Smart Audio Research Articles

Smart Audio Toothbrush With UV-filtered Toothpaste Dispenser to Improve Skills Brushing Teeth and Reducing Debris Index Blind Children

Background: Blind children are children who tend to have low dental hygiene conditions. Children's behavior in maintaining dental hygiene influences the status of their dental hygiene. Because of their limitations, it is difficult for them to interpret what they should do. To overcome this, media is used as an educational tool, namely Ada's Toothbrush to improve teeth brushing skills and reduce the debris index of blind children. Objective: To produce a Smart Audio Toothbrush With Uv-filtered toothpaste dispenser (Ada's Toothbrush) model to improve teeth brushing skills and reduce debris index for visually impaired children. Method: Using Quantitative methods with pre- experiment research design (one group pretest and post- test design). With the sampling technique, the total sampling consisted of 30 blind children given intervention with the model Ada's Toothbrush for 10 days. Results: The results of expert validation of the Ada's Toothbrush model through validity testing using Aiken V show value hit > 0.8 is declared very valid and uses a reliability test Interclass Correlationb 0.915c , because (icc>0.80) it has high reliability. So Ada's Toothbrush model is feasible as an effort to improve the teeth-brushing skills of blind children. This model is proven effective and there was an increase in skill scores (p=0.000) of blind children on how to brush their teeth before and after the intervention, and effective in improving dental hygiene status by reducing the debris index (p=0.000) before and after the intervention. Conclusion: The development of Ada's Toothbrush model is effective in improving teeth brushing skills and reducing the debris index of blind children.

Evaluation of a Smart Audio System Based on the ViP Principle and the Analytic Hierarchy Process Human–Computer Interaction Design

The current limitations of user–product interaction with smart speakers have spurred the proposal of a model to circumvent these challenges. We used the ViP design principle to redefine the user’s approach to interacting with the product. Throughout the deconstruction and design stages, we explored the structure and function of the conventional product across three layers: the product layer, interaction layer, and context layer using three models. We used the hierarchical analysis method to effectively quantify the design factors affecting user experience and identify the key design factors. This approach enabled us to contextualize the smart audio system, explore the interaction dynamics between the product and the user, and provide valuable insights on designing new products. A questionnaire method was used to survey 67 users, and a reliability test was conducted to ensure the validity of the questionnaire v (Cronbach’s coefficient α = 0.868). A pairwise comparison of factors was conducted on a 1–9 scale, with weights determined through the analytic hierarchy process (AHP). The combination of the ViP design principle and hierarchical analysis presents a novel and objective paradigm to guide designers to customize product characteristics (design attributes) to enhance user human–computer interaction experience. We validated the feasibility of the innovative design approach using the smart speaker model, offering insights for research on designing similar products.

Analysis of the application of BIM technology in the combination of interior design and smart home

Abstract This paper aims to explore the application in the combination of interior design and smart homes and constructs an intelligent algorithm of BIM+4D technology by analyzing BIM technology and its application in interior home design. The mathematical relationship of design duration is established on the basis of BIM+4D. Studied the system of BIM+ in interior home design and set up the standard and template of the interior home. The BIM+4D technology intelligent algorithm is used to analyze the survey data and verify the feasibility and development of BIM technology in the combination of interior design and smart homes. The result data shows that the amount of investment in smart home functions is increasing year by year, among which the amount of investment in smart home appliances has been at the forefront. Among the smart home functions, smart home appliances account for the highest percentage, accounting for 80; smart temperature control accounts for 50%, and smart audio accounts for 40%. Home Design VR and AR input amount growth rates of 10%, 20%, 40%, 50%, and 40%, respectively. The research in this paper is beneficial to promote better integration of interior design and smart homes.

‘I want him to tell me he loves me’: A smart audio device, Tochie, for resident‐family connection in long‐term care

Older people living in long-term care homes are particularly susceptible to loneliness and social isolation, which the COVID-19 pandemic has exacerbated further. 'Tochie' is a smart audio device that allows family members to remotely record and send messages, such as daily reminders and comforting recordings, to their loved ones in LTC settings. The purpose of this study was to assess the feasibility and acceptability of using Tochie to improve resident-family connections, and to investigate user experience, impact and lessons learned. Participants included 10 residents, nine family members and six care staff from two LTC homes in British Columbia, Canada. A Tochie was provided to each resident to use with their family members over a 4-week intervention period. The research team provided support and gathered feedback from family members and care staff through weekly phone and email correspondence. Qualitative descriptive design was used, including pre- and post-intervention focus groups and interviews held via Zoom and phone to gather participants' experiences with Tochie. Themes were identified through thematic analysis. Three themes were identified: (1) Facilitating emotional connection, (2) Using the device in creative and personalised ways and (3) Structural challenges and supports. Based on these findings, recommendations for future research and practice are provided. The COVID-19 pandemic has prompted a rethinking of what it means to 'stay in touch' with loved ones in LTC settings. This study found that Tochie has opened up new opportunities for family connection and provided emotional support for residents. The results of this study offer valuable insights into the implementation of assistive technology in LTC homes to support resident care.

A smart audio device Tochie for long‐term care residents to stay connected with family during COVID lockdown

AbstractBackgroundThe effects of isolation and loneliness have been exacerbated by the COVID‐19 pandemic. While assistive technology offers potential benefits for long‐term care residents, there is limited evidence on technology adoption in complex care environments in LTC. The voices of older persons, family members and staff perspectives are not adequately included in implementation science literature. The poster report the adoption of Tochie, a smart audio device that allows family members to remotely record and schedule messages, such as daily reminders or comforting audio recordings, to send to their loved ones in LTC care homes during the time of COVID lockdown.MethodWe applied qualitative descriptive design with interview and focus group methods. A total of 25 people in LTC participated in the study, including residents, family members, and care staff from two long‐term care homes in British Columbia, Canada. Each resident was given a device to use with their family member for a four‐week intervention period. The research team checked in with family members and staff weekly via telephone and email to provide support and gather feedback. Pre‐ and post‐intervention focus groups and interviews were held via Zoom and phone correspondence to learn about participants’ experiences using Tochie. Thematic analysis was performed to identify themes.ResultFour common themes were identified to describe the experience of using Tochie in LTC: (a) fostering emotional connection (b) connecting in creative and personalized ways (c) considering contextual considerations in LTC (d) lessons learned for future developments.ConclusionThe COVID‐19 pandemic has provided us an opportunity to redefine and reconstruct what it means to “keep in touch” with loved ones in care settings. In our study, residents, families and staff highlighted the ways in which Tochie has enabled and expanded possibilities for family connection. Our findings offer pragmatic insights into challenges and possibilities for future product development and implementation.

Using a smart audio device, Tochie to deliver family messages in long-term care.

Long-term care (LTC) residents are more likely to experience loneliness, social isolation and have dementia (Garner et al., 2018; Hou & Ngo, 2021). The effects of isolation have been exacerbated by the COVID-19 pandemic. While assistive technology has been a popular topic in gerontological health research, there have been limited findings on the experience of technology adoption in complex care environments such as LTC, and on family member and staff perspectives. "Tochie" is a smart audio device that allows family and significant others to remotely record and schedule messages, such as daily reminders or comforting audio recordings, to send to their loved ones in care settings. Our research explores the experiences of residents, families, and staff using the Tochie device in LTC. We applied qualitative descriptive design with interview and focus group methods. 10 residents, 9 family members, and 6 care staff from two long-term care homes in British Columbia, Canada, participated in the study. Each resident was given a device to use with their family member for a four-week intervention period. The research team checked in with family members and staff weekly via telephone and email to provide support and gather feedback. Pre- and post-intervention focus groups and interviews were held via Zoom and phone correspondence to learn about participants' experiences using Tochie. Thematic analysis was performed to identify themes. Four common themes were identified to describe the experience of using Tochie in LTC: (a) Tochie as a means to facilitate emotional connection (b) Using Tochie in creative, personalized ways (c) Challenges and contextual considerations in LTC (d) Ideas for future developments CONCLUSION: The COVID-19 pandemic has provided us an opportunity to redefine and reconstruct what it means to "keep in touch" with loved ones in care settings. In our study, residents, families and staff highlighted the ways in which Tochie has enabled this connection and provided feedback on their challenges and device recommendations. This study explores the valuable perspectives of residents, their loved ones, and care staff in the use of assistive audio devices to inform product development and adoption into LTC.

A Survey on Audio-Video Based Defect Detection Through Deep Learning in Railway Maintenance

Within Artificial Intelligence, Deep Learning (DL) represents a paradigm that has been showing unprecedented performance in image and audio processing by supporting or even replacing humans in defect and anomaly detection. The Railway sector is expected to benefit from DL applications, especially in predictive maintenance applications, where smart audio and video sensors can be leveraged yet kept distinct from safety-critical functions. Such separation is crucial, as it allows for improving system dependability with no impact on its safety certification. This is further supported by the development of DL in other transportation domains, such as automotive and avionics, opening for knowledge transfer opportunities and highlighting the potential of such a paradigm in railways. In order to summarize the recent state-of-the-art while inquiring about future opportunities, this paper reviews DL approaches for the analysis of data generated by acoustic and visual sensors in railway maintenance applications that have been published until August 31st, 2021. In this paper, the current state of the research is investigated and evaluated using a structured and systematic method, in order to highlight promising approaches and successful applications, as well as to identify available datasets, current limitations, open issues, challenges, and recommendations about future research directions.

Sustainable supplier evaluation and transportation planning in multi-level supply chain networks using multi-attribute- and multi-objective decision making

Supplier selection and transportation planning are essential tasks in managing supply chain networks (SCNs). The choice of a supplier has a significant influence on the transportation planning of SCNs, as the transportation routes will change. A limited number of studies in the literature have addressed the supplier selection and transportation planning issues simultaneously. This study proposes a two-stage multi-criteria decision-making (MCDM) approach for sustainable supplier evaluation and transportation planning in multi-level SCNs. Initially, a supplier evaluation framework is proposed using the modified indifference threshold-based attribute ratio analysis (ITARA) and the performance calculation technique of the integrated multiple multi-attribute decision-making (PCIM-MADM) to determine the supplier’s performance index. Subsequently, a multi-level SCN model is established, and the sustainable supplier selection and transportation planning problem is solved by the fuzzy multi-objective linear programming (FMOLP) method. A set of real-world data provided by a smart audio manufacturing company has been used to demonstrate the proposed approach. Decision-makers understand the importance of criteria through the weights constructed by the modified ITARA. Moreover, the results of the PCIM-MADM can effectively determine the supplier’s ranking and provide improving strategies for underperforming suppliers. The augmented max–min technique of the FMOLP can produce a single optimal solution of the transportation allocation. The results show that our approach can effectively evaluate sustainable supplier performance and optimize transportation planning in SCNs.

Pengaruh Media Audio Visual Edukasi Smart (AVES) Terhadap Hasil Belajar Keterampilan Dasar Praktik Mahasiswa Kebidanan

Research on the Effect of Smart Educational Audio Visual Media (AVES) on Learning Outcomes of Basic Practice Skills for Midwifery Students, is a research on the development of teaching media designed to be the main supporting tool for learning basic midwifery practice in practicing clinical skills and improving student learning outcomes. Midwifery program education requires graduates to be skilled in carrying out their professional duties as skilled midwives and declared competent after they pass the national competency exam. The purpose of this study was to determine the effect of smart educational audio visual media (AVES) on learning outcomes of students' basic skills in midwifery practice. This research method uses an experimental method with the research design that will be used is a pre-experimental design type one group pretest-posttest design. The population in this study were all 87 students of midwifery class XIII and XIV. The sampling technique is non-probability sampling with a purposive sampling model, as many as 28 students. The results of this study are that the data obtained, that tcount = 2.310 > ttable = 2.0555 with a significance of 0.029 <0.05, then H0 is rejected and H1 is accepted. the researchers can conclude that there is a positive and significant influence between Smart Audio Visual Education Media on Learning Outcomes of Basic Skills Practice of Midwifery Students

RETRACTED: Application of smart audio based on mixed reality technology in media fusion

A company of gadgets is the leading representative of complex reality technology. Do have differences in technical design and application of measurement and comparison of technology. For each technical specification and representation, and support the software functions to compare and consider. Smart Audio is based on the complex reality in the complicated fact of media convergence first worker. Because he worked for as long as he is in this Computer, the most widely used operating system on media convergence is worn on the head. It supports a full range of programs that run on this platform. It works equipment is necessary, as long as the device itself is used as a monitor, only the complex reality, and has a strong enough PC. It is very similar and does not require media integration, attached to a Personal Computer (PC) connected to a separate device. Van is very similar. It does not require the media's integration, an additional stand-alone device connected to the PC. Currently, it uses its operating system, which limits its range of small software. Virtual reality technology, complex reality, should be noted and allows to add digital content with the real world without losing visual contact with others. As a result, technology in education, where the application is called Fusion Applications media. Fusion Media will support through video link and SMS data analysis tools to encourage communication and reflective learning.

A Multi-Static Radar Network with Ultra-Wideband Radio-Equipped Devices.

A growing number of devices, from car key fobs to mobile phones to WiFi-routers, are equipped with ultra-wideband radios. In the network formed by these devices, communicating modules often estimate the channel impulse response to employ a matched filter to decode transmitted data or to accurately time stamp incoming messages when estimating the time-of-flight for localization. This paper investigates how such measurements of the channel impulse response can be utilized to augment existing ultra-wideband communication and localization networks to a multi-static radar network. The approach is experimentally evaluated using off-the-shelf hardware and simple, distributed filtering, and shows that a tag-free human walking in the space equipped with ultra-wideband modules can be tracked in real time. This opens the door for various location-based smart home applications, ranging from smart audio and light systems to elderly monitoring and security systems.

A2Event: A Micro-Watt Programmable Frequency-Time Detector for Always-On Energy-Neutral Sensing

Internet of Things (IoT) sensors are becoming more and more intelligence and unobtrusive, surrounding us in everyday life. A key requirement for those devices is to be “always-on” performing “smart” detection to catch only the events of interest when they occur. A recent and trend is to design low power circuit to extract features close to the sensors without an analog-digital conversion. The goal is to achieve place-and-forget deployment with perpetual operation: this poses the challenge of achieving micro-watt power consumption of the always-on analog event detector and of harvesting energy from environmental sources, to supply the smart sensor. This paper presents A2Event (Analog to Event), a microwatt programmable pattern recognition circuit for analog sensors, with up to 128 simultaneous time-frequency features exploiting mixed-signal low power design, which is able to generate an event when a targeted pattern is recognized. Moreover, the paper proposes a self-sustaining always-on smart audio detector that combines A2Event with energy harvesting to detect events of interests perpetually. Experimental results show that A2Event consumes only 26.89 μW in always-on mode, during the time-frequency feature-extraction, while the whole system consumes only 63 μW during pattern recognition including the power for a commercial MEMS microphone and the energy harvesting subsystem. We demonstrate that the whole smart sensor operates perpetually when powered with a small form factor flexible photovoltaic panel in indoor lighting conditions, achieving a detection accuracy of 100% in the detection of two different audio streams.

Smart Sound Sensor to Detect the Number of People in a Room.

Ambient sound monitoring is a widely used strategy to follow older adults, which could help them achieve healthy ageing with comfort and security. In a previous work, we have already developed a smart audio sensor able to recognize everyday life sounds in order to detect activities of daily living (ADL) and distress situations. In this paper, we propose to add a new functionality by analyzing the speech flow to detect the number of people in a room. The proposed algorithms are based on speaker diarization methods. This information can be used to better detect activities of daily life but also to know when the person is home alone. This functionality can also offer more comfort through light, heating and air conditioning adaptation to the number of people in an environment.

Deep Artwork Detection and Retrieval for Automatic Context-Aware Audio Guides

In this article, we address the problem of creating a smart audio guide that adapts to the actions and interests of museum visitors. As an autonomous agent, our guide perceives the context and is able to interact with users in an appropriate fashion. To do so, it understands what the visitor is looking at, if the visitor is moving inside the museum hall, or if he or she is talking with a friend. The guide performs automatic recognition of artworks, and it provides configurable interface features to improve the user experience and the fruition of multimedia materials through semi-automatic interaction. Our smart audio guide is backed by a computer vision system capable of working in real time on a mobile device, coupled with audio and motion sensors. We propose the use of a compact Convolutional Neural Network (CNN) that performs object classification and localization. Using the same CNN features computed for these tasks, we perform also robust artwork recognition. To improve the recognition accuracy, we perform additional video processing using shape-based filtering, artwork tracking, and temporal filtering. The system has been deployed on an NVIDIA Jetson TK1 and a NVIDIA Shield Tablet K1 and tested in a real-world environment (Bargello Museum of Florence).

A Study on the Customer Satisfaction for Smart Audio's Concept Features through the Kano Model

Purpose This study was conducted to analyze the potential customer's satisfaction for the concepts of smart audio features and utilize the results when developing the customer-oriented products. Methods 16 different features were derived via the market research and professionals’ interviews. The most satisfactory features were selected through “Kano model”, the relative importance of Customer Satisfaction Coefficient, and respondents’ preferences from 339 valid survey answers. Results 15 out of the 16 features were categorized as attractive attribute. “‘User Recognizing’ and ‘Strengthen Linking’ groups”, such as Auto connection with Smartphone music player, Synchronization of TV & Audio, and Volume control situational awareness, were shown to provide higher satisfactions to those potential customers. On the other hand, Group ‘Integrating Function’, such as Aromatherapy and Auto lighting reaction, was shown to be relatively least preferred features. Conclusion This study enabled which features could lead to the customer satisfaction. Nevertheless, it still requires extensive analyses in different countries and diverse cultures to target the global market. The audio product planners and R&D professionals are expected to learn useful information from such studies. Key words: Kano Model, Customer Satisfaction, Smart Audio, Concept Feature, Preference