Development of a Customized Mask Frame Using a Three-Dimensional Facial Scan for an Airtight Seal for Disposable Surgical Face Masks

Disposable surgical face masks are designed to block the airborne transmission of infectious viruses between patients and healthcare personnel;however, there are limitations to a surgical mask's ability to prevent transmissions because the mask does not provide an airtight seal around the face. This study focuses on the design and development of a custom mask frame, using individuals' three-dimensional (3D) facial scans, to improve the seal of the existing surgical masks. Three participants' facial scans with a wide range of facial dimensions were collected using a 3D hand-held scanner. During design, the contact area between the custom frame and the wearer's skin was determined based on the individual's 3D facial shape. To evaluate the effectiveness of the airtight seal, a qualitative fit (smell/taste) test kit and thermal imaging camera were utilized. When the participants wore the surgical masks without the customized mask frames, the participants smelled the saccharine scent from the test kit. However, while wearing the surgical masks fitted with the custom mask frame that held the mask in place, none of the participants could smell the scent. In addition, thermal images showed ambient temperature changes in the surgical mask suggesting air leakage around the boundary of the mask while the subject was inhaling and exhaling. With the mask frame, thermal images confirmed the effectiveness of the custom frame to block the inflow/outflow of air potentially carrying the virus. The results indicate that the custom-built mask frames are effective in providing a proper and much improved seal compared to a surgical mask without the frame. The developed custom mask frame will be particularly beneficial for frontline medical staff members who treat patients with infectious viruses transmitted through aerosols as part of their PPE.

CNFRD: A Few-Shot Rumor Detection Framework via Capsule Network for COVID-19

In recent years, COVID-19 has become the hottest topic. Various issues, such as epidemic transmission routes and preventive measures, have "occupied” several online social media platforms. Many rumors about COVID-19 have also arisen, causing public anxiety and seriously affecting normal social order. Identifying a rumor at its very inception is crucial to reducing the potential harm of its evolution to society as a whole. However, epidemic rumors provide limited signal features in the early stage. In order to identify rumors with data sparsity, we propose a few-shot learning rumor detection model based on capsule networks (CNFRD), utilizing the metric learning framework and the capsule network to detect the rumors posted during unexpected epidemic events. Specifically, we constructively use the capsule network neural layer to summarize the historical rumor data and obtain the generalized class representation based on the historical rumor data samples. Besides, we calculate the distance between the epidemic rumor sample and the historical rumor class-wise representation according to the metric module. Finally, epidemic rumors are discriminated against according to the nearest neighbor principle. The experimental results prove that the proposed method can achieve higher accuracy with fewer epidemic rumor samples. This approach provided 88.92% accuracy on the Chinese rumor dataset and 87.07% accuracy on the English rumor dataset, which improved by 7% to 23% over existing approaches. Therefore, the CNFRD model can identify epidemic rumors in COVID-19 as early as possible and effectively improve the performance of rumor detection.

Developing an App for Improving Access to COVID-19 Information in Underserved Communities

The deployment of mobile health (mHealth) apps can transform healthcare in rural and remote communities worldwide. Rural communities in Zimbabwe have limited access to information that affects their health, economic and social being due to structural and social barriers related to the inaccessibility of traditional media. mhealth apps are a valuable tool to monitor disease outbreaks and provide preventative information to the public. Lack of access to COVID-19 information results in high fatalities and public panic, and it is critical to publish reliable and timely information. The study's objective was to demonstrate the utility of a mHealth app prototype developed to enhance access to COVID-19 information in rural and remote communities in Zimbabwe. The prototype provides COVID-19 information such as statistics, preventative measures, self-diagnostics, social distancing information, and general hygiene to rural communities with limited access to official information channels on the pandemic. A design science research methodology was used to design, build and evaluate the COVID-19 mHealth app and fulfil the study's objectives. Thirty potential users participated in the evaluation of the prototype. The evaluation results show that potential users perceived that the prototype was useful, engaging, easy to learn, well designed, and provided relevant information. A strong correlation was observed between the design, engagement, functionality, and learnability. More widespread usability and more representative tests should be conducted to ascertain the efficacy and usability of the app. The study contributes literature on usability studies in developing countries. As more mHealth apps are being developed and deployed, more usability tests will be required to ensure that they are fit for purpose. The paper provides a baseline for developing related health information apps. Policymakers, health practitioners, technologists, and scholars can further investigate the deployment of digital technologies to improve healthcare and control the transmission and spread of COVID-19.

Smart Healthcare Applications over 5G Networks: A Systematic Review

Provisioning of health services such as care, monitoring, and remote surgery is being improved thanks to fifth-generation cellular technology (5G). As 5G expands globally, more smart healthcare applications have been developed due to its extensive eMBB (Enhanced Mobile Broadband) and URLLC (Ultra-Reliable Low Latency Communications) features that can be used to generate healthcare systems that allow minimizing the face-to-face assistance of patients at hospital centers. This powerful network provides high transmission speeds, ultra-low latency, and a network capacity greater than that of 4G. Fifth-generation cellular technology is expected to be a means to provide excellent quality of medical care, through its technological provision to the use of IoMT (Internet of Medical Things) devices. Due to the numerous contributions in research on this topic, it is necessary to develop a review that provides an orderly perspective on research trends and niches for researchers to use as a starting point for their work. In this context, this article presents a systematic review based on PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), with article selection based on inclusion and exclusion criteria that avoid bias. This research was based on research questions that were answered from the included works. These questions focus on technical characteristics, health benefits, and security protocols necessary for the development of smart healthcare applications. We have identified that a high percentage of existing works in the literature are proposals (56.81%, n = 25) and theoretical studies (22.73%, n = 10);few implementations (15.91%, n = 7) and prototypes (4.55%, n = 2) exist, due to the limited global deployment of 5G. However, the panorama looks promising based on proposals and future work that these technological systems allow, all based on improving healthcare for people.

Software Implementation of a Smart Bracelet Prototype to Monitor Vital Signs, Locate, and Track COVID-19 Patients in Quarantine Zone

This paper describes the design and software implementation of a wearable prototype that allows users to monitor the vital signs of COVID-19 patients in quarantine areas. This prototype consists of two parts, the bracelet, andthe Base control unit (BCU). The bracelet is built with ESP8266 and sensors as main components, as well as the battery and other parts needed to fulfill the system's purpose (monitoring the vital signs of COVID-19 patients). At the same time, the Raspberry Pi (SCB) single board computer and GSM/GPRS/HAT are the main components of the Basic Control Unit (BCU). The current work describes the main parts of the pseudocode, as well as the activity diagram for the microcontroller and Raspberry Pi. This paper describes the mechanism of sending alert messages, whereby the system's ability to configure two types of alert messages;(1) physician Messages (these Messages will be sent to the physicianassociated with the patient if one or more vital signs reach a critical value;these messages contain all measurements of a patient's vital signs);(2) Authorize messages (these messages will be sent if the quarantine rules are violated;the patient's location will be sent to the authorized person as a Google Mapslink). Also, this paper describes the graphical user interface for communication, management,. and interaction between the users of the system. © 2022 IEEE.

USED CAR CLUSTERING in BANDUNG CITY USING K-PROTOTYPES ALGORITHMS

Since the case of the 2019 Coronavirus Disease pandemic or commonly referred to as Covid-19, the use of public transportation has slowly begun to become an option as transportation to reduce the spread of the corona virus cluster, therefore some people prefer to buy private vehicles. However, due to the increasing price of cars, some people prefer to buy used cars. On the used car buying and selling platform, OLX Autos Indonesia, the demand for used cars increased by 15% to 20%. Therefore, this study was conducted to determine the characteristics of the cluster formed from the used car sales dataset taken from AtapData (atapdata.ai). AtapData is an open data site in Indonesia that can be used for research related to Data Science. This cluster model was created using the K-Prototypes algorithm, Silhouette Score and Davies Bouldin Index to evaluate the resulting cluster results. This clustering model will produce three clusters. The results of the three clusters will have one thing in common, namely brands that dominate sales, including Toyota, Honda, Daihatsu, Nissan, and Mitsubishi. Clustering evaluation using the Silhouette Score method produces a value of 0.7744140503593034. And for the evaluation of the Davies-Bouldin Index it produces a value of 0.4999221950856398. © 2022 IEEE.

An Intelligent Food Serving Robot Prototype with Android Application for Canteens

As the world faces a COVID epidemic, one of the most critical rules to observe is social separation. There are some situations where social separation is difficult to maintain, such as canteens. The proposed technology equips a college canteen with an autonomous food serving robot, allowing us to preserve social distance. People in canteens confront challenges such as long lines and food service delays. When it comes to college canteens, students only have a limited amount of time for refreshment, resulting in a rush at the canteen. Our self-serving food robot will serve the food to the clients without fail;all they have to do is order meals using the mobile app. The system relies on a mobile application to place orders and a robot to deliver the food. Users will be able to summon the robot using the help button in the mobile app, which will result in canteen trash management. For routing and finding the best way to the table, we employ a combination of sensors and Radio Frequency Identifier (RFID) technology. Our solution will benefit the admin in addition to keeping the customers happy. Making a robot will be less expensive than hiring a human waiter. The system not only has a rechargeable wallet payment interface, but also net banking, card payment, and UPI payment possibilities. © 2022 IEEE.

The Future of Epidemic and Pandemic Vaccines to Serve Global Public Health Needs.

This Review initiates a wide-ranging discussion over 2023 by selecting and exploring core themes to be investigated more deeply in papers submitted to the Vaccines Special Issue on the "Future of Epidemic and Pandemic Vaccines to Serve Global Public Health Needs". To tackle the SARS-CoV-2 pandemic, an acceleration of vaccine development across different technology platforms resulted in the emergency use authorization of multiple vaccines in less than a year. Despite this record speed, many limitations surfaced including unequal access to products and technologies, regulatory hurdles, restrictions on the flow of intellectual property needed to develop and manufacture vaccines, clinical trials challenges, development of vaccines that did not curtail or prevent transmission, unsustainable strategies for dealing with variants, and the distorted allocation of funding to favour dominant companies in affluent countries. Key to future epidemic and pandemic responses will be sustainable, global-public-health-driven vaccine development and manufacturing based on equitable access to platform technologies, decentralised and localised innovation, and multiple developers and manufacturers, especially in low- and middle-income countries (LMICs). There is talk of flexible, modular pandemic preparedness, of technology access pools based on non-exclusive global licensing agreements in exchange for fair compensation, of WHO-supported vaccine technology transfer hubs and spokes, and of the creation of vaccine prototypes ready for phase I/II trials, etc. However, all these concepts face extraordinary challenges shaped by current commercial incentives, the unwillingness of pharmaceutical companies and governments to share intellectual property and know-how, the precariousness of building capacity based solely on COVID-19 vaccines, the focus on large-scale manufacturing capacity rather than small-scale rapid-response innovation to stop outbreaks when and where they occur, and the inability of many resource-limited countries to afford next-generation vaccines for their national vaccine programmes. Once the current high subsidies are gone and interest has waned, sustaining vaccine innovation and manufacturing capability in interpandemic periods will require equitable access to vaccine innovation and manufacturing capabilities in all regions of the world based on many vaccines, not just "pandemic vaccines". Public and philanthropic investments will need to leverage enforceable commitments to share vaccines and critical technology so that countries everywhere can establish and scale up vaccine development and manufacturing capability. This will only happen if we question all prior assumptions and learn the lessons offered by the current pandemic. We invite submissions to the special issue, which we hope will help guide the world towards a global vaccine research, development, and manufacturing ecosystem that better balances and integrates scientific, clinical trial, regulatory, and commercial interests and puts global public health needs first.

Development of mHealth-Apps for Hearing Aids – Requirements and Assessments of a First Prototype

An aging of the working population is expected. Consequently, age-related impairments of sensory functions (e.g., hearing impairment) will become more prominent. An increase of people with hearing impairment can already be observed today. In the last years, the importance of digitalization has increased constantly. This was further driven by the COVID19-pandemic. Therefore, the question whether mHealth-apps could be able to improve the first start experience of possible new hearing aid users and how such an app should be designed has continuously become more important. Former research showed that participants rated possible hearing app-functions significantly different. The aim of the presented study was to verify these results and to extend it with additional functions. Furthermore, possible future users should assess first paper-based prototypes. Therefore, an exploratory online study was conducted. Overall, the sample consists of 41 participants (29 female;19–58 years old). 18 of them were subjectively at least mild hearing impaired. The results of the study show that participants rated possible functions and the different hearing app-prototypes significantly different. Interestingly, effects of hearing impairment and gender can be shown. Overall, the results can improve the development of a new mHealth-app to support new users of hearing aids. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Design of a software prototype to make a Tour in the Infantery Museum Marine Park using View 360 technology

Before the arrival of the pandemic due to SARS-CoV-2, the Infantery Museum Marine Park was among the most visited tourist sites in Coveñas, however, due to Colombian decree 457, the museum closed its doors to the visitors, thus avoiding the exposure of the national military heritages that are exposed in it, restricting one of the most important contributions to the educational context in the Caribbean Region. Therefore, the objective of the research is to design the model of a web prototype, using View 360 ° technology, for the remote exhibition of the facilities and heritage of the Infantery Museum Marine Park. The type of research is basic and applied, where a documentary analysis of the 360 ° view technology was carried out, identifying the technical and user requirements for the development of the prototype design, which will integrate 360 ° panoramic photographs and points of access, strengthening the exhibition of the heritages and there was a completely new way for the museum professionals to communicate the exhibits to the public. It is concluded that the proposed prototype meets the functional requirements necessary to solve the problem presented.

The Assistant Personal Robot Project: From the APR-01 to the APR-02 Mobile Robot Prototypes

This paper describes the evolution of the Assistant Personal Robot (APR) project developed at the Robotics Laboratory of the University of Lleida, Spain. This paper describes the first APR-01 prototype developed, the basic hardware improvement, the specific anthropomorphic improvements, and the preference surveys conducted with engineering students from the same university in order to maximize the perceived affinity with the final APR-02 mobile robot prototype. The anthropomorphic improvements have covered the design of the arms, the implementation of the arm and symbolic hand, the selection of a face for the mobile robot, the selection of a neutral facial expression, the selection of an animation for the mouth, the application of proximity feedback, the application of gaze feedback, the use of arm gestures, the selection of the motion planning strategy, and the selection of the nominal translational velocity. The final conclusion is that the development of preference surveys during the implementation of the APR-02 prototype has greatly influenced its evolution and has contributed to increase the perceived affinity and social acceptability of the prototype, which is now ready to develop assistance applications in dynamic workspaces.

Gender, diversity and the 2020 US presidential election: towards an androgynous presidential profile?

Purpose>The purpose of this study was to explore issues of gender and diversity raised by the 2020 US presidential election.Design/methodology/approach>Samples from two populations (n = 667) described either an ideal president or one of the major-party candidates for president (Donald Trump and Joe Biden) or vice president (Mike Pence and Kamala Harris) on an instrument that assessed self-ascribed masculinity and femininity. Androgyny was calculated as the difference between masculinity and femininity;the closer the score to zero, the more androgynous the candidate.Findings>The ideal president was viewed as androgynous (i.e. balanced in masculine and feminine traits) rather than masculine as in previous studies of presidential leadership. Compared to the White male candidates, Harris, a woman of color, displayed the most androgynous profile. The Democratic ticket represented a “balanced” team, with one candidate (Biden) higher on femininity and the other (Harris) higher on masculinity;in essence, an androgynous ticket. In contrast, the Republican ticket (Trump and Pence) represented a decidedly masculine ticket. Ideal president profiles differed according to respondents’ gender and preferred president.Practical implications>The Democrats winning the election with an androgynous ticket suggests that a more level playing field for female vis-à-vis male candidates for political leader roles may be arriving.Originality/value>The finding of an ideal president as androgynous rather than masculine is an original contribution to the literature on presidential leadership.

COVID-19 Patient Under Investigation Self-Monitoring Mobile Application: Development and Implementation

This research aims to develop a mobile application for Covid-19’s Patient Under Investigation (PUI) Self-Monitoring (PUISM). The intended audience for this project is PUI cases, specifically (Covid-19) cases. The application was developed for PUI self-health monitoring in order to keep doctors, nurses, and administrators updated about their health status. As a method, the ADDIE model was used in this project. The ADDIE model was employed in this project as an approach. Five phases comprise the ADDIE method: Analysis, Design, Development, Implementation, And Evaluation. During the design phase, the developer will produce a prototype of mobile applications for PUI that will achieve the patient’s goals and patient requirements. The developer can then create mobile applications that follow the prototype’s design. During the implementation phase, the developer will publish the mobile application. The developer will then collect feedback, analyze the effectiveness of the mobile application for PUI, and determine whether the application is entirely functional or not. Finally, our endeavour benefits all frontlines by supporting them in tracking PUI that meet the criteria for Covid-19 occurrences. Additionally, this treatment reduces the transmission of infection Covid-19 to lessen the burden on the health care system and improve home self-monitoring.

Designing the temporary dental clinic in the Covid-19 global pandemic

Covid-19 pandemic has directed hospitals to concentrate services for patients who are positive or still in undefined status. Some countries are even forced to build temporary structures or utilize multifunctional buildings such as sports/public halls. On the other hand, hospitals still have to keep performing other routine services and this becomes a challenge for them. When global attention nowadays focuses more on how hospitals serve the Covid-19 cases, this research proposes another side of healthcare service needed by people in the pandemic, which is the dental clinic. The spread of Covid-19 through droplets puts both dental patients and practitioners at risk target of Covid-19 transmission. Therefore, particular standards and protocols are mandatory to be deployed. A prototype design of the temporary dental clinic is the main output from this research. The main objective is to provide service for the community without being afraid of contracting the pandemic as the clinic will be isolated from the regular hospital buildings. To achieve this objective, this research employed three approaches for the methodology. It was started with the desk study to review references on recent technology of temporary building structures. Followed by the online questionnaire using the Google platform distributed to 206 registered dental practitioners in Aceh, in collaboration with the Indonesian Dental Association, Aceh Province, Indonesia. The questionnaire collected the data related to the needs, standards, procedures, and dental service protocols under the Covid-19 pandemic as the main reference for the design process. The last approach was gathering feedback from dentists and international architects who are experts in building science and technology. This was done through a series of pre-design reviews. This research has a high degree of urgency globally, including Saudi Arabia, which is also impacted by the Covid-19 pandemic. It is also in line with Saudi Vision 2030 to enhance the standard quality and sustainability of healthcare services. The prototype design proposed in this research does not only contribute to the Covid-19 pandemic in particular but also post-Covid scenarios or other possible global pandemics in the future.

Effects of Agrivoltaic Systems on the Surrounding Rooftop Microclimate

Agrivoltaic systems have the potential to maximize the usefulness of spaces in building rooftops. Urban farming systems improve the microclimatic conditions, which are beneficial to solar photovoltaic (PV) systems, as they lower the operating temperatures, resulting in a higher operating efficiency. Microclimate simulations by means of ENVI-met simulation showed that between 0800 h and 1800 h, PV temperatures in the plot that has crops below the PV system were on average lower by 2.83 °C and 0.71 °C as compared without crops on a typical sunny and cloudy day, respectively. Hence, we may see PV efficiency performance improvement of 1.13–1.42% and 0.28–0.35% on a sunny day and cloudy day, respectively. Data collected from a physical prototype of an agrivoltaic system suggested that evaporative cooling was responsible for the reduction in ambient temperatures. The presence of crops growing underneath the PV canopy resulted in the agrivoltaic prototype generating between 3.05 and 3.2% more energy over the day as compared to a control system with no crops underneath.

Direct Sunlight Driven In2S3 Thin Film Based Water Treatment Proto-Type

A multi-faceted energy intensive technology that can be used for water disinfection and synthesis of electrolysed water (EW) is the need of the hour to achieve a sustainable post COVID 19 water management strategy. Direct sunlight driven processes are legislatively green technologies and hold the key in environmental sustenance. The development of a laboratory proto type reactor powered by a photovoltaic module for the treatment open source river water is described in this paper. This paper reports on the efficacy of the developed proto type technology for multipurpose application namely: (1) the production of Electrolysed water (EW) in a cost efficient manner using direct sunlight and (2) the removal of organic impurity from water using direct sunlight without the use of any photo catalyst or membrane. The prototype reactor utilizes chemical spray pyrolysis deposited highly photo-conducting indium sulphide thin films grown on fluorine doped tin oxide (F:SnO2) substrate (coated using chemical spray pyrolysis technique in-house) as the photo electrode. Dissolved organic matter arising in river water has distinctive fluorescence properties, and this research has utilized it to identify dissolved organic substances in both random samples and treated water. The work proves that photovoltaic module powered electrolytic reactors consisting of In2S3 electrodes can be used for treatment of river water. A diaphragm free, energy intensive route for the production of electrolysed water with the use of non-hazardous NaCl as the electrolyte has been demonstrated here. We conclude that In2S3 electrodes can be used for non-photo catalytic reduction of humic-derived impurities in river water. These results are also encouraging on the prospects of treating Nitrates present in the river water. The likes of techniques as described in this report that do not use photo catalyst or membranes may pave way for real time photovoltaic module powered floating reactors that can decontaminate water bodies on a large scale. The technique used by us demonstrates that a chlorine free route can be optimized for the synthesis of EW eliminating the production of large amounts of wastewater with high levels of biological oxygen demand (BOD).

Implementation of Cloud Computing Protocol in E-Learning for Future Wireless Systems

Schooling system is rapidly shifting according to time. The 4G and 5G machineries are engineered to work flawlessly in heterogeneous platforms unlike 2G, 3G, and 4G wireless networks. New educational techniques are introduced for different environmental needs and E-learning, which is getting popular around the world, and wireless networking plays the vital role in it. E-learning is the requirement of every educational institute. There are a number of problems in the existing prototypes which need to be addressed and improved. This study provides the prototype for E-learning to make the higher education system more efficient. Especially, for the students who need distance learning and an online learning system, this research proposes a user-friendly cloud network infrastructure environment. Machine learning and cloud have strong relation in cloud computing;we store big amount of customer data but to analyze the data and create chatbots, we need machine learning algorithms. We need to enhance the existing prototype for the betterment of the higher education system in rural areas such a time of this COVID-19 pandemic. For this purpose, the existing prototype is critically examined. To achieve this factor why and how E-learning is familiar to the students of rural areas in developing countries, it was analyzed, as the method of education using a platform and interpreting the results. The researcher tried to discover the reason why E-learning is not being applied in higher education. Furthermore, attempts were made to change the existing model by adding the component “Cloud-based structure” that complements and fits the environment of the education system and benefits the long-term sustainability of higher education.

IoT-based indoor access control and monitoring: a case study from the containment measures of the COVID-19 pandemic

The COVID-19 pandemic has led many serving environments to seek solutions to control people's access and avoid crowding in order to contain its spread, and to ensure the health and safety of users. Given the various current solutions, this paper presents a monitoring system that shows, in real-time, via web, the status of people in closed environments. It uses internet of things (IoT) techniques for data interconnections and electronic components - NodeMCU board and proximity sensors - to monitor the entrance and exit of people in an enclosed environment, providing the statistics through an IoT platform (application) that can be installed in a mobile device (smartphone). This study highlights a low-budget system, shows the implementation of IoT platforms in the development of prototypes and the tests carried out in the academic service office.

Rehabilitation monitoring prototype: Arduino Nano 35 BLE

Nowadays, smart health has been developing in the healthcare system by implementing the Internet of Things. One of the implementations of smart health is remote monitoring systems for rehabilitating patients such as stroke. Today, with the rising Covid-19 pandemic, patients undergoing rehabilitation at home have difficulties meeting with their doctors due to the moving restrictions. The healthcare facilities are focused on treating Covid-19 patients. These restrictions have caused doctors and patients not to meet regularly to collect their data on the rehabilitation progress. This research suggests building a prototype to monitor a post-stroke patient’s lower limb strength rehabilitation process by using embedded sensors and microcontrollers. The prototype will measure key components of the rehabilitation process and will be discussed in the later section of this paper.

A smart door prototype with a face recognition capability

This research aimed to integrate a face recognition capability in a smart door prototype. By using a camerabased face recognition, the house owner does not need to make physical contact to open the door. Avoid physical contact is important due to the coro navirus disease 2019 (COVID19) pandemic. Raspberry Pi 3B was used as the main controller, while a servo motor was utilized as a locking door actuator. The program was developed using NodeRED , Blynk , and message queue telemetry transport ( MQTT ) platforms which are very powerful for developing internet of things (IoT) devices. All of the programs were coded using Python. Haar cascade and local binary pattern histogram methods were implemented on the face recognition stage. Google Assistant int egration was done by using D ialogflow and Firebase as Google Cloud services. Integration of face recognition and the smart door was successful. The smart door was unlocked if faces were recognized (average threshold=60%). If a face was not recognized, an e mail notification containing a face image is sent to the house owner. The Google Assistant could handle user requests successfully with a success rate of 92.8% from 147 trials .