Readwell: A Book Recommender Android Application with a Point-of-Sales System

The COVID-19 pandemic has given people much free time. With this, the researchers want to encourage these people to read instead of scrolling through social media. A barrier to reading for many people is not knowing what to read and disinterest in popular books that they would find when they search online. The existing websites that encourage book reading rely on social networking for their recommendations, while the collaborative filtering algorithms applied to books do not exist in the mobile application form. Readwell is a book recommender Android app with a Point-of-Sales System created using Java, Python, and SQLite databases. The information regarding the books was web scraped from the Goodreads website. It aims to apply the more efficient collaborative filtering algorithm to an accessible mobile application that allows users to directly buy the books they are interested in, thus encouraging the reading and buying of books. The researchers created unit test cases to validate the different functionalities of the application. © 2022 IEEE.

Android Based Smart Appointment System (SAS) for Booking and Interacting with Teacher for Counselling

An appointment system is going to be popular nowadays. The necessity of these types of systems is increasing day by day specially in education sector. Worldwide COVID-19 pandemic provoke the demand of these types of application. In this research paper, an Android-based appointment is built for booking an appointment and communicating with the teacher. To use this system both student and teacher have to an android device with connection of the internet. A single android application will be used for both types of users. Students can get the information of all teachers and book an appointment with teachers and teachers can accept or decline this appointment. Java programming language is used for this system and Google's Firebase is used for the database. In addition, the modern coding Architecture pattern MVVM (Model- View-View Model) followed to build this system. Hopefully, this system saves valuable time and makes the teacher-student interaction journey easier. © 2023 IEEE.

Smart Embedded Framework of Real-Time Pollution Monitoring and Alert System

The sustainability and progress of humanity depend on a clean, pollution-free environment, which is essential for good health and hygiene. Huge indoor auditorium does not have proper ventilation for air flow so when the auditorium is crowded the carbon di-oxide is emitted and it stays there for many days this may be a chance to spreading of COVID-19 and other infectious diseases. Without proper ventilation virus may present in the indoor auditorium. In the proposed system, emissions are detected by air, noise, and dust sensors. If the signal limit is exceeded, a warning is given to the authorities via an Android application and WiFi, and data is stored in cloud networks. In this active system, CO2 sensor, noise sensor, dust sensor, Microcontroller and an exhaust fan are used. This ESP-32 based system is developed in Arduino Integrated Development Environment (Aurdino IDE) to monitor air, dust and noise pollution in an indoor auditorium to prevent unwanted health problems related to noise and dust. More importantly, using IoT Android Application is developed in Embedded C, which continuously records the variation in levels of 3 parameters mentioned above in cloud and display in Android screen. Also, it sends an alert message to the users if the level of parameters exceeds the minimum and maximum threshold values with more accuracy and sensitivity. Accuracy and sensitivity of this products are noted which is very high for various input values. © 2022 IEEE.

HanAPP Buhay: Android Java-Based Mobile Commerce Application for Freelance Home Service Providers and Client Job Seekers

Service providers from the informal sectors in the Philippines are left unemployed or want to look for part-time jobs due to the sudden COVID-19 pandemic. With the country on lockdown and as strict restrictions are implemented, people started adopting the e-commerce and m-commerce market. The rise in the Filipino masses using smartphones and participating in mobile commerce to purchase products and services over the Internet has given researchers a potential solution for the arising problem. Thus, the primary objective of the research is to design and develop a user-friendly mobile application that will give a platform where potential home service providers can offer their services to potential clients. HanAPP Buhay, a mobile application that is created in Android Studio with Java as a programming language, is a platform where service providers can offer a variety of home services including laundry, plumbing, cleaning, and electrical works to potential clients. As for the Application Programming Interface (API), Stripe and Firebase are the tools utilized for databases and transaction purposes. The researchers conducted a series of surveys and experiments and have determined that in the 38 trials, the HanAPP Buhay mobile application is functioning 100% accurately as expected, 99.995382330563% and 99.994941213182% working at real-time booking of appointments in the 16 trials for clients and 22 trials for workers respectively, have a reliable user's interface and secured data of both users through the Scrypt algorithm, and effective in its overall specifications in terms of customer's satisfaction. © 2022 IEEE.

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.

Development of an Android Application for Tracking Post COVID Symptoms

Patients with COVID-19 generally recover within a fortnight or a month. However, some patients, even those with milder types of the disease, experience symptoms after they have recovered. Symptoms of COVID-19 might continue for months at a time. The virus affects the heart, brain, and lungs, perhaps leading to long-term health-related problems. Thus, it is critical to keep track of any post-COVID symptoms to prevent further complications. Keeping that in focus, two apps are created to monitor these symptoms in people who have recovered from COVID 19 with comorbidities includes Diabetes, coronary artery diseases and hypertension. In this project, the patient's data was obtained from selected hospitals in Pune, and stored in Google Firebase. This data was used while making the backend algorithms for the apps. Android Studio and Figma were used to design and develop these apps. One app will be used by the patients, which allows them to post their health conditions if they are suffering with symptoms of post COVID complications and another App will be used by the investigators to monitor these symptoms and provides an access to post the advises pertaining to the patient's health condition. The biggest challenge is with patients suffering from conditions like hypertension, diabetes and other chronic illness which can be fatal if not monitored and addressed, specially for the elderly to frequently visit the hospital just for monitoring. The prime objective of the app developed in this work is to provide monitoring and to prevent post COVID complications and save the life of patients who have recovered from COVID and already have underlying issues. These apps allow researchers/Doctors to contact the patients personally to counsel them against the symptoms they are experiencing. Both these apps were tested in Android 8 Oreo and are functional in Android 8 Oreo, Android 9 Pie, Android 10, and Android 11 supported devices. These applications will soon be deployed in the Play Store. © 2023 IEEE.

Geometrical Tolerances Android Application Developed for Student for a Better Understanding of Orientation Tolerances According to the Latest ISO Standards

In the year 2021, a virtual reality training application has been developed, specifically for the Oculus Quest 2 headset, in order to allow the users to view and analyse 3D models for a wide variety of geometrical tolerances, tolerance zones and even the conformity condition and the datum features. This application allows the students to better understand the geometrical tolerances in accordance with the latest ISO GPS standards by using different 3D interactive models in order to highlight different types of geometrical tolerances and tolerance zones. In order to try to make the virtual reality training application more mobile and accessible for students, a mobile application, designed for the android operating system smartphones, has been developed. This application can facilitate better learning outcomes within the teaching-learning process by enabling the students to visualize a wide variety of 3D models representing different types of geometrical tolerances. Due to the dramatic evolution of technology in the past 20 years and the need to constantly keep up with it, the learning and teaching process suffered a massive change. The Covid pandemic has closed Universities all over the world and so, for the teaching process to continue, a sudden shift from traditional teaching to a more modern one involving the digital world was needed. Thanks for the fact that, nowadays, students are more inclined to use different types of mobile devices, the shift to the new learning paradigm has not left a great "scar” on student and teachers. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

CovScan: Smart non-contact IR-Temperature scanning and online database system integrated with RFID authentication

Considering the public safety in current COVID-19 out-break, an IOT (Internet of Things) based non-contact temperature monitoring system integrated with RFID authentication system with an interactive Android application, and a web-portal to manage users and temperature records has been proposed. Temperature screening has become essential for all the industries, educational institutions, factories and corporate sector. This system is an online real-time non-contact monitoring system with an interactive android application and user-friendly web portal that help end-users to monitor and keep a record of temperature variations of registered users on daily/weekly/monthly basis. The temperature records are saved in a real-time database which is embedded with the user's RFID card information. In case of an alert (high temperature), a notification is sent to the authorized personnel on their cellphones or their desktop systems via web portal. An alarm is also generated immediately on the device (buzzer and blinking LEDs) to indicate high temperature, alerting the nearby security staff. As per the survey and testing of the device under different temperature environments it has been found that the proposed system has an overall accuracy of 99%. © 2022 IEEE.

Android Application for Human Respiratory System Diagnosis: A Systematic Review

This paper presents a systematic review of android app respiratory system on smartphone. For some diseases, doctors have succeeded in inventing the necessary treatments that lasts for a short period, but in several cases, the treatment can stay for a lifetime. The goal of this system is to detect if a patient has any respiratory disease(s) by specifying the symptoms the patient encounters, schedules an appointement in the hospital for patient through the system to the linked specialist doctors to avoid contact in the case of Covid-19 patient. This research will help raise patient's awareness of the high risk of late discovery of having respiratory diseases (like Lung Cancer. corona virus etc), and also to develop a model that will help detect this disease early through mobile application. The focus of this review is to encourage medical institutions to adopt the health android app that can help patients in self-managing behavioral activities such as physical activities, using symptoms to determine the stage(early or critical) of the disease and drug suggestions with research evaluation using the app, this could help patients monitor and manage their health conditions. © 2022 IEEE.

Fitness Industry Propelling on IoT

In the contemporary work-from-home period and the previous Covid-19 times, fitness or, to put it another way, obesity, has emerged as a significant issue. Technology usage has suddenly increased and become ingrained in our daily lives. For the development of such individuals, we are developing the fitness application FITWORLD, which supports individuals in achieving their objectives by offering customised training and dietary regimens. Our proposal is based on research into the workout habits of many individuals with various objectives and BMIs. These guidelines are simple to follow and help boost immunity, which further guards against Covid. We are leveraging a variety of technologies and tools, including: •Android Studio •Kotlin •XML •Draw.io •Figma •Star UML •Firebase As a consequence, we are striving to create Fitworld, an app, employing the tools and technologies indicated above. By assisting individuals in maintaining a healthy lifestyle via the use of our app, we want to make our nation healthy and fit in the future. © 2022 IEEE.

REMICARE—Medicine Intake Tracker and Healthcare Assistant

An automated reminder mechanism is built in this Android-based application. It emphasizes the contact between doctors and patients. Patients can set a reminder to remind them when it is time to take their medicine. Multiple medications and timings, including date, time, and medicine description, can be programmed into the reminder by using image processing. Patients will be notified through a message within the system, as preferred by the patients. They have the option of looking for a doctor for assistance. In this COVID-19 pandemic situation where nurses have to remind the patients in the hospitals to take their medications, our application can be useful, alerting the patient every time of the day when he/she has to take the medicine and in what amounts. Also, all the necessary tests report and prescriptions can be saved on the cloud for later use. Patients will be provided with doctor contact information based on their availability. Also, patients will be notified of the expiry date of the medicine, and the former history of the medicines can be stored for further reference. The proposed system prioritizes a good user interface and easy navigation. Image processing will be accurate and efficient with the help of powerful CNN-RNN-CTC algorithm. It also emphasizes on a secure storage of the user's data with the help of the RSA algorithm for encryption and the gravitational search algorithm for secure cloud access. We attempted to create a Medical Reminder System that is cost-effective, time-saving, and promotes medication adherence. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

An experience in the use of SCRUM and KANBAN for project development in a Waterfall environment

SIDIA R&D Institute is responsible for developing, validating, and localizing the Android Operating System (Android OS) used in smart devices, such as smartphones and tablets, sold in Latin American countries. Traditionally, SIDIA's Model department is responsible for such development, and it is comprised of smaller teams working on individual Android components. For example, the Application team works on the Android's System Apps layer, such as Photo Gallery and Phone Dialer. Like all Model's teams, the Application employs the Waterfall methodology, a straightforward and widespread software development framework. However, the Application team can receive requests to work on projects unrelated to its primary activities. In these cases, the Waterfall methodology is unsuitable because it follows a linear pipeline [1], making it challenging to work on multiple and simultaneous projects. Hence, the present paper aims to report the experience of the Application team in transitioning from a pure Waterfall environment to a mix of Waterfall and Agile methodologies. Specifically, the team applied the SCRUM and KANBAN methodologies in four independent projects. The challenges caused by this culture change and the COVID-19 pandemic, which forced our workforce to work from home, are reported here. Furthermore, the team used Retrospective and Post-Mortem meetings to gather feedback from members about their experience with these new methodologies. © 2021 ACM.

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.

Suspicious Permissions Detection of Covid-19 Themed Malicious Android Applications

The malicious actors continuously produce malicious Android applications with a COVID-19 theme in the context of the pandemic. Users frequently grant the necessary permissions to install those phoney apps without paying much attention. Android permissions are essential points of weakness. Major privacy issues often result from this vulnerability. Hackers with malicious intent have viewed the COVID-19 pandemic as an opportunity to conduct malware attacks to profit financially and advance their nefarious goals. Through COVID-19-related content, people are becoming victims of phishing scams. The android malware seen explicitly during the pandemic of Covid-19 is discussed in this study, and we next analyze malware detection methods with a focus on these Covid-19-Themed malware mobile applications. This research paper attempts to identify dangerous android permissions and the malware families that erupted during the Covid-19 outbreak. © 2023 IEEE.

No Salvation from Trackers: Privacy Analysis of Religious Websites and Mobile Apps

Many religious communities are going online to save costs and reach a large audience to spread their religious beliefs. Since the COVID-19 pandemic, such online transitions have accelerated, primarily to maintain the existence and continuity of religious communities. However, online religious services (e.g., websites and mobile apps) open the door to privacy and security issues that result from tracking and leakage of personal/sensitive information. While web privacy in popular sites (e.g., commercial and social media sites) is widely studied, privacy and security issues of religious online services have not been systematically studied. In this paper, we perform privacy and security measurements in religious websites and Android apps: 62,373 unique websites and 1454 Android apps, pertaining to major religions (e.g., Christianity, Buddhism, Islam, Hinduism). We identified the use of commercial trackers on religious websites—e.g., 32% of religious websites and 78% of religious Android apps host Google trackers. Session replay services (FullStory, Yandex, Inspectlet, Lucky Orange) on 198 religious sites sent sensitive information to third parties. Religious sites (14) and apps (7) sent sensitive information in clear text. Besides privacy issues, we also identify sites with potential security issues: 19 religious sites were vulnerable to various security issues;and 69 religious websites and 29 Android apps were flagged by VirusTotal as malicious. We hope our findings will raise awareness of privacy and security issues in online religious services. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

E-Passport COVID-19 Adopting RFID Implants based on Microservices

COVID-19 has spread throughout the global and has restrained humans in all aspects of life including society, economy, education, etc. The first Corona virus appeared in China on 2019 and had mutated into several variants such as B.1.1.7 (Alpha), B.1.351 (Beta), E484Q (Delta), and BA.2 (Omicron). In order to block the virus to mutate and spread in the communities, we proposed a design of E-Passport by adopting RFID Implants with integrated Microservices technology. Our concepts is we design an android application (E-passport) that will be used by every institution on public places to stop the positive patients getting inside the public space to spread the virus. The checker in every public places need to scan the RFID implants on every humans hand by using NFC technology embedded on android phone with installed E-Passport to determine whether can enter or forbidden to enter. The RFID Implant stored a unique code that can be read as the reference of the person's data information stored in cloud database based on Microservices infrastructure. Our proposed design and architecture are dedicated to stop the COVID-19 virus to spread among public communities. © 2022 IEEE.

E-Commerce Platform with Recommender System and Android Mobile Application

E-commerce shows steady growth in the marketplace since it makes the lives of people easier. Today's generation is more inclined toward convenience in purchasing goods. The COVID-19 shut down many food establishments across the Philippines, resulting in an online bakeries boom. Pastries are one of the most sought goods online, especially with the pandemic surge where physical stores are seldomly open. E-commerce with a recommender system is the trend that helps customers choose products, which helps in decision-making on what to purchase. On the other hand, a mobile application counterpart could increase brand recognition and customer engagement as it is now the most effective, direct, and personalized way to deliver product information. In this study, the descriptive research method was used, with a questionnaire using the functionality, usability, reliability, performance and supportability (FURPS) serving as the instrument for testing the acceptability. The overall quality of the system was given an acceptable rating with a weighted mean of 4.07, indicating that the system's functions were well integrated, that navigation was simple, performed consistently, and that the system was accessible regardless of device. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

A Friendly Interface Medical Service Robot with Fault-tolerant Voice Recognition and Mobile Phone Remote Control

In recent years, due to the impact of COVID-19 around the world, there has been a serious shortage of medical resources. In order to supplement the manpower and fear that medical staff's contact with patients will cause a breach in the epidemic, reduce the workload of nurses, and help nurses perform repetitive tasks so that nurses can concentrate more on the patient's condition. Therefore, this paper proposes M-Robot, which is a friendly interface service robot based on the Android system and can be controlled by voice, touch, and remote control in the medical care field. The system is mainly divided into two parts. One is the web server. The web server is divided into two parts: front-end and back-end. The front-end is responsible for friendly user interface management, and the back-end is for accessing the SQLite database, as well as processing speech recognition and semantic understanding in voice services. In the other part, we use TEMI robot to develop and complete the desired service. Its service content includes environment introduction, delivery service, questionnaire survey, broadcast car, scheduling reminder, follow-up record, and patient instruction video. In the voice control mode, the user can say the wake-up word to the robot and say the required service content, and the robot will execute after receiving the message;in the remote control mode, we provide a friendly web interface for remote control. As well as the information needed to manage various services. © 2022 IEEE.

An Android-Based Application to Detect COVID-19 and Pneumonia Using Deep Learning

The novel coronavirus disease has produced destructive effects on human life, taking away millions of lives. The biggest bottleneck in detecting the COVID-19-affected patient is the limited availability and time-consuming features of conventional RT-PCR tests and the lack of specialized sample extraction laboratories. Early detection of this virus may help in the advancement of a medication approach and disease control strategies. In this research, we have developed an Android smartphone application that can detect pneumonia and COVID-19 from chest X-ray photographs using convolutional neural network deep learning algorithms (VGG16 and VGG19). The COVID-19, pneumonia, and healthy chest X-ray images are collected from various repositories of a public database, Kaggle. After applying the data augmentation technique, 9,000 chest X-ray photographs were used for training, including 3,000 images for COVID-19, pneumonia, and normal cases. For testing, 3,000 chest X-ray photographs were collected, with 1,000 images for all three cases. VGG16 model achieved better performance than the VGG19 with a training accuracy of 98.31% and validation accuracy of 95.03%. Next, the deep learning-based automatic classification framework is deployed into a smartphone application. Finally, the application has been tested and assessed by a focused group, and analytical results have been presented. © 2022 IEEE.

Sentiment Analysis Model for KlikIndomaret Android App During Pandemic Using Vader and Transformers NLTK Library

COVID-19 has changed the Indonesian people's shopping habits for consumer goods. The online retail application came as a response to social distancing and stay-at-home advice. KlikIndomaret is an online retail application that uses the omnichannel concept. As the number of downloads increased, the number of various comments and sentiments on that application also increased. In this study, the researcher did a sentiment analysis aimed to improve the quality of application experiences and retail services. The result of the analysis reflected the services given to customers thus far. The data included reviews and star ratings derived from 4,066 reviews which went under the process of data pre-processing. The methods used in this study were VADER and NLTK, improved by Transformer, without pre-training data. These methods could filter the users' reviews with sarcasm tone. The results were sentiment labels that were appropriate based on the score comparison of positive and negative sentiments in one user's review. This approach made the review sentiment process of thousands of data faster and more accurate. © 2022 IEEE.