1,140 research outputs found

    SHELDON Smart habitat for the elderly.

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    An insightful document concerning active and assisted living under different perspectives: Furniture and habitat, ICT solutions and Healthcare

    Location estimation in smart homes setting with RFID systems

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    Indoor localisation technologies are a core component of Smart Homes. Many applications within Smart Homes benefit from localisation technologies to determine the locations of things, objects and people. The tremendous characteristics of the Radio Frequency Identification (RFID) systems have become one of the enabler technologies in the Internet of Things (IOT) that connect objects and things wirelessly. RFID is a promising technology in indoor positioning that not only uniquely identifies entities but also locates affixed RFID tags on objects or subjects in stationary and real-time. The rapid advancement in RFID-based systems has sparked the interest of researchers in Smart Homes to employ RFID technologies and potentials to assist with optimising (non-) pervasive healthcare systems in automated homes. In this research localisation techniques and enabled positioning sensors are investigated. Passive RFID sensors are used to localise passive tags that are affixed to Smart Home objects and track the movement of individuals in stationary and real-time settings. In this study, we develop an affordable passive localisation platform using inexpensive passive RFID sensors. To fillful this aim, a passive localisation framework using minimum tracking resources (RFID sensors) has been designed. A localisation prototype and localisation application that examined the affixed RFID tag on objects to evaluate our proposed locaisation framework was then developed. Localising algorithms were utilised to achieve enhanced accuracy of localising one particular passive tag which that affixed to target objects. This thesis uses a general enough approach so that it could be applied more widely to other applications in addition to Health Smart Homes. A passive RFID localising framework is designed and developed through systematic procedures. A localising platform is built to test the proposed framework, along with developing a RFID tracking application using Java programming language and further data analysis in MATLAB. This project applies localisation procedures and evaluates them experimentally. The experimental study positively confirms that our proposed localisation framework is capable of enhancing the accuracy of the location of the tracked individual. The low-cost design uses only one passive RFID target tag, one RFID reader and three to four antennas

    How Low Can You Go? Performance Trade-offs in Low-Resolution Thermal Sensors for Occupancy Detection: A Systematic Evaluation

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    We contribute by systematically analysing the performance trade-offs, costs (privacy loss and deployment cost) and limits of low-resolution thermal array sensors for occupancy detection. First, to assess performance limits, we manipulate the frame rate and resolution of images to establish the lowest possible values where reliable occupancy information can be captured. We also assess the effect of different viewing angles on the performance. We analyse performance using two datasets, an open-source dataset of thermal array sensor measurements (TIDOS) and a proprietary dataset that is used to validate the generality of the findings and to study the effect of different viewing angles. Our results show that even cameras with a 4x2 resolution - significantly lower than what has been used in previous research - can support reliable detection, as long as the frame rate is at least 4 frames per second. The lowest tested resolution, 2x2, can also offer reliable detection rates but requires higher frame rates (at least 16 frames per second) and careful adjustment of the camera viewing angle. We also show that the performance is sensitive to the viewing angle of the sensor, suggesting that the camera's field-of-view needs to be carefully adjusted to maximize the performance of low-resolution cameras. Second, in terms of costs, using a camera with only 4x2 resolution reveals very few insights about the occupants' identity or  behaviour, and thus helps to preserve their privacy. Besides privacy, lowering the resolution and frame rate decreases manufacturing and operating costs and helps to make the solution easier to adopt. Based on our results, we derive guidelines on how to choose sensor resolution in real-world deployments by carrying out a small-scale trade-off analysis that considers two representative buildings as potential deployment areas and compares the cost, privacy and accuracy trade-offs of different resolutions.Peer reviewe

    Implementing and Evaluating a Wireless Body Sensor System for Automated Physiological Data Acquisition at Home

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    Advances in embedded devices and wireless sensor networks have resulted in new and inexpensive health care solutions. This paper describes the implementation and the evaluation of a wireless body sensor system that monitors human physiological data at home. Specifically, a waist-mounted triaxial accelerometer unit is used to record human movements. Sampled data are transmitted using an IEEE 802.15.4 wireless transceiver to a data logger unit. The wearable sensor unit is light, small, and consumes low energy, which allows for inexpensive and unobtrusive monitoring during normal daily activities at home. The acceleration measurement tests show that it is possible to classify different human motion through the acceleration reading. The 802.15.4 wireless signal quality is also tested in typical home scenarios. Measurement results show that even with interference from nearby IEEE 802.11 signals and microwave ovens, the data delivery performance is satisfactory and can be improved by selecting an appropriate channel. Moreover, we found that the wireless signal can be attenuated by housing materials, home appliances, and even plants. Therefore, the deployment of wireless body sensor systems at home needs to take all these factors into consideration.Comment: 15 page

    Smart furniture as a component of a smart city-definition based on key technologies specification

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    There are dozens of definitions of smart furniture with meanings that vary greatly. Thus, the aim of this paper is to provide an exact definition of the phrase ``smart furniture'' based on literature and patent analysis. Why a definition? Because by providing a good definition, we have a statement that captures the meaning, the use, the function, and the essence of a term or a concept and allows the impacts on stakeholders to be described. A literature search was undertaken between 20 July 2018 and 31 August 2018, and the databases searched included SCOPUS, Web of Science, and IEEE Xplore (1998 2017), which were searched by keywords that included the phrase ``smart furniture.'' Patent searching was performed in the ESPACENET database, where 226 articles from scientific databases and 737 patent applications were examined. After the application of strict criteria, we obtained 23 articles and six patents containing meaningful definitions of smart furniture. Based on the results, smart furniture should be defined as designed, networked furniture that is equipped with an intelligent system or is controller operated with the user's data and energy sources. Smart furniture needs to have the ability to communicate and anticipate a user's needs using a plurality of sensors and actuators inside the user's environment, resulting in user-adapted furniture. The research results and discussion presented in this paper are based on the recognition that the smart furniture research has great policymaking, technological, and economy potential while contributing to the user's wellbeing and Quality of Life (QoL). This paper indicates that the collaboration between the ICT and social-economic research has to be initiated and consolidated in a sustainable way or in an environment that satisfies the needs expressed by the user.This work supported in part by the LTC INTER COST, Evaluation of the Potential for Reducing Health and Social Expenses for Elderly People Using the Smart Environment, through the Ministry of Education, Youth and Sports, Czech Republic, under Project LTC18035, in part by the Spanish Ministry of Science and University under Project TIN2016-75850-R, in part by the Universiti Teknologi Malaysia (UTM) under Research University Grant Vot-20H04, in part by the Malaysia Research University Network (MRUN) under Grant Vot 4L876, and in part by the Fundamental Research Grant Scheme (FRGS) through the Ministry of Education Malaysia under Grant Vot 5F073
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