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1

Marak, Salma B., and Dinesh V. Rojatkar. "e-Home Assistant." International Journal of Trend in Scientific Research and Development Volume-1, Issue-6 (October 31, 2017): 782–85. http://dx.doi.org/10.31142/ijtsrd4674.

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Rocha, Ana Patrícia, Maksym Ketsmur, Nuno Almeida, and António Teixeira. "An Accessible Smart Home Based on Integrated Multimodal Interaction." Sensors 21, no. 16 (August 13, 2021): 5464. http://dx.doi.org/10.3390/s21165464.

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Our homes are becoming increasingly sensorized and smarter. However, they are also becoming increasingly complex, making accessing them and their advantages difficult. Assistants have the potential for improving the accessibility of smart homes, by providing everyone with an integrated, natural, and multimodal way of interacting with the home’s ecosystem. To demonstrate this potential and contribute to more environmentally friendly homes, in the scope of the project Smart Green Homes, a home assistant highly integrated with an ICT (Information and communications technology) home infrastructure was developed, deployed in a demonstrator, and evaluated by seventy users. The users’ global impression of our home assistant is in general positive, with 61% of the participants rating it as good or excellent overall and 51% being likely or very likely to recommend it to others. Moreover, most think that the assistant enhances interaction with the smart home’s multiple devices and is easy to use by everyone. These results show that a home assistant providing an integrated view of a smart home, through natural, multimodal, and adaptive interaction, is a suitable solution for enhancing the accessibility of smart homes and thus contributing to a better living ambient for all of their inhabitants.
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Ambulkar, Pradnya. "Home Automation Using Google Assistance." International Journal for Research in Applied Science and Engineering Technology 10, no. 2 (February 28, 2022): 676–80. http://dx.doi.org/10.22214/ijraset.2022.40319.

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Abstract: This document has an automation proposal using voice via Google Assistant. Home Automation or Domestic a household automation term invented by Jim Hill has been significantly evolved. The Apple Home Kit is also significantly more expensive, over $100 (USD) more than the Google Home for a basic setup. Philips Hue, a smart light controlled by Google Assistant, Amazon Echo and Siri, Apple's voice assistant, costs around $145 (USD). So overall we can see here that to make our home smart we have to invest a lot, say around $250 (USD) for a basic setup. What if we could automate our home indoors (Smartphone cost is not included as it's supposed to belong to every individual these days) $10 (USD) and you can control up to 8 devices at the Google assistant help? Well, this document describes the implementation of such a system. Keywords: IOT, Nodemcu, Relay board, Google Assistance, IFTTT
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Chkroun, Merav, and Amos Azaria. "A Safe Collaborative Chatbot for Smart Home Assistants." Sensors 21, no. 19 (October 6, 2021): 6641. http://dx.doi.org/10.3390/s21196641.

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Smart home assistants, which enable users to control home appliances and can be used for holding entertaining conversations, have become an inseparable part of many people’s homes. Recently, there have been many attempts to allow end-users to teach a home assistant new commands, responses, and rules, which can then be shared with a larger community. However, allowing end-users to teach an agent new responses, which are shared with a large community, opens the gate to malicious users, who can teach the agent inappropriate responses in order to promote their own business, products, or political views. In this paper, we present a platform that enables users to collaboratively teach a smart home assistant (or chatbot) responses using natural language. We present a method of collectively detecting malicious users and using the commands taught by the malicious users to further mitigate activity of future malicious users. We ran an experiment with 192 subjects and show the effectiveness of our platform.
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Bhanuabhiram, K., L. Tharun Kumar, and N. Srinivasan. "Google Assistant Controlled Home Automation." Journal of Computational and Theoretical Nanoscience 16, no. 8 (August 1, 2019): 3259–64. http://dx.doi.org/10.1166/jctn.2019.8173.

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World’s interest for power had become 85% somewhere in the range of 2010 and 2017 this expansion is more than the present all out utilization of power in India, USA, Japan, Australia consolidated. We can’t diminish the power development rate however we can decrease the measure of power squandered every year by killing our home machines when not being used. This venture shows a plan and model of Home Automation framework that will utilize ESP8266 Wi-Fi module as a system supplier in associating with different machines. The proposed framework has two principle segments. The primary fundamental part is Arduino, which controls and oversees contribution of Wi-Fi module. The other principle segment is Wi-Fi module through Wi-Fi module a web server can be added to the module which will help in controlling of gadgets over Internet. One server can oversee numerous equipment interface modules as long as it exists on Wi-Fi arrange inclusion. It bolsters a wide scope of home mechanization gadgets like power the board segments, and security parts. We need to make this automation framework incorporated and misleadingly astute. The framework is executed utilizing common family apparatuses Natural language voice directions are given to the Google Assistant and with the assistance of IFTTT (If This Then That) application and the Blynk application the directions are decoded and after that sent to the microcontroller, the microcontroller thusly controls the transfers associated with it as required, turning the gadget associated with the separate hand-off On or OFF according to the clients demand to the Google Assistant. The microcontroller utilized is Node MCU (ESP8266) and the correspondence between the microcontroller and the application is built up by means of Wi-Fi.
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Harikrishnan, K. S., and Daniel Glad Stephen. "Hospital/Home Medical Assistant Robot." IOP Conference Series: Materials Science and Engineering 912 (September 12, 2020): 062015. http://dx.doi.org/10.1088/1757-899x/912/6/062015.

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Rishi, Rajesh, and Pinki Doloi. "Home Automation Using Google Assistant." IJIREEICE 9, no. 6 (June 30, 2021): 116–27. http://dx.doi.org/10.17148/ijireeice.2021.9626.

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Xu, Rong, Min Zhuo, Zhikai Yang, and Jie Dong. "Experiences with Assisted Peritoneal Dialysis in China." Peritoneal Dialysis International: Journal of the International Society for Peritoneal Dialysis 32, no. 1 (January 2012): 94–101. http://dx.doi.org/10.3747/pdi.2010.00213.

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ObjectiveAbout half the patients on peritoneal dialysis (PD) in China need to be assisted by family members or home assistants. We explored whether these patients have a higher risk for peritonitis and death compared with self-care PD patients.MethodsWe prospectively followed 313 incident PD patients until death or censoring. This cohort was divided into assisted and self-care PD groups according to the independence of bag exchange. Data on baseline demographics, Charlson comorbidity index, biochemistry, and residual renal function were recorded during the first 3 – 6 months. The outcome variables were first episode of peritonitis and all-cause mortality.ResultsOf the 313 patients in this cohort study, 122 needed assistance in performing bag exchanges (86 from a family member, 36 from a home assistant); the remaining 191 patients did not need assistance. During a follow-up period averaging 44.5 months, 122 patients developed a first episode of peritonitis, and 135 patients died. Compared with patients having a family assistant, those with a home assistant had similar peritonitis-free and survival times, but a higher risk of mortality after adjustments for variables such as age, sex, Charlson comorbidity score, hemoglobin, serum albumin, and residual renal function. Furthermore, compared with self-care patients, assisted patients overall had a similar peritonitis-free time, but a higher risk of mortality, even after adjusting for covariates.ConclusionsBased on our single-center experience in China, we conclude that assisted PD is a good option for patients with poor self-care ability. This result provides evidence for recruiting patients who need assistance to PD programs in China.
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Thakor, Jitendra. "Home Automation over the Home Assistant using Raspberry Pi." International Journal for Research in Applied Science and Engineering Technology 8, no. 7 (July 31, 2020): 359–65. http://dx.doi.org/10.22214/ijraset.2020.7059.

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Dempsey, P. "The Teardown: Google Home personal assistant." Engineering & Technology 12, no. 3 (April 1, 2017): 80–81. http://dx.doi.org/10.1049/et.2017.0330.

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Bertrand, Rosanna M., Tracy L. Porchak, Therese J. Moore, Donna T. Hurd, Victoria Shier, Rebecca Sweetland, and Sandra F. Simmons. "The Nursing Home Dining Assistant Program." Journal of Gerontological Nursing 37, no. 2 (August 23, 2010): 34–43. http://dx.doi.org/10.3928/00989134-20100730-04.

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Riddell, Heather, and Christopher Fenner. "Hey Google: A thematic analysis of Twitter users’ comments on the privacy of AI devices in the home." Explorations in Media Ecology 20, no. 4 (December 1, 2021): 457–77. http://dx.doi.org/10.1386/eme_00111_1.

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The advancement of technology has been accompanied by the rise of data breaches and privacy concerns. The integration of artificial intelligence (AI)-based virtual assistants into society has led to smart homes that enable users to complete commands instantly. This project uses the diffusion of innovation theory to explain why consumers adopt the technology. A thematic analysis was conducted on Twitter news stories, and open coding showed a strong negative reaction to the stories, with users concluding that privacy was too essential to purchase a virtual assistant for their home. These findings have implications for the future rate of adoption of AI and virtual assistant technology.
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Wiyanto, Wiyanto, and Yayan Oktavianti. "Prototype Smart Home Pengendali Lampu Dan Gerbang Otomatis Berbasis IoT Pada Sekolah Islam Pelita Insan Menggunakan Microcontroller Nodemcu V3." UNISTEK 8, no. 1 (February 28, 2021): 68–75. http://dx.doi.org/10.33592/unistek.v8i1.1209.

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Current technological developments have penetrated into human life, such as the development of a smart home called a smart home, that can provide convenience, comfort, safety and efficiency for users. Internet of Things (IoT) can be used in smart homes to control electronic equipment such as lights and home gates. This research designed an automatic controller and light gate based IoT (Internet of Things) smart home system using a NodeMCU microcontroller with a prototype method that aims to save electricity, make it effective and efficient, and make it easier for schoolkeepers to turn on lights and control the gate automatically through the Google assistant. The results of this study are in the form of an automatic light and gate control system using the Google assistant application based on the Internet of Things Using a NodeMCU v3 microcontroller. Can be concluded with the automatic light and gate control system using the google assistant application by giving commands to the google assistant connected to the NodeMCU V3 microcontroller, it can make it easier for school administrators to make efficient and efficient lights or gates using the google assistant application and can facilitate school administrators to maintain the security of the Internet-based school of Things.
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Perumal, Sujitha, and Mohammed Saqib Javid. "Voice Enabled Smart Home Assistant for Elderly." International Journal of Computer Sciences and Engineering 7, no. 11 (November 30, 2019): 30–37. http://dx.doi.org/10.26438/ijcse/v7i11.3037.

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Kadali, Bhavyasri, Neha Prasad, Pranaya Kudav, and Manoj Deshpande. "Home Automation Using Chatbot and Voice Assistant." ITM Web of Conferences 32 (2020): 01002. http://dx.doi.org/10.1051/itmconf/20203201002.

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In a world with ever increasing needs for comfort, human race is relying more and more on technological advancements to find solutions to their problems. Home Automation Systems have become a go-to arena in the recent years. In the following paper, we propose a Home Automation system that uses a wholesome blending of some technologies like Internet of Things, Natural Language Processing and Machine Learning. The prime feature of this system is that, it provides two modes of communication to the user : Text and Voice. The text input from the user will be given via a Chatbot Application and the voice input from the user will be given via a voice assistant. The input will undergo Natural Language Processing to find the action that the user wants the system to perform. The IoT component, Raspberry Pi would perform the actuations in the form of switching On or Off of Lights and Fans of a room in the house.
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Yamazaki, Kimitoshi, Ryohei Ueda, Shunichi Nozawa, Mitsuharu Kojima, Kei Okada, Kiyoshi Matsumoto, Masaru Ishikawa, Isao Shimoyama, and Masayuki Inaba. "Home-Assistant Robot for an Aging Society." Proceedings of the IEEE 100, no. 8 (August 2012): 2429–41. http://dx.doi.org/10.1109/jproc.2012.2200563.

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Malmström, Raija, Riitta Muroma-Karttunen, Meeri Kilpiä, and Eero Honkanen. "Experiences on Home Hemodialysis without an Assistant." Hemodialysis International 7, no. 1 (February 2003): 73–104. http://dx.doi.org/10.1046/j.1492-7535.2003.01277.x.

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Munteanu, Laurentiu, Marius Cornel Suvar, and Gheorghe Daniel Florea. "Residential security through the Home Assistant Platform." MATEC Web of Conferences 354 (2022): 00008. http://dx.doi.org/10.1051/matecconf/202235400008.

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The etymology of the word safety means: lack of danger; feeling of peace and confidence; shelter from any danger; feeling of security. A security system of goods, values and protection of people can be implemented through an automated platform, under the name of Home Assistant. This server software application can communicate with an easy control system for fast and two-way access, which can be mounted to a restricted main entrance. The automatic opening of the access door is controlled both by stand-alone RFID (Radio-Frequency Identification) modules, which act on an electric closing mechanism, and by an automation system configured in the Home Assistant application. The ultimate goal is the security of the premises through a system that can operate both locally and online via internet connection. The research methodology was based on the study of intelligent applications for residential access, described in the literature, aiming at integration into the open-source HA platform, by developing new code sequences. I come with this paper in support of those who want to bring an improvement in the existing automation system, respectively to encourage those who want an automated residence at a higher level.
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Wu, Han, Tao Wang, Tuo Dai, Xiaoyu Wang, Yuanzhen Lin, and Yizhou Wang. "Let home nursing assistant robots see your heart rate." International Journal of Crowd Science 2, no. 3 (September 3, 2018): 198–211. http://dx.doi.org/10.1108/ijcs-09-2018-0023.

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Purpose This paper aims to design a vision-based non-contact real-time accurate heart rate (HR) measurement framework for home nursing assistant. Design/methodology/approach The study applied Second-Order Blind Signal Identification (SOBI) algorithm to extract remote HR signal and analyzed it with Fast Fourier Transform (FFT). Multiple regions of interest are chosen and analyzed to obtain a more accurate result. Findings An accurate non-contact hear rate (HR) measurement framework is proposed and proved to be efficient. Originality/value The contributions of this HR measurement framework are as follows: accurate measurement of HR, real-time performance, robust under various scenes such as conversation, lightweight computation which is suitable and necessary for home nursing assistance. This framework is designed to be flexibly used in various real-life scenes such as domestic health assistance and affectively intelligent agents and is proved to be robust under such scenes.
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Lalit Kumar. "Desktop Voice Assistant Using Natural Language Processing (NLP)." International Journal for Modern Trends in Science and Technology 6, no. 12 (December 15, 2020): 332–35. http://dx.doi.org/10.46501/ijmtst061262.

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Voice assistants are the great innovation in the field of AI that can change the way of living of the people in a different manner. the voice assistant was first introduced on smartphones and after the popularity it got. It was widely accepted by all. Initially, the voice assistant was mostly being used in smartphones and laptops but now it is also coming as home automation and smart speakers. Many devices are becoming smarter in their own way to interact with human in an easy language. The Desktop based voice assistant are the programs that can recognize human voices and can respond via integrated voice system. This paper will define the working of a voice assistants, their main problems and limitations. In this paper it is described that the method of creating a voice assistant without using cloud services, which will allow the expansion of such devices in the future.
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Marx, M. S., D. Wolf, L. Pheng, V. Walker, A. Elises, R. C. Feldman, P. Werner, J. Cohen-Mansfield, S. Dubroff, and S. Lipson. "Eye Care in a Nursing Home." Journal of Visual Impairment & Blindness 85, no. 3 (March 1991): 105–7. http://dx.doi.org/10.1177/0145482x9108500305.

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This article describes an example of an in-house eye care clinic for elderly nursing home residents. The success of this clinic is due not to any one person, but to the combined efforts of a team: a clinic supervisor, a nursing assistant, a medical assistant, an ophthalmic technician, and an ophthalmologist. The implications of providing good and effective eye care to nursing home residents are discussed.
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Linan-Reyes, Matias, Joaquin Garrido-Zafra, Aurora Gil-de-Castro, and Antonio Moreno-Munoz. "Energy Management Expert Assistant, a New Concept." Sensors 21, no. 17 (September 2, 2021): 5915. http://dx.doi.org/10.3390/s21175915.

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In recent years, interest in home energy management systems (HEMS) has grown significantly, as well as the development of Voice Assistants that substantially increase home comfort. This paper presents a novel merging of HEMS with the Assistant paradigm. The combination of both concepts has allowed the creation of a high-performance and easy-to-manage expert system (ES). It has been developed in a framework that includes, on the one hand, the efficient energy management functionality boosted with an Internet of Things (IoT) platform, where artificial intelligence (AI) and big data treatment are blended, and on the other hand, an assistant that interacts both with the user and with the HEMS itself. The creation of this ES has made it possible to optimize consumption levels, improve security, efficiency, comfort, and user experience, as well as home security (presence simulation or security against intruders), automate processes, optimize resources, and provide relevant information to the user facilitating decision making, all based on a multi-objective optimization (MOP) problem model. This paper presents both the scheme and the results obtained, the synergies generated, and the conclusions that can be drawn after 24 months of operation.
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Hanani, Ajib, and Mokhamad Amin Hariyadi. "Smart Home Berbasis IoT Menggunakan Suara Pada Google Assistant." Jurnal Ilmiah Teknologi Informasi Asia 14, no. 1 (April 18, 2020): 49. http://dx.doi.org/10.32815/jitika.v14i1.456.

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Penelitian ini membangun sebuah Smart Home berbasis IoT menggunakan suara pada Google Assistant. Hal ini dibutuhkan sebagai solusi untuk orang sakit yang berada di kursi roda/tempat tidur atau orang disabilitas tetapi dapat berbicara atau orang lanjut usia yang tidak dapat mencapai saklar agar dapat menghidupkan/mematikan perangkat rumah. Selain itu, agar dapat mengontrol perangkat rumah dari jarak yang sangat jauh. Sistem yang dibangun menggunakan perintah suara pada aplikasi Google Assistant di android. Google Assistant mengubah perintah suara menjadi teks. Teks tersebut kemudian diteruskan dari Google Assistant ke Webhooks oleh IFTTT. Webhooks akan melakukan request ke HTTP RESTful API. Dengan library phpMQTT yang terdapat di HTTP RESTful API, perintah di publish ke MQTT Broker. ESP32 Dev Kit sebagai microcontroller yang terhubung dengan internet menerima perintah dari MQTT Broker untuk menyalakan atau mematikan lampu yang ada di rumah. Pada pengujian sistem telah berhasil menyalakan dan mematikan lampu dengan perintah suara menggunakan Google Assistant.
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Chung, Gawon. "Nursing Assistant Views on Nursing Home Regulatory Inspection." Journal of Applied Gerontology 31, no. 3 (October 27, 2010): 336–53. http://dx.doi.org/10.1177/0733464810386369.

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Jimenez, Clara, Edgar Saavedra, Guillermo del Campo, and Asuncion Santamaria. "Alexa-Based Voice Assistant for Smart Home Applications." IEEE Potentials 40, no. 4 (July 2021): 31–38. http://dx.doi.org/10.1109/mpot.2020.3002526.

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Kumer, S. V. Aswin, P. Kanakaraja, A. Punya Teja, T. Harini Sree, and T. Tejaswni. "Smart home automation using IFTTT and google assistant." Materials Today: Proceedings 46 (2021): 4070–76. http://dx.doi.org/10.1016/j.matpr.2021.02.610.

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Alrumayh, Abrar S., Sarah M. Lehman, and Chiu C. Tan. "Context aware access control for home voice assistant in multi-occupant homes." Pervasive and Mobile Computing 67 (September 2020): 101196. http://dx.doi.org/10.1016/j.pmcj.2020.101196.

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Stoica, Anda, Tibor Kadar, Camelia Lemnaru, Rodica Potolea, and Mihaela Dînşoreanu. "Intent Detection and Slot Filling with Capsule Net Architectures for a Romanian Home Assistant." Sensors 21, no. 4 (February 9, 2021): 1230. http://dx.doi.org/10.3390/s21041230.

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As virtual home assistants are becoming more popular, there is an emerging need for supporting languages other than English. While more wide-spread or popular languages such as Spanish, French or Hindi are already integrated into existing home assistants like Google Home or Alexa, integration of other less-known languages such as Romanian is still missing. This paper explores the problem of Natural Language Understanding (NLU) applied to a Romanian home assistant. We propose a customized capsule neural network architecture that performs intent detection and slot filling in a joint manner and we evaluate how well it handles utterances containing various levels of complexity. The capsule network model shows a significant improvement in intent detection when compared to models built using the well-known Rasa NLU tool. Through error analysis, we observe clear error patterns that occur systematically. Variability in language when expressing one intent proves to be the biggest challenge encountered by the model.
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Koon, Lyndsie M., Kenneth Blocker, and Wendy Rogers. "VOICE-ACTIVATED DIGITAL ASSISTANTS: PERCEPTIONS FROM NOVICE USERS WITH LONG-TERM MOBILITY DISABILITY." Innovation in Aging 3, Supplement_1 (November 2019): S759—S760. http://dx.doi.org/10.1093/geroni/igz038.2791.

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Abstract Voice-activated digital assistants (e.g., Amazon Echo, Google Home) are an emerging technology that have great potential to provide support for adults aging with a long-term mobility disability. Digital assistant technologies allow the user to perform a variety of everyday tasks and activities through voice interactions. Such tasks may include environmental control (e.g., turning on/off lights, voice-activated temperature control); supporting self-health management (e.g., providing medication reminders, encouraging physical activity engagement); and fostering opportunities for social engagement (e.g., messaging/calling others, playing games remotely). This presentation will focus on the perceived facilitators and barriers to digital assistant use in the home among adults aging with mobility disabilities. The findings provide design guidelines and insight for intervention implementation for the use of these technologies for the target population.
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Holmberg, Bodil, Ingrid Hellström, and Jane Österlind. "Elements of assisted bodily care: Ethical aspects." Nursing Ethics 27, no. 6 (May 7, 2020): 1377–95. http://dx.doi.org/10.1177/0969733020914348.

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Background: Many frail older persons who die in Swedish nursing homes need assisted bodily care. They must surrender their bodies to the authority of assistant nurses, which may affect their autonomy and dignity of identity. While assistant nurses claim to support older persons’ wishes, older persons claim they have to adapt to assistant nurses' routines. The provider–receiver incongruence revealed here warrants investigation. Aim: To describe the elements of assisted bodily care, as performed in a nursing home. Research design: Data were collected through thirty-nine observations of assisted bodily care, analyzed with qualitative content analysis. Participants and research context: Seventeen older persons and twenty-two assistant nurses from a Swedish nursing home. Ethical considerations: The research was conducted in line with the Declaration of Helsinki, further approved by the regional ethics committee. Findings: Findings show that assisted bodily care consists of assistant nurses’ practical work, performed at a high tempo. Assistant nurses still attempt to adapt this work to the older persons’ wishes for self-determination, taking into account their day-to-day state of health. In spite of time pressure and occasional interruptions, there is room for consideration and affection in assisted bodily care. Discussion: Assistant nurses try to promote older persons’ dignity of identity, but sometimes fail, possibly due to lack of time. They nevertheless seem to know the older persons well enough to adapt the assisted bodily care according to their preferences and to support self-determination. This indicates that openness to older persons’ lifeworlds may be more important than the amount of time available. Conclusion: Nursing home contexts might benefit from adopting a person-centered palliative care perspective, highlighting the value of relationships and shared decision-making. If so, older persons and assisted nurses could agree on practices and goals in assisted bodily care beforehand. Such routines may be time-saving and beneficial to all.
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Helgheim, Berit Irene, and Birgithe Sandbaek. "Who Is Doing What in Home Care Services?" International Journal of Environmental Research and Public Health 18, no. 19 (October 7, 2021): 10504. http://dx.doi.org/10.3390/ijerph181910504.

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(1) Background: This paper investigates the distribution of work hours by activity, for the main staff categories in home care services in three rural Norwegian municipalities. In Norway these categories are registered nurses, assistant nurses and assistant health workers. (2) Methods: The three categories of home care staff recorded 20,964 eligible observations over 8 weeks. We identified 19 activities, which were recorded. The majority of staff used a smartphone application for the time measuring, while some staff used a manual form for reporting purposes. (3) Results: The registered nurses (RNs) spent 32% of their time on direct patient work, while driving accounted for 18%. Direct patient work and driving accounted for the majority of activities performed by assistant nurses (48% and 29%, respectively) and assistant health workers (70% and 17%, respectively). (4) Conclusions: The demand for home care services is increasing in terms of both size and complexity. Simultaneously, there is a growing shortage of skilled staff. RNs is the group with the least face-to-face time with patients. To meet the patients’ needs, it is necessary to discuss and modify existing home care service systems in order to use resources appropriately and effectively.
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Filippova, O. M., A. M. Bessmertny, M. N. Kuzin, and S. Yu Petrov. "Prospects of using the TVGD-02 tonometer for assisted monitoring of intraocular pressure at home." Russian Ophthalmological Journal 14, no. 2 (June 20, 2021): 27–35. http://dx.doi.org/10.21516/2072-0076-2021-14-2-27-35.

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Purpose: to evaluate the safety and convenience of self-using the intraocular pressure tonometer TVGD-02 at home with no participation of medical professionals. Material and methods. 42 people formed 30 pairs: a patient and an assistant. In 9 pairs, each person played both roles. The participants practiced the technique of transpalpebral measurement of intraocular pressure (IOP) at home, and, as assistants, measured IOP of their partner patients. All subjects were asked to fill in a questionnaire to evaluate the convenience and safety of the tonometer use by a 5-point system. Results. The assistant users, aged 22 to 83 (ave. 59.68 ± 17.20 years) had diverse educational levels. Of the patient users, aged 22 to 82 (ave. 60.64 ± 17.10 years), 82.14 % had ocular pathology, while 35.7 % had glaucoma with concomitant pathology. In 100 % of cases, the participants required no professional assistance to properly prepare the tonometer for operation and perform IOP measurement. The accuracy and reproducibility of measurement results significantly increased with the assistants’ gaining skills of operating the tonometer. On the 1st day, the data obtained in a series of measurements scattered for the control block within 2.07 ± 1.70 [7; 0] mm Hg, while the measured IOP of the patient scattered within 2.89 ± 19.10 [8; 0]. In contrast, on the 5th day, measurement accuracy increased significantly and the scatter dropped to 1.21 ± 0.72 [2; 0] and 0.85 ± 0.69 [2; 0] mm Hg, respectively. The users rated the ease of using the device at different staged from 4.21 ± 0.67 to 5.0 ± 0.0 points. Conclusion. Assisted transpalpebral tonometry with the TVGD-02 tonometer ensures an adequate assessment of IOP in patients at home. The principles of device operation and the technique can be learned and skills can be gained without the participation of medical personnel.
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Kadylak, Travis, Maya Malecki, Leonardo Galoso, Saahithya Gowrishankar, Amy Brown, Ramavarapu Sreenivas, and Wendy Rogers. "Exploring Use of Digital Home Assistants for Older Adults: A Demonstration Project." Innovation in Aging 5, Supplement_1 (December 1, 2021): 423–24. http://dx.doi.org/10.1093/geroni/igab046.1643.

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Abstract Emerging digital home assistant technology has potential to support older adults in their homes. Voice-activated assistants can be used for entertainment, environmental control, physical activities, health management, and social engagement. However, many older adults have limited experience with these devices, which are not designed with them in mind. We conducted a demonstration project to explore how seven older adult assisted and independent living residents interacted with digital assistants over four months. We conducted monthly semi-structured telephone interviews and pre/post questionnaires. Participants desired to use their devices to communicate with others, and for a range of health activities, including nutrition tracking, medication management, and health information searching. However, numerous usability barriers emerged. Some participants perceived their device as a social companion. These findings indicate that older adults are willing to use digital assistants for various activities that may enhance independence, although instructional and training materials are needed to support their use.
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Holmberg, Bodil, Ingrid Hellström, and Jane Österlind. "End-of-life care in a nursing home: Assistant nurses’ perspectives." Nursing Ethics 26, no. 6 (June 27, 2018): 1721–33. http://dx.doi.org/10.1177/0969733018779199.

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Background: Worldwide, older persons lack access to palliative care. In Sweden, many older persons die in nursing homes where care is provided foremost by assistant nurses. Due to a lack of beds, admission is seldom granted until the older persons have complex care needs and are already in a palliative phase when they move in. Objective: To describe assistant nurses’ perspectives of providing care to older persons at the end of life in a nursing home. Research design: Data were collected in semi-structured individual interviews and analyzed with inductive qualitative content analysis. Participants and research context: Seven assistant nurses from a nursing home in Sweden were randomly selected. Ethical consideration: The research was approved by the local ethics committee. Results: Three main categories emerged; “Death a natural part of life”; “The older person’s well-being”; and “Care in the moment of death”; and seven sub-categories. The assistant nurses described themselves as knowing the older persons well enough to provide good end-of-life care. This was achieved by making small-talk while providing daily care. Relying on experience-based knowledge, they strove to provide end-of-life care built upon respect and engagement with the ambition to strengthen older persons’ dignity, for example, by lowering the tempo of care at the end of life, in spite of organizational restrictions. Discussion: The assistant nurses offered attentive end-of-life care, focusing upon bodily care. The existential needs of the older persons were not foregrounded. Conclusion: To develop their work, and to promote an ethical foundation for such care, assistant nurses might need support and education to be able to offer a care more in line with the aims of palliative care. Furthermore, the organization of care needs to promote, not impede, the realization of this development.
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Fachri Rizal, Isni, I. Wayan Agus Arimbawa, and Royana Afwani. "Rancang Bangun Digital Home Assistant Dengan Perintah Suara Menggunakan Raspberry Pi Dan Smart Phone." Journal of Computer Science and Informatics Engineering (J-Cosine) 2, no. 2 (December 24, 2018): 127–34. http://dx.doi.org/10.29303/jcosine.v2i2.84.

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Digital home assistant merupakan salah satu bagian dari teknologi smart home. Smart home merupakan salah satu riset teknologi yang berfokus untuk home automation, sehingga interaksi antara manusia dengan rumah menjadi lebih mudah dan peraktis. Salah satu interaksi yang dapat dilakukan yaitu menggunakan perintah suara. Saat ini teknologi digital home assistant dapat diimplementasikan dengan berbagai macam konsep dan berbagai macam alat. Salah satu alat yang dapat digunakan adalah smart phone. Smart phone merupakan alat komunikasi yang memiliki berbagai macam tools untuk memenuhi kebutuhan pengguna, salah satunya adalah tool yang ditawarkan oleh sistem operasi Android yaitu google speech API. Dengan google speech API kita dapat membuat aplikasi yang dapat memahami perkataan manusia. Agar peralatan elektronika di rumah dapat berkomunikasi dengan smart phone, digunakanlah micro controller yang dipasangkan pada elektronika di rumah. Beberapa micro controller yang dapat digunakan yaitu Raspberry Pi dan Arduino. Pada penelitian ini dibangun suatu digital home assistant dengan perintah suara menggunakan Raspberry Pi dan smart phone. Digital home assistant yang dibangun digunakan untuk pengendalian lampu, TV, dan AC. Google speech API digunakan pada smart phone untuk proses penerjemahan perintah suara yang diberikan oleh pengguna sistem. Hasil yang didapatkan untuk pengendalian lampu, TV dan AC dengan perintah suara menggunakan smart phone dan Raspberry Pi adalah sistem dapat berjalan dengan keberhasilan 90% dan waktu rata-rata eksekusi perintah mencapai 5.32 detik.
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Kadylak, Travis, Roshanak Khaleghi, Kenneth Blocker, Saahithya Gowrishankar, Widya Ramadhani, Lyndsie Koon, Ramavarapu Sreenivas, and Wendy Rogers. "Digital Home Assistant Health Applications for Older Adults With Long-Term Mobility Disabilities." Innovation in Aging 4, Supplement_1 (December 1, 2020): 600. http://dx.doi.org/10.1093/geroni/igaa057.2019.

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Abstract The aim of the current study was to evaluate the feasibility, usability, safety, and efficacy of digital home assistant health applications (e.g., meditation applications, medication reminders, hydration management) for older adults with mobility disabilities. We used a multi-pronged approach. First, we compiled, categorized, and assessed a list of commercially available health applications compatible with Amazon Alexa devices. We reviewed data from the National Health and Aging Trends Study and the ACCESS study to identify challenges that older adults with mobility disabilities face within the home. We also reviewed the literature on the acceptance and use of digital home assistant health applications by older adults. Lastly, we conducted user testing in a laboratory and in a home-simulation environment to assess usability of different health applications. Our results provide guidance for the implementation of digital home assistant health applications to support older adults with long-term mobility disabilities.
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Smith, Raymond, Julia Wood, Fiona Jones, Liezl Anderson, and Michael Hurley. "Active residents in care homes: A holistic approach to promoting and encouraging meaningful activity for residents living in care homes: Innovative Practice." Dementia 18, no. 5 (September 10, 2017): 1942–47. http://dx.doi.org/10.1177/1471301217727129.

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The active residents in care homes intervention aim to promote meaningful activity among care home residents. Residents, family members and staff from three residential care homes in South London are participating. It is a whole systems approach which involves formal and ‘on the floor’ training to empower care home staff to facilitate activity. Training is delivered by two occupational therapists, a physiotherapist and a rehabilitation assistant. This paper describes the active residents in care homes intervention, the evaluation methods and discusses some preliminary findings.
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Thomas, F. M., and R. Juliana. "Integrating novel state of the art techniques into generic Personal Assistants with Home Assistant functionality." International Journal of Computer Sciences and Engineering 06, no. 03 (April 30, 2018): 167–72. http://dx.doi.org/10.26438/ijcse/v6si3.167172.

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39

Fifit Alfiah, Budi Rahman, and Imelda. "Control System prototype Smart Home IoT based with MQTT method using Google Asisstant." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 4, no. 2 (April 20, 2020): 303–10. http://dx.doi.org/10.29207/resti.v4i2.1721.

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The internet of Things for Smart Home is here to offer convenience in controlling electrical devices or lectronic devices remotely by only giving voice commands that have been integrated with Google Assistant services, now traveling home in uncertain times no longer need to worry about turning on or turn off electrical appliances at home with a smart home. The design of this prototype tool implements lights and fans as electrical devices, in making smart home systems require a microcontroller namely the ESP8266 NodeMCU V3 CH340 module as MQTT Broker protocol, IFTTT as a subscriber, and the publisher Google Assistant using MTTQ (Message Queuing Telemetry Transport) method. MQTT used today is using a free cloud server provided by Adafruit. Based on the results of testing the prototype of the IoT-based smart home control system with the MQTT method using google assistant proved that the number of tests for Relay 1, Relay 2 and Relay 3 is six(6), succeeded 5 and failed 1 then the accuracy of success on Relay 1 testing was 88%. Only by giving the command "Ok Google turn on/off the lamp 1 or turn on/off a fan" to the Google Assistant installed on the Smartphone, lights and fans can be controlled remotely as long as NodeMCU ESP8266 gets an internet network.
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Leff, Ellen W., Gail L. Hagenbach, and Kathryn K. Marn. "Preventing Home Health Nursing Assistant Back and Shoulder Injuries." Joint Commission Journal on Quality Improvement 26, no. 10 (October 2000): 587–600. http://dx.doi.org/10.1016/s1070-3241(00)26050-1.

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41

Evans, Marc. "Care assistant regulation would help improve care home quality." Nursing Standard 28, no. 42 (June 18, 2014): 34. http://dx.doi.org/10.7748/ns.28.42.34.s40.

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42

Nabagiez, John P., Masood A. Shariff, Muhammad A. Khan, William J. Molloy, and Joseph T. McGinn. "Physician assistant home visit program to reduce hospital readmissions." Journal of Thoracic and Cardiovascular Surgery 145, no. 1 (January 2013): 225–33. http://dx.doi.org/10.1016/j.jtcvs.2012.09.047.

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43

Et.al, E. Shirisha. "IOT Based Home Security And Automation Using Google Assistant." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 6 (April 11, 2021): 117–22. http://dx.doi.org/10.17762/turcomat.v12i6.1275.

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Internet of Things (IOT) is an important technology that affects the internet and communication technology. IOT allows people and objects to be connected anytime, anywhere, in any way/shape and function. Earth's mechanical systems have become very popular in the last few decades and improved living conditions. This project provides the structure and model of an automated earth system. The most important feature is the Raspberry pi, which has an internal Wi-Fi module that allows you to control your device over the Internet. It supports a variety of earth tools, such as energy management systems. Besides, the application is built where the user can control the device using Google Assistant. The IOT project also aims to build a wireless home protection system that uses the ESP32 camera Node MCU module to send alerts to owners if anyone takes a picture of the door and sends it to the owner.
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Triyono, L., T. R. Yudantoro, S. Sukamto, and I. Hestinigsih. "VeRO: Smart home assistant for blind with voice recognition." IOP Conference Series: Materials Science and Engineering 1108, no. 1 (March 1, 2021): 012016. http://dx.doi.org/10.1088/1757-899x/1108/1/012016.

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45

Rogers, W. A., A. D. Fisk, M. A. Neerincx, J. Lindenberg, C. A. P. G. van der Mast, and O. A. Blanson Henkemans. "Usability of an Adaptive Computer Assistant that Improves Self-care and Health Literacy of Older Adults." Methods of Information in Medicine 47, no. 01 (2008): 82–88. http://dx.doi.org/10.3414/me9105.

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Summary Objectives: We developed an adaptive computer assistant for the supervision of diabetics’ self-care, to support limiting illness and need for acute treatment, and improve health literacy. This assistant monitors self-care activities logged in the patient’s electronic diary. Accordingly, it provides context-aware feedback. The objective was to evaluate whether older adults in general can make use of the computer assistant and to compare an adaptive computer assistant with a fixed one, concerning its usability and contribution to health literacy. Methods: We conducted a laboratory experiment in the Georgia Tech Aware Home wherein 28 older adults participated in a usability evaluation of the computer assistant, while engaged in scenarios reflecting normal and health-critical situations. We evaluated the assistant on effectiveness, efficiency, satisfaction, and educational value. Finally, we studied the moderating effects of the subjects’ personal characteristics. Results: Logging self-care tasks and receiving feedback from the computer assistant enhanced the subjects’ knowledge of diabetes. The adaptive assistant was more effective in dealing with normal and healthcritical situations, and, generally, it led to more time efficiency. Subjects’ personal characteristics had substantial effects on the effectiveness and efficiency of the two computer assistants. Conclusions: Older adults were able to use the adaptive computer assistant. In addition, it had a positive effect on the development of health literacy. The assistant has the potential to support older diabetics’ self care while maintaining quality of life.
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Carlin, Angela, Caomhan Logue, Jonathan Flynn, Marie H. Murphy, and Alison M. Gallagher. "Development and Feasibility of a Family-Based Health Behavior Intervention Using Intelligent Personal Assistants: Randomized Controlled Trial." JMIR Formative Research 5, no. 1 (January 28, 2021): e17501. http://dx.doi.org/10.2196/17501.

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Background Intelligent personal assistants such as Amazon Echo and Google Home have become increasingly integrated into the home setting and, therefore, may facilitate behavior change via novel interactions or as an adjunct to conventional interventions. However, little is currently known about their potential role in this context. Objective This feasibility study aims to develop the Intelligent Personal Assistant Project (IPAP) and assess the acceptability and feasibility of this technology for promoting and maintaining physical activity and other health-related behaviors in both parents and children. Methods This pilot feasibility study was conducted in 2 phases. For phase 1, families who were attending a community-based weight management project were invited to participate, whereas phase 2 recruited families not currently receiving any additional intervention. Families were randomly allocated to either the intervention group (received a smart speaker for use in the family home) or the control group. The IPAP intervention aimed to promote positive health behaviors in the family setting through utilization of the functions of a smart speaker and its linked intelligent personal assistant. Data were collected on recruitment, retention, outcome measures, intervention acceptability, device interactions, and usage. Results In total, 26 families with at least one child aged 5 to 12 years were recruited, with 23 families retained at follow-up. Across phase 1 of the intervention, families interacted with the intelligent personal assistant a total of 65 times. Although device interactions across phase 2 of the intervention were much higher (312 times), only 10.9% (34/312) of interactions were coded as relevant (related to diet, physical activity or well-being). Focus groups highlighted that the families found the devices acceptable and easy to use and felt that the prompts or reminders were useful in prompting healthier behaviors. Some further intervention refinements in relation to the timing of prompts and integrating feedback alongside the devices were suggested by families. Conclusions Using intelligent personal assistants to deliver health-related messages and information within the home is feasible, with high levels of engagement reported by participating families. This novel feasibility study highlights important methodological considerations that should inform future trials testing the effectiveness of intelligent personal assistants in promoting positive health-related behaviors. Trial Registration ISRCTN Registry ISRCTN16792534; http://www.isrctn.com/ISRCTN16792534
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Nardelwar, Miss Sanjana, Mr Saket Junghare, Mr Aditya Dhawale, Miss Nayan Gokhale, Prof Mohammad Hassan, and Dr Neetu Gyanchandani. "A Review Paper on Intelligent Home Automation Using Goggle Assistant." International Journal for Research in Applied Science and Engineering Technology 10, no. 3 (March 31, 2022): 57–62. http://dx.doi.org/10.22214/ijraset.2022.40560.

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Abstract: We are living in a world that's fleetly evolving in terms of automation. Automation is the capability to record events for bias connected to a original network or the Internet through time- related or encouragement- started programs. Smart energy effective intelligent home automation system is proposed that can pierce and control home appliances from every corner of the world. In order to make the operation more stoner friendly,web grounded and android grounded technologies have gained their significance in this slice edge technology. Determining the operating time of home appliances requires tuning a number of parameters according to the available energy supplied to the smart home. The seeing of colorful variables outdoors is done using the NodeMCU-ESP8266 microcontroller board, which allows real time data seeing. Home automation is grounded on multimodal operation which can be operated using the stoner's voice recognition commands using Google Assistant or through web grounded operation and It's using MQTT is presented for transferring entering data from detectors. Wireless networks enable multiple electronics widgets to use the same network connection without physical contact. It enables mobile widgets similar as smart phones, laptops, iPods and tablets to mobile freely within the content space and still maintain connectivity to the network. Keywords: Home Automation, Node MCU (ESP8266), Internet of Things (IoT), Google Assistant, Voice Control, Smartphone
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Fontecha, Jesús, Iván González, and Alberto Salas-Seguín. "Using Conversational Assistants and Connected Devices to Promote a Responsible Energy Consumption at Home." Proceedings 31, no. 1 (November 20, 2019): 32. http://dx.doi.org/10.3390/proceedings2019031032.

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Today, households worldwide are being increasingly connected. Mobile devices and embedded systems carry out many tasks supported by applications which are based on artificial intelligence algorithms with the aim of leading homes to be smarter. One of the purposes of these systems is to connect appliances to the power network, as well as to the internet to monitor consumption data among others. In addition, new interaction ways are emerging to manage all these systems. For example, conversational assistants which allow us to interact by voice with devices at home. In this work, we present GreenMoCA, a system to monitor energy consumption data from connected devices at home with the aim of improving sustainability aspects and reducing such energy consumption, supported by a conversational assistant. This system is able to interact with the user in a natural way, providing information of current energy use and feedback based on previous consumption measures in a Smart Home environment. Finally, we assessed GreenMoCA from a usability and user experience approach on a group of users with positive results.
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Sebastian, J., and Y.-L. Hsu. "Talking to the home: IT infrastructure for a cloud-based robotic home smart-assistant." Gerontechnology 17, s (April 24, 2018): 102. http://dx.doi.org/10.4017/gt.2018.17.s.099.00.

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Masina, Fabio, Valeria Orso, Patrik Pluchino, Giulia Dainese, Stefania Volpato, Cristian Nelini, Daniela Mapelli, Anna Spagnolli, and Luciano Gamberini. "Investigating the Accessibility of Voice Assistants With Impaired Users: Mixed Methods Study." Journal of Medical Internet Research 22, no. 9 (September 25, 2020): e18431. http://dx.doi.org/10.2196/18431.

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Background Voice assistants allow users to control appliances and functions of a smart home by simply uttering a few words. Such systems hold the potential to significantly help users with motor and cognitive disabilities who currently depend on their caregiver even for basic needs (eg, opening a door). The research on voice assistants is mainly dedicated to able-bodied users, and studies evaluating the accessibility of such systems are still sparse and fail to account for the participants’ actual motor, linguistic, and cognitive abilities. Objective The aim of this work is to investigate whether cognitive and/or linguistic functions could predict user performance in operating an off-the-shelf voice assistant (Google Home). Methods A group of users with disabilities (n=16) was invited to a living laboratory and asked to interact with the system. Besides collecting data on their performance and experience with the system, their cognitive and linguistic skills were assessed using standardized inventories. The identification of predictors (cognitive and/or linguistic) capable of accounting for an efficient interaction with the voice assistant was investigated by performing multiple linear regression models. The best model was identified by adopting a selection strategy based on the Akaike information criterion (AIC). Results For users with disabilities, the effectiveness of interacting with a voice assistant is predicted by the Mini-Mental State Examination (MMSE) and the Robertson Dysarthria Profile (specifically, the ability to repeat sentences), as the best model shows (AIC=130.11). Conclusions Users with motor, linguistic, and cognitive impairments can effectively interact with voice assistants, given specific levels of residual cognitive and linguistic skills. More specifically, our paper advances practical indicators to predict the level of accessibility of speech-based interactive systems. Finally, accessibility design guidelines are introduced based on the performance results observed in users with disabilities.
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