Embedded systems and ambient technology enable users to interact at any time and anywhere. In the BASIS project for identity management, CWI investigates transparent biometrics in home environments. Possible application areas are user profiling for shopping , listening to one's favourite music and operating gadgets and appliances in the home.
Purpose Building services technologies such as home automation systems and remote monitoring are increasingly used to support people in their own homes. In order for these technologies to be fully appreciated by the endusers (mainly older care recipients, informal carers and care professionals), user needs should be understood1,2. In other words, supply and demand should match. Steele et al.3 state that there is a shortage of studies exploring perceptions of older users towards technology and the acceptance or rejection thereof. This paper presents an overview of user needs in relation to ambient assisted living (AAL) projects, which aim to support ageing-in-place in The Netherlands. Method A literature survey was made of Dutch AAL projects, focusing on user needs. A total of 7 projects concerned with older persons, with and without dementia, were included in the overview. Results & Discussion By and large technology is considered to be a great support in enabling people to age-in-place. Technology is, therefore, accepted and even embraced by many of the end-users and their relatives. Technology used for safety, security, and emergency response is most valued. Involvement of end-users improves the successful implementation of ambient technology. This is also true for family involvement in the case of persons with dementia. Privacy is mainly a concern for care professionals. This group is also key to successful implementation, as they need to be able to work with the technology and provide information to the end-users. Ambient technologies should be designed in an unobtrusive way, in keeping with indoor design, and be usable by persons with sensory of physical impairments. In general, user needs, particularly the needs of informal carers and care professionals, are an understudied topic. These latter two groups play an important role in implementation and acceptance among care recipients. They should, therefore, deserve more attention from the research community.
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Introduction: Ambient intelligence technologies are a means to support ageing-in-place by monitoring clients in the home. In this study, monitoring is applied for the purpose of raising an alarm in an emergency situation, and thereby, providing an increased sense of safety and security. Apart from these technological solutions, there are numerous environmental interventions in the home environment that can support people to age-in-place. The aim of this study was to investigate the needs and motives, related to ageing-in-place, of the respondents receiving ambient intelligence technologies, and to investigate whether, and how, these technologies contributed to aspects of ageing-in-place. Methodology: This paper presents the results of a qualitative study comprised of interviews and observations of technology and environmental interventions in the home environment among 18 community-dwelling older adults with a complex demand for care. These respondents had a prototype of the Unattended Autonomous Surveillance system, an example of ambient intelligence technology, installed in their homes as a means to age-in-place. The UAS-system offers a large range of functionalities, including mobility monitoring, voice response, fire detection, as well as wandering detection and prevention, which can be installed in different configurations. Results: The respondents had various motives to use ambient intelligence technologies to support ageing-in-place. The most prominent reason was to improve the sense of safety and security, in particular, in case of fall incidents, when people were afraid not to be able to use their existing emergency response systems. The ambient intelligence technologies were initially seen as a welcome addition to strategies already adopted by the respondents, including a variety of home modifications and assistive devices. The systems tested increased the sense of safety and security and helped to postpone institutionalisation. Respondents came up with a set of specifications in terms of the operation and the design of the technology. False alarms were also regarded as a sign that the ambient intelligence technology is functioning. Moreover, a good integration of the new technologies in the provision of health care is indispensable, and installation should be done in an acceptable and unobtrusive manner. Ambient intelligence technologies can contribute to an increased safety and security at home. The technologies alone offer no all encompassing solution as home care and additional environmental interventions are still needed to support ageing-in-place. Results of the study are used to further improve the ambient intelligence technologies and their implementation.
A world where technology is ubiquitous and embedded in our daily lives is becoming increasingly likely. To prepare our students to live and work in such a future, we propose to turn Saxion’s Epy-Drost building into a living lab environment. This will entail setting up and drafting the proper infrastructure and agreements to collect people’s location and building data (e.g. temperature, humidity) in Epy-Drost, and making the data appropriately available to student and research projects within Saxion. With regards to this project’s effect on education, we envision the proposal of several derived student projects which will provide students the opportunity to work with huge amounts of data and state-of-the-art natural interaction interfaces. Through these projects, students will acquire skills and knowledge that are necessary in the current and future labor-market, as well as get experience in working with topics of great importance now and in the near future. This is not only aligned with the Creative Media and Game Technologies (CMGT) study program’s new vision and focus on interactive technology, but also with many other education programs within Saxion. In terms of research, the candidate Postdoc will study if and how the data, together with the building’s infrastructure, can be leveraged to promote healthy behavior through playful strategies. In other words, whether we can persuade people in the building to be more physically active and engage more in social interactions through data-based gamification and building actuation. This fits very well with the Ambient Intelligence (AmI) research group’s agenda in Augmented Interaction, and CMGT’s User Experience line. Overall, this project will help spark and solidify lasting collaboration links between AmI and CMGT, give body to AmI’s new Augmented Interaction line, and increase Saxion’s level of education through the dissemination of knowledge between researchers, teachers and students.
Assemblageprocessen en diensten van producenten van hightech systemen worden in Noordwest-Europa gekenmerkt door een hoge variatie aan producten en oplossingen met laag volume. Productieautomatisering, flexibilisering en optimalisatie zijn essentiële processen om kleinere series te produceren en tegelijkertijd de grote verscheidenheid aan producten en diensten te realiseren. Om arbeidsproductiviteitsverbeteringen mogelijk te maken worden apparaten steeds vaker uitgerust met visionsystemen voor pick-and-place toepassingen, kwaliteitscontroles, objectlokalisaties en objectherkenning. Visionsystemen zijn echter gevoelig voor veranderingen in de omgeving, waardoor systemen kunnen stilvallen. Visionsystemen zijn met name gevoelig voor onvoorspelbare veranderingen in de omgeving, zoals belichting, schaduwvorming, oriëntatie van producten en grote optische variaties in bijvoorbeeld natuurlijke producten. Machine Learning (ML), een vorm van kunstmatige intelligentie, kan deze tekortkomingen grotendeels oplossen en kan visionsystemen robuuster en sneller configureerbaar maken; ML is uitermate geschikt om toegepast te worden in visiontoepassingen. Echter, ML voor vision is voor veel MKB’ers een ver-van-mijn-bed-show, voorbestemd voor multinationals met grote budgetten. Bovenal is de structuur en kennis over het toepassen van ML voor vision niet helder noch eenvoudig toegankelijk. Daarom is de onderzoeksvraag: Hoe kunnen door het industriële MKB machine learning frameworks binnen visiontoepassingen worden gebruikt om efficiëntere productieprocessen te realiseren? Met dit project wil het consortium deze ML-structuur inzichtelijk maken; ten tweede ML beschikbaar maken voor MKB; ten derde samen onderzoeken hoe ML voor vision industrieel kan worden toegepast middels drie casussen en ten vierde de opgedane kennis borgen en verspreiden binnen MKB en onderwijs. Het project is een samenwerking tussen lectoraten mechatronica en ambient intelligence van Saxion, Computer Vision & Data Science van NHL Stenden. De participerende bedrijven zijn actief als hightech systeemontwikkelaar, kennis-toeleverancier en/of eindgebruiker als productiebedrijf. Daarnaast zijn het Smart Industry Fieldlab TValley en brancheorganisatie BOOST betrokken. Dit project zal kennis ontwikkelen ten behoeve van het adequaat toepassen van Machine Learning algoritmes in visionapplicaties.
De fysiotherapie staat onder toenemende druk, daarom is er een noodzaak om de zorg effectiever en efficienter in te richten. Dit project onderzoekt of de toepassing van technologieën als augmented videoconferencing (integratie van sensoren in videoconsulten) de fysiotherapiebehandeling effectiever en efficiënter kan maken.
