaches.publishersversionpublishe

SPLICEcube Architecture: An Extensible Wi-Fi Monitoring Architecture for Smart-Home Networks

The vision of smart homes is rapidly becoming a reality, as the Internet of Things and other smart devices are deployed widely. Although smart devices offer convenience, they also create a significant management problem for home residents. With a large number and variety of devices in the home, residents may find it difficult to monitor, or even locate, devices. A central controller that brings all the home’s smart devices under secure management and a unified interface would help homeowners and residents track and manage their devices. We envision a solution called the SPLICEcube whose goal is to detect smart devices, locate them in three dimensions within the home, securely monitor their network traffic, and keep an inventory of devices and important device information throughout the device’s lifecycle. The SPLICEcube system consists of the following components: 1) a main cube, which is a centralized hub that incorporates and expands on the functionality of the home router, 2) a database that holds network data, and 3) a set of support cubelets that can be used to extend the range of the network and assist in gathering network data. To deliver this vision of identifying, securing, and managing smart devices, we introduce an architecture that facilitates intelligent research applications (such as network anomaly detection, intrusion detection, device localization, and device firmware updates) to be integrated into the SPLICEcube. In this thesis, we design a general-purpose Wi-Fi architecture that underpins the SPLICEcube. The architecture specifically showcases the functionality of the cubelets (Wi-Fi frame detection, Wi-Fi frame parsing, and transmission to cube), the functionality of the cube (routing, reception from cubelets, information storage, data disposal, and research application integration), and the functionality of the database (network data storage). We build and evaluate a prototype implementation to demonstrate our approach is scalable to accommodate new devices and extensible to support different applications. Specifically, we demonstrate a successful proof-of-concept use of the SPLICEcube architecture by integrating a security research application: an Inside-Outside detection system that classifies an observed Wi-Fi device as being inside or outside the home

Facilitating Inter-Domain Synergies in Ambient Assisted Living Environments

Current Ambient Assisted Living (AAL) environments lack integration of sensors and actuators of other sub-domains. Creating technical and organizational integration is addressed by the BASIS project (Build Automation by a Scalable and Intelligent System), which aims to build a cross-domain home bus system. The main objective of this paper is to present an overview of design, architecture and state of realization of BASIS by describing the requirements development process, underlying hardware design and software architecture. We built a distributed system of one independent building manager with several redundantly meshed segment controllers, each controlling a bus segment with any number of bus nodes. The software system layer is divided into logical partitions representing each sub-domain. Structured data storage is possible with a special FHIR based home centered data warehouse. The system has been implemented in six apartments running under daily living conditions. BASIS integrates a broad range of sub-domains, which poses challenges to all project partners in terms of a common terminology, and project management methods, but enables development of inter-domain synergies like using the same sensor and actuator hardware for a broad range of services and use cases

Modeling, Simulation and Emulation of Intelligent Domotic Environments

Intelligent Domotic Environments are a promising approach, based on semantic models and commercially off-the-shelf domotic technologies, to realize new intelligent buildings, but such complexity requires innovative design methodologies and tools for ensuring correctness. Suitable simulation and emulation approaches and tools must be adopted to allow designers to experiment with their ideas and to incrementally verify designed policies in a scenario where the environment is partly emulated and partly composed of real devices. This paper describes a framework, which exploits UML2.0 state diagrams for automatic generation of device simulators from ontology-based descriptions of domotic environments. The DogSim simulator may simulate a complete building automation system in software, or may be integrated in the Dog Gateway, allowing partial simulation of virtual devices alongside with real devices. Experiments on a real home show that the approach is feasible and can easily address both simulation and emulation requirement