Jelle Nelis

Towards a social and context-aware multi-sensor fall detection and risk assessment platform

For elderly people fall incidents are life-changing events that lead to degradation or even loss of autonomy. Current fall detection systems are not integrated and often associated with undetected falls and/or false alarms. In this paper, a social- and context-aware multi-sensor platform is presented, which integrates information gathered by a plethora of fall detection systems and sensors at the home of the elderly, by using a cloud-based solution, making use of an ontology. Within the ontology, both static and dynamic information is captured to model the situation of a specific patient and his/her (in)formal caregivers. This integrated contextual information allows to automatically and continuously assess the fall risk of the elderly, to more accurately detect falls and identify false alarms and to automatically notify the appropriate caregiver, e.g., based on location or their current task. The main advantage of the proposed platform is that multiple fall detection systems and sensors can be integrated, as they can be easily plugged in, this can be done based on the specific needs of the patient. The combination of several systems and sensors leads to a more reliable system, with better accuracy. The proof of concept was tested with the use of the visualizer, which enables a better way to analyze the data flow within the back-end and with the use of the portable testbed, which is equipped with several different sensors.

DYAMAND: DYnamic, Adaptive MAnagement of Networks and Devices

Consumer devices increasingly are “smart” and hence offer services that can interwork with and/or be controlled by others. However, the full exploitation of the inherent opportunities this offers, is hurdled by a number of potential limitations. First of all, the interface towards the device might be vendor and even device specific, implying that extra effort is needed to support a specific device. Standardization efforts try to avoid this problem, but within a certain standard ecosystem the level of interoperability can vary (i.e. devices carrying the same standard logo are not necessarily interoperable). Secondly, different application domains (e.g. multimedia vs. energy management) today have their own standards, thus limiting trans-sector innovation because of the additional effort required to integrate devices from traditionally different domains into novel applications. In this paper, we discuss the basic components of current so-called service discovery protocols (SDPs) and present our DYAMAND (DYnamic, Adaptive MAnagement of Networks and Devices) framework. We position this framework as a middleware layer between applications and discoverable/controllable devices, and hence aim to provide the necessary tool to overcome the (intra- and inter-domain) interoperability gaps previously sketched. Thus, we believe it can act as a catalyst enabling transsector innovation.

OMUS: an optimized multimedia service for the home environment

Media content in home environments is often scattered across multiple devices in the home network. As both the available multimedia devices in the home (e.g., smartphones, tablets, laptops, game consoles, etc.) and the available content (video and audio) is increasing, interconnecting desired content with available devices is becoming harder and home users are experiencing difficulties in selecting interesting content for their current context. In this paper, we start with an analysis of the home environment by means of a user study. Information handling problems are identified and requirements for a home information system formulated. To meet these requirements we propose the OMUS home information system which includes an optimized content aggregation framework, a hybrid group-based contextual recommender system, and an overall web-based user interface making both content and recommendations available for all devices across the home network. For the group recommendations we introduced distinct weights for each user and showed that by varying the weights, the coverage (i.e., items that can be returned by the recommender) considerably increases. Also the addition of genre filter functionality was proven to further boost the coverage. The OMUS system was evaluated by means of focus groups and by qualitative and quantitative performance assessment of individual parts of the system. The modularity of internal components and limited imposed hardware requirements implies flexibility as to how the OMUS system can be deployed (ranging from e.g., embedded in hardware devices or more software services based).

Intelligent distributed multimedia collection: Content aggregation and integration

Peoples multimedia content is spread around their home network and content services on the Internet, such as YouTube, Flickr, Facebook. In this paper we present a system that aggregates all the multimedia content of the end user and integrates it into a unified collection for the users convenience. The system provides location transparency of multimedia content, content filtering on player compatibility and metadata completion to aid in improved usability. This effectively enables the user to rediscover his multimedia collection without any technical knowledge. A proof-of-concept implementation known as Intelligent Distributed Multimedia Collection (IDMC) has been made that is able to detect and browse UPnP MediaServer devices as well as collect information from YouTube. This implementation also contains a media player and is able to control UPnP MediaRenderer devices remotely. Furthermore, performance has been measured to assess different ways of iterating through a multimedia collection.

Automatic provisioning of end-to-end QoS into the home

Due to a growing number of high bandwidth applications today (such as HDTV), and an increasing amount of network and cloud based applications, service providers need to pay attention to QoS in their networks. We believe there is a need for an end-to-end approach reaching into the home as well. The Home Gateway (HG) as a key component of the home network is crucial for enabling the end-to-end solutions. UPnP-QoS has been proposed as an inhome solution for resource reservations. In this paper we assess a solution for automatic QoS reservations, on behalf of non-UPnP-QoS aware applications. Additionally we focus on an integrated end-to-end solution, combining GMPLS-based reservations in e.g., access/metro and UPnP-QoS based reservation in the home network.

Personalized robotic intervention strategy by using semantics for people with dementia in nursing homes

The Semantic Web - 14th International Conference, ESWC 2017, Portorož, Slovenia, May 28 - June 1, 2017, Proceedings, Part II

Integrating personal media and Digital TV with QoS guarantees using virtualized set-top boxes: Architecture and performance measurements

Nowadays, users consume a lot of functionality in their home coming from a service provider located in the Internet. While the home network is typically shielded off as much as possible from the ‘outside world’, the supplied services could be greatly extended if it was possible to use local information. In this article, an extended service is presented that integrates the users multimedia content, scattered over multiple devices in the home network, into the Electronic Program Guide (EPG) of the Digital TV. We propose to virtualize the set-top box, by migrating all functionality except user interfacing to the service provider infrastructure. The media in the home network is discovered through standard Universal Plug and Play (UPnP), of which the QoS functionality is exploited to ensure high quality playback over the home network, that basically is out of the control of the service provider. The performance of the subsystems are analysed.

Internet of Robotic Things: Context-Aware and Personalized Interventions of Assistive Social Robots (Short Paper)

Assistive service and companion robots are versatile and dexterous actuators that operate in our daily living environment. These robots are able to manipulate physical objects, to displace themselves and to engage in conversations. Human behavior is dynamic and oftentimes unpredictable, therefore it is crucial for such robotic systems to be assisted by a cloud-backend which: i) analyzes data from sensor and wearables ii) determines which robotic tasks need to be executed and iii) provides the necessary support for the execution of these tasks in our daily living environment. In this paper, we present our Internet-of-Robotic-Things system architecture design for a case study on personal interactions by a companion robot to alleviate behavioral disturbances of people with dementia.

Social-aware Event Handling within the FallRisk Project

OBJECTIVES With the uprise of the Internet of Things, wearables and smartphones are moving to the foreground. Ambient Assisted Living solutions are, for example, created to facilitate ageing in place. One example of such systems are fall detection systems. Currently, there exists a wide variety of fall detection systems using different methodologies and technologies. However, these systems often do not take into account the fall handling process, which starts after a fall is identified or this process only consists of sending a notification. The FallRisk system delivers an accurate analysis of incidents occurring in the home of the older adults using several sensors and smart devices. Moreover, the input from these devices can be used to create a social-aware event handling process, which leads to assisting the older adult as soon as possible and in the best possible way. METHODS The FallRisk system consists of several components, located in different places. When an incident is identified by the FallRisk system, the event handling process will be followed to assess the fall incident and select the most appropriate caregiver, based on the input of the smartphones of the caregivers. In this process, availability and location are automatically taken into account. RESULTS The event handling process was evaluated during a decision tree workshop to verify if the current day practices reflect the requirements of all the stakeholders. Other knowledge, which is uncovered during this workshop can be taken into account to further improve the process. CONCLUSIONS The FallRisk offers a way to detect fall incidents in an accurate way and uses context information to assign the incident to the most appropriate caregiver. This way, the consequences of the fall are minimized and help is at location as fast as possible. It could be concluded that the current guidelines on fall handling reflect the needs of the stakeholders. However, current technology evolutions, such as the uptake of wearables and smartphones, enables the improvement of these guidelines, such as the automatic ordering of the caregivers based on their location and availability.

Remote Management of a Large Set of Heterogeneous Devices Using Existing IoT Interoperability Platforms

With the evolution of the Internet of Things, devices of many different technologies and manufacturers are being developed (e.g. for use cases ranging from home automation to smart cities). This creates challenges regarding interoperability between these heterogeneous devices, as well as integrating them to enable innovative applications. Currently, several integration platforms already exist to integrate technologies in a local gateway (e.g. OpenHAB, Zodianet, etc.). Yet, the local set-up and configuration still is overly complex, especially for non-technical users. In this paper, we present a remote management platform that focuses on ease of configuration and installation. It allows monitoring, configuration, diagnostics and service provisioning without manual intervention of a technical person. The platform reacts on local changes such as the installation of a new device or state changes of discovered services. This information can then be used to install required plugins, generate alarms or take problem-solving actions.