Smartphone Research Articles

Can we Use Smart Phone on a Moving Vehicle Without Worrying About Carsickness? Developing an Effective Motion Cue APP with Driving Simulator and Real Vehicle Experiments

The prevalence of motion sickness among passengers using personal electronic devices, such as smartphones, during vehicle journeys has become a growing concern. This issue is expected to intensify with the increasing adoption of assistant or automated driving functions, which may lead to non-driving tasks (NDT) being performed by all on-board passengers, including the user in the “driver” seat during conditionally or fully automated driving modes. This trend presents challenges related to motion sickness, particularly in terms of specific performance requirements for non-driving tasks. In response to the need to alleviate passenger motion sickness, we have developed an easy-to-understand animation cue app that can be conveniently implemented on smartphones. The motion cue conveys information about vehicle accelerations, including their directions and magnitudes, using the metaphors of traffic signal colors and backward-moving lane lines, either in straight or curved lane driving. Following several rounds of improvements based on moving-base simulator and real car experiments, finally a successful cue design was found, which could significantly alleviate motion sickness of passengers while engaging in NDT, with minimal impact on their NDT performances. However, the study also revealed limitations to the sickness-alleviating capability of our motion cue design, including potential lack of universal acceptance among different users and reduced effectiveness in severely uncomfortable driving conditions. This work may provide valuable insights for further visual cue improvements that can contribute in future carsickness-proof vehicles.

The effect of smart phone applications on the effect of fractal teaching by means of smart phone applications on the development of conceptual understanding among students of the College of Education

The effect of smart phone applications on the effect of fractal teaching by means of smart phone applications on the development of conceptual understanding among students of the College of Education

Laboratory Automation System Using IOT Device

Agriculture has a major role in the overall economic prosperity of a nation. An important component of smart agriculture is the Internet of Things (IoT). This project aims to construct an automated agriculture system that maximizes crop consumption of water and fertilizer. This endeavor also include identifying animals and stopping trees. The goal of the project is to create more efficient ways to handle irrigation systems manually and automatically with a smart phone. The proposed system utilizes embedded devices, PROTEUS software, and MPLAB. The present study offers a comprehensive approach to the supervision and control of an intelligent irrigation and regulating system.

A “Turn-Off” Pyrene-Based Ligand as a Fluorescent Sensor for the Detection of Cu2+ and Fe2+ Ions: Synthesis and Application in Real Water Samples, Logic Gate Construction, and Bio-Imaging

Herein, we report the synthesis and characterization of a novel Schiff base ligand, (Z)-5-((pyren-1-ylmethylene)amino)-2,4-dihydro-3H-pyrazol-3-one (PMDP). The characterization of ligand PMDP was carried out using ESI-MS, 1H NMR, and UV–Visible spectroscopic techniques. As a probe, PMDP displayed a detectable, colorimetric colour shift in the presence of Cu2+ and Fe2+ ions. The solution was seen to have a light brown colour and to exhibit a fluorometric “turn off” response when Cu2+ and Fe2+ ions were present in a DMSO solution (HEPES 0.01 M, pH = 7.4) at room temperature. Job’s plot revealed that the PMDP binding ratio to Cu2+ and Fe2+ ions was in 1:2 ratio. In contrast to the other metal ions (Cd2+, Mn2+, Co2+, Na+, Ni2+, Cu+, Fe3+, Hg2+, Mg2+, Zn2+, K+, and V5+), the synthesised probe showed exceptional sensitivity and selectivity for detecting Cu2+ and Fe2+ metal ions. The results indicate that the detection limits for Cu2+ and Fe2+ are 0.42 μM and 0.51 μM, respectively. Furthermore, PMDP was efficiently utilised for the quantitative analysis of Cu2+ and Fe2+ in real water samples, RGB colour values in smart phones, logic gate construction, and cell imaging in HeLa cells.

Revolution in Data Market: A Study on Data Consumption in India

India has been a developing country; in the process of development India has seen massive revolution in information technology. As information technology industry is growing in a fast phase that has enabled the people to use smartphones and computers extensively which has resulted in excessive consumption of data. Smart phones are not just phones now they have become an integral part of our life, as a result of which the data consumption has also seen an immense growth. In this article we will be discussing on how smart phones have replaced many elements and also how extensively data is being consumed in the name of entertainment, though India is in developing stage which has a lot of disparities in rural and urban region, but in urban and semi urban and also in rural some portion of society, terrain there is a community which is using the data enormously. Data consumption has grown a massive growth specially in the period of covid. The covid lock down has also contributed to the OTT platforms like amazon prime, Netflix, voot, zee5 etc are demanded by the middle income and high income group people. We will be comparing the average amount spent on data purchase and average amount of data consumed per head. In this article we have attempted to understand at what rate data is being consumed, what is the average amount of money spend on data per head.

A Model for Detection and Prevention of AndroRat in Mobile Devices

Android operating systems has gained increasing popularity in smart phones and other mobile intelligent terminals in recent years. Unpleasantly, the accumulation development and open nature of the platform has also attracted a vast number of malware developers. This dissertation presents a model for detecting and preventing AndroRat, a notorious Remote Administration Tool (RAT), on android devices. The research systematically pursued predefined objectives, leading to the development of a robust detection framework that utilizes the Outlier Technique. This framework significantly enhances the accuracy of AndroRat identification. Moreover, the dissertation introduces a preventive mechanism based on Recurrent Neural Network (RNN), fortifying Android phones against potential threats posed by RATs. By achieving the outlined objectives, this research makes a noteworthy contribution to the field of mobile device security. It demonstrates a practical application of machine learning techniques in mitigating evolving cybersecurity threats. A dataset was gathered for constructing the model. Object Oriented Analysis and Design (OOAD) was used as the research methodology and python was used as the programming language. The implementation of the Python Programming Language in this system not only ensured efficient execution but also established a versatile and accessible platform, laying the groundwork for future enhancements and adaptations. The comparative analysis conducted against existing systems highlights the effectiveness and innovation embedded in the proposed model, affirming its potential as a valuable addition to the realm of AndroRat detection and prevention with an accuracy of 99.99%. This dissertation not only addresses current security challenges but also establishes a foundation for continued advancements in mobile device security through the integration of cutting-edge technologies.

Highly sensitive and flexible ammonia sensor based on PEDOT:PSS doped with Lewis acid for wireless food monitoring

Ammonia serves as a crucial indicator of food spoilage, but current sensors lack sufficient sensitivity, stability, selectivity, and automation for practical on-site and real-time monitoring. A highly sensitive and flexible ammonia sensor based on PEDOT:PSS doped with Lewis acid (FeCl3 solution) for wireless food monitoring is proposed in this study to solve the above limitations. The intercalation effect caused by the diffusion of Fe3+ and hydrolyzed H+ in the film coordinating with SO3− groups present in PSS chains leads to an increased distance between adjacent PEDOT-rich domains. It enhances ammonia sensitivity by providing additional ionic carriers and carrier transport paths within the PEDOT:PSS molecule. The results demonstrated a significant enhancement in the sensitivity of PEDOT:PSS sensor doped with FeCl3, exhibiting a response value of about 25 % at 25 ℃ for 1 ppm NH3, with an impressive detection limit of 0.23 ppm and quantification limit of 0.78 ppm (1–400 ppm). Moreover, it showcases acceptable repeatability both at 1 ppm (RSD = 4.30 %) and 100 ppm ammonia (RSD = 3.61 %), along with the notable selectivity and long-term stability. XPS, Raman analysis, and the density function theory (DFT) calculations further elucidated the sensing mechanism of the sensor towards ammonia. Additionally, a portable wireless detection device was designed, which was equipped with the Bluetooth communication and the micro-controller system to detect the decay process of fresh shrimp, realizing wirelessly real-time monitoring of food freshness through a smart phone. It’s worth noting that the innovative sensing technology holds great promise for food quality monitoring.

VolMemDroid—Investigating android malware insights with volatile memory artifacts

Android based smartphones have become a top target for malware writers due to their widespread use. A number of malicious applications are present on play stores and downloaded on daily basis, posing a significant threat to users’ personal and business data. As a result, the design of malware analysis frameworks is crucial in protecting the growing number of users who rely on their smart phones for routine and business tasks. The traditional signature based schemes for malware detection are unable to handle new and sophisticated malware. Furthermore, generic solutions based on static analysis schemes become less effective in the presence of obfuscated malware. In this study, a dynamic analysis based framework, VolMemDroid, for detecting malicious applications for Android is proposed. The framework extracts the volatile memory artifacts for profiling malicious Android applications. For this purpose, the memory forensic framework of volatility is utilized. A number of volatility plugins are analyzed for their compatibility w.r.t the Android platform and their ability in modeling the application’s behavior. After testing a number of plugins, chosen plugins are further processed for extraction of features. A comprehensive feature set for Android malware detection and categorization is proposed. It has been found that the suggested framework is effective for detecting Android malicious applications with an F1-score of 0.972, which is better than existing volatile memory based approaches for Android malware detection. The framework is also found to be effective in categorizing malicious Android applications into four distinct classes.

A Study on the Design of Smartphone APPs Targeting the Behavioral Characteristics of the Elderly under the Background of Artificial Intelligence

As a practical technology, artificial intelligence has an important impact on the development of mobile media. Intelligent analysis and understanding of user behavior and realistic personalized service have become key factors in APP development. At the same time, China has entered the development stage of a deeply aging society, and the discussion on the "age-appropriate" design of smart phone APPs for elderly users is not sufficient. Through literature review, the physiological characteristics of the elderly are combed and analyzed. With the help of field interviews, the behavioral characteristics of the elderly are deeply studied and their characteristics are summarized. Based on this, the design and practice of smart phone "aging" APP are completed, and the theoretical model is constructed. It is hoped to provide reference for the design, development and renewal of digital products for the aged in China.

A non-contact colour correction system on mobile display under various light sources

Human recognize perceived color on the display device of a smart phone under various types of light sources and illuminance differently even though the display represents the same color. This study investigated the relationship between input RGB code and output color tristimulus (XYZ) on two types of smartphone displays under various types of light sources and illuminances. A non-contact color correction system to transfer similar color with actual object was then proposed under various types of light sources and illuminances. Furthermore, the color correction model was validated by input color RGB predicted for representing the desired color and a survey test on displays of two types of smartphone, iPhone 13 Pro and Galaxy S22.

A review of the challenges and opportunities in implementing health informatics in rural healthcare settings

This paper reviews the challenges and opportunities associated with implementing health informatics in rural healthcare settings. It examines the unique barriers rural communities face, such as infrastructure limitations, workforce shortages, and financial constraints, which can impede the adoption and utilization of health informatics solutions. However, it also explores the promising opportunities afforded by health informatics, including telemedicine, electronic health records (EHRs), and mobile health technologies, to overcome these challenges and improve healthcare access, quality, and efficiency in rural areas. By addressing these challenges and leveraging the opportunities presented by health informatics, stakeholders can work towards achieving equitable healthcare outcomes for rural populations. By addressing these challenges and leveraging the opportunities presented by health informatics, stakeholders can work towards achieving equitable healthcare outcomes for rural populations. Health informatics holds immense potential to revolutionize healthcare delivery, particularly in rural settings where access to quality care is often limited Health informatics holds immense potential to revolutionize healthcare delivery, particularly in rural settings where access to quality care is often limited. Health informatics holds immense potential to revolutionize healthcare delivery, particularly in rural settings where access to quality care is often limited. Telemedicine, for instance, enables remote consultations and diagnostic services, breaking down geographic barriers and providing rural patients with access to specialists and healthcare expertise they may not have locally. Electronic Health Records (EHRs) streamline administrative processes, improve care coordination, and enhance patient safety by ensuring that vital health information is readily accessible to healthcare providers regardless of location. Mobile health technologies, including smartp hone apps and wearable devices, empower rural residents to monitor their health, track chronic conditions, and engage in self-management activities from the comfort of their homes.By embracing these innovations and overcoming infrastructure challenges, stakeholders in rural healthcare can significantly improve healthcare access, quality, and efficiency. Additionally, leveraging health informatics can help address workforce shortages by enabling healthcare providers to deliver more effective and integrated care, even in remote areas. Ultimately, by harnessing the opportunities presented by health informatics while addressing the unique challenges of rural healthcare, stakeholders can work towards achieving equitable healthcare outcomes for rural populations. Keywords: Health Informatics, Rural Healthcare, Electronic Health Records (EHRS), Mobile Health, Challenges.

Impact of integrating smartphones in the teaching and learning of Mathematics in Mberengwa district, Zimbabwe

Worldwide, the utility of smartphones in the teaching and learning of Mathematics has been greatly recognized and taken advantage of. This is mainly because of the precisions this technology can bring in the classroom. This study investigated the impact of integrating smart phones in the teaching and learning of Mathematics at secondary schools in Chegato Cluster in Mberengwa district, Zimbabwe. It also examined strategies that can be used to enhance the use of smartphones in these schools. The study used a mixed method approach where both qualitative and quantitative data was gathered and was used to answer the formulated research questions. Ten parents, 10 Mathematics teachers, 4 school heads and 40 learners participated in the study. The study found that the introduction of the competence-based curriculum by the ministry of Education in Zimbabwe, which is in solidarity with Education 5.0 calls for the use of smart phones in the teaching and learning of Mathematics which ensures that several modern skills are being acquired by learners in Chegato secondary schools. Learners in Chegato Cluster benefit by using smartphones to store soft copies of various Mathematics textbooks which are often scarce in hard-copy form. Students also benefit from Mathematical applications that are installed in their smartphones. Teachers use smartphones as media in the classroom to enhance learner-understanding of the concepts. Again, in Chegato, the use of smartphones has exposed learners to various Mathematical technological skills that help in the learning of Mathematics and has the potential of improving the pass rate. School heads and teachers acknowledged that the availability of smartphones in the schools has greatly assisted “O” level Mathematics learners to accomplish their tasks.Strategies that can be used to enhance the use of smartphones in secondary schools include the use of individualised student passwords which are controlled and monitored by the school administrators to ensure that the activities of each learner on the Internet can be tracked and any attempts by students to visit undesirable sites are detected. Also, the use of software applications, such as Mikrotik Hotspot Blocker, can be used to block students from accessing unsavoury Internet sites. The study concluded that though challenges such as lack of technological resources and some educators’ negative attitudes towards the use of smart phones affect Chegato Cluster, most participants found it helpful to use smartphones in the classroom because the gadget expose learners to new and better ways of dealing with Mathematical concepts. The study finally calls for all the involved parties in the cluster and beyond to actively take up their responsibilities facilitating the use of smartphones for the benefits of the students.

Utilizing Real – Time Face Recognition Based Bio-Metric System for Online Transaction

A crucial component of contemporary banking is now online banking. Due to the present password- based authentication paradigm’s inadequacies in terms of efficiency and robust, as well as their suspectibility to automated attacks, several attempts are successful in gaining access to social network accounts. The easiest solution is to add more identifying features, like one-time PIN numbers that are created by the user’s own device(like a smart phone) or sent to them via SMS to the single factor(Password-based) authentication procedure. With the help of this technology, client’s identities may be instantly and conveniently verified. The goal of this project is to create an online banking system that authenticates customer’s using real-time facial recognition technology. The system will be made to offer a safe and convenient user interface that enables users to perform financial operation like bill payment, money transfers, and balance queries. A facial recognition algorithm, such Grassmann learning, which can record and evaluate customer’s facial traits in real time, will be included into the system. To confirm customer’s identification, the algorithm will match the customer’s facial traits with those in the bank’s database. The technology would give users a safe and convenient interface to conduct real-time banking transactions. Notifications about banking amount transactions are sent to the user in this suggested netbanking application.

Feature fusion method for pulmonary tuberculosis patient detection based on cough sound.

Since the COVID-19, cough sounds have been widely used for screening purposes. Intelligent analysis techniques have proven to be effective in detecting respiratory diseases. In 2021, there were up to 10 million TB-infected patients worldwide, with an annual growth rate of 4.5%. Most of the patients were from economically underdeveloped regions and countries. The PPD test, a common screening method in the community, has a sensitivity of as low as 77%. Although IGRA and Xpert MTB/RIF offer high specificity and sensitivity, their cost makes them less accessible. In this study, we proposed a feature fusion model-based cough sound classification method for primary TB screening in communities. Data were collected from hospitals using smart phones, including 230 cough sounds from 70 patients with TB and 226 cough sounds from 74 healthy subjects. We employed Bi-LSTM and Bi-GRU recurrent neural networks to analyze five traditional feature sets including the Mel frequency cepstrum coefficient (MFCC), zero-crossing rate (ZCR), short-time energy, root mean square, and chroma_cens. The incorporation of features extracted from the speech spectrogram by 2D convolution training into the Bi-LSTM model enhanced the classification results. With traditional futures, the best TB patient detection result was achieved with the Bi-LSTM model, with 93.99% accuracy, 93.93% specificity, and 92.39% sensitivity. When combined with a speech spectrogram, the classification results showed 96.33% accuracy, 94.99% specificity, and 98.13% sensitivity. Our findings underscore that traditional features and deep features have good complementarity when fused using Bi LSTM modelling, which outperforms existing PPD detection methods in terms of both efficiency and accuracy.

Fake News Detection using Machine Learning

Fake News Detection using Machine Learning

Smart and Intelligent Weather Adaptive Street Lighting System Using IoT

In this paper, an Internet of Things (IoT)- based smart and intelligent weather-adaptive street lighting system containing an Arduino UNO, an ESP 8266, an LDR, a voltage sensor, a current sensor, a PIR, a relay, and a mobile or web application is designed and implemented. This project's primary goal is to create an intelligent and adaptable street lighting system that will guarantee constant lighting for rural residents. This project is to minimize the electricity losses, reduce the manpower used in manually switching on-off the street lights and & energy cost. There are three primary parts to the system: An Arduino NANO, ESP 8266 is a Wi-Fi module for signal transfer and a smart phone that can operate web page servers. These days, consumers are searching for smart systems that require less maintenance and use less energy. This intelligent street light only turns on when needed, and it continues to run on its own subsequent evenings even in the absence of sunlight. Furthermore, an Arduino NANO was used to include a PIR sensor, which detects motion and turns on the lights to bright mode by turning on more lights. Taking those factors into account, these smart streetlights are equipped with an Internet of Things (IoT) powered adaptive system that can detect malfunctions and send message to parent system.

A New Intelligent Home Automation with Integration of Solar and Grid

This project presents a groundbreaking paradigm shift in residential energy management and automation, offering an innovative solution that seamlessly integrates two diverse energy sources: solar and conventional grid (EB) power. With solar energy taking precedence as the primary power supply, meticulously controlled by the versatile ESP32 microcontroller, the system ensures a consistent and reliable energy supply by intelligently switching to grid power when solar resources are scarce, seamlessly reverting back to solar power as soon as it becomes available again. In addition to its dynamic energy management capabilities, the project incorporates an LCD screen to provide homeowners with real-time insights into their energy consumption patterns, offering a comprehensive overview of usage data from both energy sources. This invaluable information empowers users to make informed decisions about their energy usage habits, fostering a more conscious and efficient approach to power consumption. Furthermore, the integration of the Blynk 2.0 IoT platform elevates the project to new heights by enabling remote monitoring and control of the system. Through this intuitive interface, users can effortlessly manage their energy usage from anywhere using their smart phones or computers, ensuring maximum flexibility and convenience. Expanding beyond traditional energy management, the project delves into the realm of home automation with the incorporation of an additional ESP32 microcontroller. This feature-rich functionality empowers users to remotely control lighting fixtures, enhance safety measures with gas detection capabilities utilizing MQ2 sensors, and efficiently monitor water levels using ultrasonic sensors, all seamlessly integrated into the IoT eco system. This holistic solution not only prioritizes renewable energy sources and automates power source transitions but also leverages the transformative potential of IoT technology to create a sustainable and intelligent approach to energy management. Powered by ESP32 technology, this project serves as a trailblazer for the future of smart, efficient, and eco-friendly homes, setting a new standard for residential energy management and automation.

The Impact of Smartphones on the Academic Performance of University Students

Smartphones have become an important medium of connection and information. It is frequently used for social and academic purposes. This study examines the intricate relationship between smartphone usage patterns and academic performance among university students. Data was collected from 300 participants with the help of a Google survey form. Descriptive statistics, ANOVA (Analysis of Variance), factor analysis, and logistic regression were used for the analysis of data. The findings revealed that the majority of students spend 1-3 hours daily on their smartphones with social media emerging as the primary purpose for usage. Despite prevalent smart phone usages, students reported relatively high cumulative grade point averages (CGPAs), indicating positive academic achievement levels. However, the analysis also uncovered that smartphone usages, brings distractions while studying. Logistic regression analysis identified the significant predictors of CGPA, highlighting the importance of managing smartphone habits effectively. Multi-dimensional scaling (MDs) and factor analysis provided insights into the clustering of factors related to smartphone usage and academic performance. Overall, these findings underscore the need for targeted intervention to promote responsible smartphone usage habits and support academic success among university students.

Implementation of a Smart Teaching and Assessment System for High-Quality Cardiopulmonary Resuscitation.

The purpose of this study is to develop a smart training and assessment system called SmartCPR, for teaching and training cardiopulmonary resuscitation (CPR), based on human posture estimation techniques. In this system, trainees can automatically recognize and evaluate whether chest compressions during CPR meet the standard of high-quality CPR by simply using a device such as a smart phone. Through the system, trainees are able to obtain real-time feedback on the quality of compressions so that they can adjust the cycle, depth, frequency, and posture of compressions to meet the standard of high-quality CPR. In addition, the SmartCPR system is convenient for CPR trainers. Trainers can instantly and accurately assess whether the trainee's compressions meet the standard of high-quality CPR, which reduces the risk of manual assessment errors and also reduces the trainer's teaching pressures. Therefore, the SmartCPR system developed in this study can be an important tool for CPR teaching and training for physicians, which can provide training and guidance for high-quality CPR maneuvers and enable trainees to become more proficient in CPR and self-training.

Corporate learning in a disruptive digital era: a new global organizational paradigma (A case-study of IBM’s Your Learning Platform)

In a digital world when the technologies as well as the market places are evolving at an alarming pace, facilitating the employees to acquire newer knowledge and helping them advance their learning is most challenging than ever before. Staying agile and to become and remain ahead of competition in this swiftly changing business landscape is a daunting task indeed for companies. Corporate universities and Classrooms in B-schools have totally been overshadowed and got undermined by newer versions of learning and we are witnessing that the buffet of teaching employees is expanding and changing more than ever before. In addition to tracking down a plethora of in-person opportunities in the form of mentorships and training, employees are able to use their computers and smart phones to sift through facilely rich content online at any time and place. It may be in the form of online social media networks, published papers, as well as videos and courses. Nowadays, mobile and cloud technologies, and social networks are taken for granted by the tech-savvy modern employees. And not surprisingly, the millennials believe that technology makes them more effective and productive and hence always prefer to communicate through the electronic mode at workplace than face to face or for that matter even the telephone. They are found to be using technology only routinely. This Paper addresses the important challenge of shifting learning to the 21st Century platform economy faced by corporates and discusses how IBM has successfully tackled the same through its Your Learning Platform.