A Detection System for Comfortable Locations Based on Facial Expression Analysis While Riding Bicycles

In recent years, the use of bicycle as a healthy and economical means of transportation has been promoted worldwide. In addition, with the increase in bicycle commuting due to the COVID-19, the use of bicycles are attracting attention as a last-mile means of transportation in Mobility as a Service(MaaS). To help ensure a safe and comfortable ride using a smartphone mounted on a bicycle, this study focuses on analyzing facial expressions while riding to determine potential comfort along the route with the surrounding environment and to provide a map that users can explicitly feedback(FB) after riding. Combining the emotions of facial expressions while riding and FB, we annotate comfort to different locations. Afterwards, we verify the relationship between locations with high level of comfort based on the acquired data and the surrounding environment of those locations using Google Street View(GSV). © 2023 Owner/Author.

Collaborative mapping of the noise level in Guayaquil during COVID-19

The SARS-CoV-2 virus triggered a never-before-seen scenario worldwide. Ecuador declared a state of emergency to contain coronavirus transmission by applying social isolation policies and mobility limitations. During this period, noise pollution decreased in Guayaquil city. This study proposes the use of smartphones to collect noise data and generate soundscape maps of Guayaquil during different time slots. The results revealed traffic as the predominant type of noise, followed by vehicles, buses, and people´s voices. This article demonstrates the feasibility of crowdsourcing for the collection of environmental variables. © 2022 National Institute for Space Research, INPE. All rights reserved.

Impact of Biomedical Engineering on Human & social Dynamics: A Review on Recent Approaches Through Bioengineering from Recent Past to Post-Covid-19

INTRODUCTION: The paper aims to discuss the various issues/ problems that people face in day to day life. Using diverse scenarios ranging from mental health issues to common grafting procedures, the author here strives to link these issues to bioengineering and how they are being impacted by modern technology. Most methods and procedures discussed attempt to utilize day-to-day activities and ease of access. The paper has adopted rapid review method. For literature collection, Google scholar database has been used with a scope of specific keywords and time frame of 5 weeks to complete the study © COPYRIGHT RED FLOWER PUBLICATIONS PVT LTD

Molecular Diagnostics on Smartphone

During the COVID-19 pandemic, point-of-care genetic testing (POCT) devices were used for on-time and on-site detection of the virus, which helped to prevent and control the spread of the pandemic. Smartphones, which are widely used electronic devices with many functions, have the potential to be used as a molecular diagnostic platform for universal healthcare monitoring. Several integrated diagnostics platforms for the real-time and end-point detection of COVID-19 were developed using the functions of smartphones, such as the operating system, power, sound, camera, data storage, and display. These platforms use the 5V output power of smartphones, which can be amplified to power a micro-capillary electrophoresis system or a thin-film heater, and the CMOS camera of smartphones can capture the color change during a colorimetric loop-mediated isothermal amplification test and detect fluorescence signals. Smartphones can also be used with self-written web-based apps to enable automatic and remote pathogen analysis on POCT platforms. Our lab developed a handheld micro-capillary electrophoresis device for end-point detection of SARS-CoV-2, as well as an integrated smartphone-based genetic analyzer for the qualitative and quantitative colorimetric detection of foodborne pathogens with the help of a custom mobile app. © 2023 SPIE.

Mobile Intellectual Property Marketplace Model for Commercialization of Intellectual Property Rights

This study discusses the development of the intellectual property (IP) marketplace model based on mobile location-aware computing. Referring to statistics released by the Directorate General of Intellectual Property, there has been a growth in the number of intellectual property rights (IPR) applications in recent years, even during the Covid-19 pandemic. On the other hand, after IPR protection, the commercialization of IPR is one of the pillars of the IP system. Nevertheless, research institutions such as LIPI/BRIN indicate that the potential for commercializing IPR is still low. Furthermore, the opportunity is that cellular networks have covered almost all parts of Indonesia, and there has been significant growth in smartphone users. The method utilized in this research is prototyping. This research results from an IP marketplace model based on mobile location-aware computing in Indonesia. Using the smartphone user's location, contextual IPR information from the user's location related to IPR will enter their smartphone. The experimental results indicate that the application can display a list of IPR information according to the smartphone user's location. Furthermore, the search feature can forage IPR listing information based on user queries. © 2022 IEEE.

Rapid, sensitive detection of intact SARS-CoV-2 using DNA nets and a smartphone-linked fluorimeter

We report a single-step, room-temperature, 5-10 minute SARS-CoV-2 saliva self-monitoring method that overcomes the limitations of existing approaches through the use of fluorophore-releasing Designer DNA Nanostructures (DDNs) that bind with the multivalent pattern of spike proteins on the exterior intact virions and an inexpensive smartphone-linked, pocket-size fluorimeter, called a "V-Pod” for its resemblance to an Apple AirPod™ headphone case. We characterize the V-Pod fluorimeter performance and the DDN-based assay to demonstrate a clinically relevant detection limit of 104 virus particles/mL for pseudo-typed WT SARS-CoV-2 and 105 virus particles/mL for real pathogenic variants, including Delta, Omicron, and D614g. © 2023 SPIE.

Teachers' Perceptions of Videoconferencing and Smartphones in a Retrospective Analysis 2009-2020: An Educational Social Internet of Things Framework

Schools have become increasingly influenced by what has been called the Social Internet of Things (SIoT). As many schools transitioned to online teaching and learning in 2020 because of the COVID-19 pandemic, there is a need to analyze data on technology adoption in schools for changes and continuity since the inception of increasingly popular smartphones since 2007 that has affected videoconferencing, blended learning, and the flipped classroom concept. In this study, videoconference technology is the main factor analyzed in relation to IoT and schools in which handheld devices are considered gateways to further integration of schools into an IoT framework. The researchers analyze a selection of a 2009 dataset and a 2019 dataset from the National Center for Education Statistics (United States) to discuss teachers' perceptions of technology, especially the use of handheld devices and videoconference technology. Recommendations for educator preparation programs (EPPs) are made based on the discussion of the results of this analysis in context with the events of 2020 for why EPPs could emphasize flipped classroom design models within an SIoT framework. © 2023 IEEE.

EyesOnMe: Investigating Haptic and Visual User Guidance for Near-Eye Positioning of Mobile Phones for Self-Eye-Examinations

The scarcity of professional ophthalmic equipment in rural areas and during exceptional situations such as the COVID-19 pandemic highlights the need for tele-ophthalmology. This late-breaking work presents a novel method for guiding users to a specific pose (3D position and 3D orientation) near the eye for mobile self-eye examinations using a smartphone. The user guidance is implemented utilizing haptic and visual modalities to guide the user and subsequently capture a close-up photo of the user's eyes. In a within-subject user study (n=24), the required time, success rate, and perceived demand for the visual and haptic feedback conditions were examined. The results indicate that haptic feedback was the most efficient and least cognitively demanding in the positioning task near the eye, whereas relying on only visual feedback can be more difficult due to the near focus point or refractive errors. © 2023 Owner/Author.

Monintoring Student Depression by Mobile Devices with Autoencoder Networks

The timely assessment of mental health is difficult since we lack the objective measurements of symptoms, especially for the Covid-19 pandemic quarantined students. Fortunately, smart phones can capture the real-world data such as the GPS traces and the phone active time et.al that link the behavioral patterns to the mental health. However, recent studies are based on a very small size of participants and only collect fewer phone features, which means that the effective predicting models which require various features are hardly adopted. In this paper, we develop an android application to record multidimensional data of users as well as a PHQ-9 and a SAS questionary, and we distribute it to 176 college students to collect larger scale data when in quarantine period. To address the unprecise problem of handcrafted feature extraction, we design an autoencoder machine learning model to monitor the student mental health. Extensive experiments indicate that the performance of the proposed method improves its F-1 score for PHQ-9 and SAS by 5% and 6% to the state of the current studies, respectively. © 2023 IEEE.

Impact of Covid Pandemic on OTT Streaming Services

Starting from Cable connections to various options in satellite TV brands, the transition paved the way gradually for free content on applications like YouTube, which further led to the demand for quality content on OTT platforms. Over-the- Top or OTT is the abbreviation for "over-the-top” which is a new age streaming of films and TV series over the web without the need for traditional cable, or satellite pay-TV providers;the consumers can stream across multiple gadgets according to our time convenience. Beginning in the late 90s, the early 2000s marked the era of Television streaming in India. The first OTT application launched in India was BigFix, which changed the course of content consumption in our country. The Television industry once driven by cable and satellite operators has transitioned into a consumer-driven domain. Unlike TV, which requires a cable connection or an antenna, OTT material is delivered directly over Online platforms and paid for directly by viewers. The implications are that the consumers may get OTT services including video, voice, messaging and audio services, at any time and from any location, which serves to be a significant advantage over traditional TV programming. In this paper, we focus on how this paradigm change took place and what impact it has created, especially since the pandemic. © 2023 IEEE.

Social Media App Usage in Relation with PHQ-9 Depression Scores during the COVID-19 Pandemic

With about 300 million affected people, major depressive disorder (MDD) is one of the most common diseases worldwide. During the COVID-19 pandemic, the number of cases increased even further, by 28%. Many factors may be correlated with MDD, including the excessive use of social media apps. In this paper, we investigated the relationship between the use of social media and communication apps and depressive symptoms during the COVID-19 pandemic. The pandemic and social distancing like lockdowns probably changed smartphone usage times and usage patterns. While previous studies have shown an association between depression and social media usage, we report about the situation during these special circumstances. We employed a log-linear regression to examine the association of social media and communication app usage and depression. To quantify the usage, we applied the total usage time in hours of social media apps (e.g., WhatsApp, Facebook) as well as communication apps (Phone and Messaging) within one week. To measure depressive symptoms, we used the PHQ-9 score. We discovered a significant association between the usage time and the PHQ-9 score (beta=0.0084, p-value=0.010). We conclude that social media usage is a robust marker for depression severity and future research should focus on a better understanding of the underlying causality and potential counter-measures. © 2022 ACM.

Need of Technological Interventions for Indoor Air Quality and Risk Assessment Upon Short-Term Exposure: A Futuristic Approach

The variation in ambient air pollution hampers indoor air quality (IAQ), and even the short-term variation is very hazardous for the exposed population. Technological interventions including sensors, smartphones and other gadgets are implemented to build smart environments. However, these interventions are still not fully explored in developing countries like India. The COVID-19 pandemic has made it very important to keep a tab on the air we breathe in as those already suffering from respiratory troubles are prone to fall victim to the deadly disease. In such a scenario, even a rise in pollution for a short duration is dangerous to the exposed pollution. Such short-term exposure facilitated by the meteorological creates a disaster for environmental health. The short-term rise in the concentration of pollutants makes things worse for the exposed people, even indoors. It is therefore critical to come up with a concrete solution to predict the IAQ instantly and warn the exposed population which can be only achieved by technological interventions and futuristic Internet of Things-based computational predictions. This chapter is intended to elaborate the health hazards linked to short-term rise in pollutants, which often goes unnoticed but has a critical impact and how with the help of IoT-based applications, the short-term variation can be predicted through different strategies. Similarly, the assessment of the health impact associated with short-term exposure to air pollution is also significant, and different exposure assessment models and computational strategies are discussed in the course of the study. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

COVID-19 Detection from Cough Recording by means of Explainable Deep Learning

The new coronavirus disease (COVID-19), declared a pandemic on 11 March 2020 by the World Health Organization, has caused over 6 million victims worldwide. Because of the rapid spread of the virus, with the aim to perform screening we exploit deep learning model to quickly diagnose altered respiratory conditions. In this paper, we propose a method to recognize and classify cough audio files into three classes to distinguish patients with COVID-19 disease, symptomatic ones and healthy subjects, with the use of a convolutional neural network (CNN). Cough audios were recorded by using a smartphone and its built-in microphone. From cough recordings, we generate spectrogram images and we obtain an accuracy equal to 0.82 with a deep learning network developed by authors. Our method also provides heatmaps, which show the relevant input areas used by the model for the final forecast, and this aspect ensures the explainability of the method. © 2022 IEEE.

The Tale of a Complicated Relationship: Insights from Users' Love/Breakup Letters to Their Smartphones before and during the COVID-19 Pandemic

Smartphones have gotten under public scrutiny due to their ostensible negative impact on users' well-being. Nonetheless, users and related work report positive aspects of smartphones, too. We investigated this discrepancy through the prism of the emotional user-smartphone relationship by having people write love/breakup letters to their smartphones. We gathered 82 letters - 42 before and 40 during the COVID-19 pandemic. We found a mixed nature regarding the distribution of love and breakup letters and associated emotions based on the revisited OCC-model of emotions - with a slight shift towards the negative emotional spectrum during the COVID-19 pandemic. Furthermore, we performed an extensive qualitative analysis of 819 user statements extracted from the letters, resulting in a connection of emotions to 17 smartphone features and eight themes of real-life consequences of smartphone use. We then identified eight common patterns of this connection, classified as smartphone roles. The collected letters mostly model a complex user-smartphone relationship, comprising different roles depending on users' inner and outer context. We discuss how HCI could help in shaping the complex user-smartphone relationship in future research and suggest supporting a healthy balance between users' daily life and smartphone use. © 2023 ACM.

Beauty Face: An Android Application for Cosmetic Consumers to Try On and Receive Product Recommendation

Nowadays, the number of smartphone users shopping online over the internet is increasing due to the COVID-19 pandemic situation. People need to stay safe at home and work from home according to the social distancing policy. It is difficult for people to go shopping onsite at a physical store. Especially, cosmetic consumers cannot try on cosmetic products, and they are not sure which product is suitable for them. Therefore, to solve these problems, this research project proposes 'Beauty Face', which is an android application for cosmetic consumers who would like to try on products and receive recommendations. The Beauty Face application allows users to find the desired products and view product information. Also, it provides a useful feature for users to try on products by applying augmented reality (AR) technology to simulate cosmetic and beauty products on the user's face. Moreover, the Beauty Face application can recommend products that are appropriate for users by applying machine learning (ML) technology. The Beauty Face application can be helpful for cosmetic users to be more convenient in buying cosmetic and beauty products online and reducing chances of being infected or spreading COVID-19. © 2022 IEEE.

Heart Rate Evaluation by Smartphone: An Overview

In this paper, an overview of the smartphone measurement methods for Heart Rate (HR) and Heart Rate Variability (HRV) is presented. HR and HRV are important vital signs to be evaluated and monitored especially in a sudden heart crisis and in the case of COVID-19. Unlike other specific medical devices, the smartphone can always be present with a person, and it is equipped with sensors that can be used to estimate or acquire such vital signs. Furthermore, their computation and connection capabilities make them suitable for Internet of Things applications. Although in the literature many interesting solutions for evaluating HR and HRV are proposed, often a lack in the analysis of the measurement uncertainty, the description of the measurement procedure for their validation, and the use of a common gold standard for testing all of them is highlighted. The lack of standardization in experimental protocol, processing methodology, and validation procedures, impacts the comparability of results and their general validity. To stimulate the research activities to fill this gap, the paper gives an analysis of the most recent literature together with a logical classification of the measurement methods by highlighting their main advantages and disadvantages from a metrological point of view together with the description of the measurement methods and instruments proposed by authors for their validation. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

Covid-19 Vest for Social distancing and Monitoring

In recent years, due to the rise in the number of novel coronaviruses across the globe nations step forward to stop the crisis. With guidelines of the WHO many methodologies came into existence to prevent the spreading of coronavirus. My SD: A Smart Social distance and Monitoring System takes advantage of the features of the smartphone's hardware which usually has Bluetooth transmitter-receiver, like GPS to determine the safe distance and required level of compliance. Through artificial intelligence, this new smart device helps maintain uniform social distance and detect COVID 19 patients. In these COVID 19 environments, everyone knows how safe they are. In this paper, we have automated the process whereby the layman can control himself without any priming which makes the system more user-friendly for the public. The user himself or herself can monitor body temperature, social distancing and get an alert in abnormal selfisolation conditions using contactless thermometer, ultrasonic sensors, and GSM modules. © 2022 IEEE.

Impact of Mobile Technology and Use of Big Data in Physics Education During Coronavirus Lockdown

The speed of spread of Coronavirus Disease 2019 led to global lockdowns and disruptions in the academic sector. The study examined the impact of mobile technology on physics education during lockdowns. Data were collected through an online survey and later evaluated using regression tools, frequency, and an analysis of variance (ANOVA). The findings revealed that the usage of mobile technology had statistically significant effects on physics instructors' and students' academics during the coronavirus lockdown. Most of the participants admitted that the use of mobile technologies such as smartphones, laptops, PDAs, Zoom, mobile apps, etc. were very useful and helpful for continued education amid the pandemic restrictions. Online teaching is very effective during lock-down with smartphones and laptops on different platforms. The paper brings the limelight to the growing power of mobile technology solutions in physics education. © 2018 Tsinghua University Press.

Wireless LAN Operation and Behavioral Inferences from Usage Analysis

The majority of network connections on campus is shifting from wired to wireless. Understanding and analyzing the usage of wireless LANs can lead us beyond mere network management to the analysis of users' behavior on campus and the discovery of new insights. In 2022, campus activity has returned to levels seen before the pandemic, but the effects of the COVID-19 disaster remain. Compared to pre-pandemic years, the use of wireless LANs on campus has increased significantly due to high smartphone ownership rates and the promotion of distance learning reliant on personally owned devices (BYOD). The use of multiple devices per person has also increased, creating new issues such as congestion and IP allocation problems. To accurately understand and improve these situations, we are collecting and analyzing connection information of our wireless LAN systems. Interestingly, our analysis of wireless LAN use provides information beyond the mere discovery of technical problems. From the results, we were able to identify ways we might improve the operation of the wireless LAN, as well as information to make inferences about the time spent by students on campus, their flow lines, and their behavior patterns. In this paper, we will report on the current status of the operation of the wireless LAN at Fukuoka University and the behavioral information inferred from our analysis of wireless LAN usage. © 2023 Owner/Author.

Sensor based Smart Plant Monitoring using IOT and Deep Learning: A Systematic Approach

As we can see, only a select few gadgets, such as PCs and smartphones, are internet-connected in the modern world and since governments across the world instituted lockdowns to stop the spread of COVID-19, interest in home gardening has exploded. Internet of Things (IoT) and the internet have completely taken over today's world. All humans utilize the internet to fulfill basic needs. The network of actual items is known as the Internet of Things (IOT). Simply put, it refers to the process of keeping an eye on a physical machine or object. It can also refer to the interconnection of physical objects that have been implanted with electronics, sensors, software, and network connectivity. The foundation of our nation is agriculture. The main issue in agriculture is water scarcity. The water resource is not used in an effective manner, so the water is wasted. To overcome this problem, we proposed plant monitoring approach. © 2022 IEEE.