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.

Utilization of Waste Banks System in the COVID-19 Pandemic

People's perspectives and behaviors altered in a variety of ways during the pandemic period, most notably in areas related to health, environment, and most notably waste management. Many people still prefer to work from home and this in turn leads to a large accumulation of garbage without having any proper means of disposal. As a result, the garbage area will serve as a breeding ground for illness. Garbage is usually composed of a residual waste generated from a product or object that has outlived its useful life, but can still be recycled into a valuable item. On this basis, the solution is to use a waste bank;it is a collection point for sorted garbage. It is claimed that using a waste bank can help in preventing the garbage accumulation. The main purpose of this study is to determine the contribution of the waste bank to end garbage accumulation. The information gathered through a review of the literature and direct interviews with multiple informants. According to the findings of the literature review, waste banks can provide a variety of benefits to users, as well as the community and surrounding environment. The proposed research study's findings show that the changes in community activity patterns contribute to an increase in garbage, and that the community plays an important role in waste control. From the performed research study, it is evident that m any individuals are interested about garbage banks and their benefits based on this presumption. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Efficiency of Online Learning during Covid-19 Pandemic

COVID-19 pandemic has had a profound effect on campuses, compelling learning systems to shift away from face-to-face engagement and toward online instruction. The purpose of this research is to investigate the effectiveness of remote learning in the event of a COVID-19 pandemic. To obtain responses, a self-administered online survey was used. After data screening, 315 data were proceeded to the next analysis. Additionally, the data were devoid of missing cases and outliers. The measuring model was evaluated for indicator and internal consistency reliability, convergent and discriminant validity. Meanwhile, the structural model was evaluated by SmartPLS version 3.2.9 utilising the bootstrapping approach. Findings revealed self-discipline and flexibility were significant towards effectiveness of online learning among students at the UiTM Kelantan, Kota Bharu Campus. The findings argue that, in the modern era, internet technologies have increased the flexibility of post secondary education in a variety of ways. Institutions should make strategic use of these new flexibility, concentrating on chances to engage students more deeply in learning that results in practical outcomes. © 2023, World Scientific and Engineering Academy and Society. All rights reserved.

Prediction of Waste Disposal During Covid-19 Using System Dynamics Modeling

Sound and effective solid waste management practices are important to mitigate health risks and protect the surrounding environment. Proper Municipal Solid Waste (MSW) management practices are especially important during the COVID pandemic. Since the beginning of the COVID pandemic different waste disposal and recycling behaviors are observed in Regina, the capital city of Saskatchewan. It is believed the changes of waste disposal rate at Regina landfill is related to the new hygienic guidelines, more opportunities for work from home, distinct consumer behaviors, and COVID related regulations and recommendations. Waste generation and recycling behaviors are complex and multi-dimensional. The objective of this study is to model waste disposal rate at the City of Regina landfill using a System Dynamics (SD) model. The proposed SD model will help us better manage the City of Regina’s human resources during the pandemic and estimate the demand of additional personal protective equipment required for the waste management workers. In the present work, a total of 7.5 years of waste disposal data is collected, consolidated, and verified. Socio-economical parameters such as GDPs and population at Regina were also collected during the study period from 2013 to 2020. The model is built using stock-flow diagram to illustrate the effects of various inter-related variables on the waste generation behaviors. Construction and demolition (C&D), Grit, Asphalt Shingles Only, Asphalt Shingles Mixed and Treated Biomedical wastes data are used in the SD model. Results show that waste generation has affected by the pandemic and there is a general increase in amount of waste generation. The modeling results are important because it helps us predict the amount of MSW during and after the pandemic. © 2023, Canadian Society for Civil Engineering.

Efficiency of Online Learning during Covid-19 Pandemic

COVID-19 pandemic has had a profound effect on campuses, compelling learning systems to shift away from face-to-face engagement and toward online instruction. The purpose of this research is to investigate the effectiveness of remote learning in the event of a COVID-19 pandemic. To obtain responses, a self-administered online survey was used. After data screening, 315 data were proceeded to the next analysis. Additionally, the data were devoid of missing cases and outliers. The measuring model was evaluated for indicator and internal consistency reliability, convergent and discriminant validity. Meanwhile, the structural model was evaluated by SmartPLS version 3.2.9 utilising the bootstrapping approach. Findings revealed self-discipline and flexibility were significant towards effectiveness of online learning among students at the UiTM Kelantan, Kota Bharu Campus. The findings argue that, in the modern era, internet technologies have increased the flexibility of post secondary education in a variety of ways. Institutions should make strategic use of these new flexibility, concentrating on chances to engage students more deeply in learning that results in practical outcomes. © 2023, World Scientific and Engineering Academy and Society. All rights reserved.

Adaptive Distance Sensing in Contact Tracing Applications Through Indoor/Outdoor Detection

Physical distancing is one of the most effective measures for limiting the spreading of the COVID-19 disease. Smartphones, being carried by their owners most of the time, are particularly appealing for increasing the awareness of people about their closeness to other individuals. Sensing the distance using communications technologies like Bluetooth is known to be affected by the surrounding environment. In this paper, we study the benefits that can be achieved by automatically recognizing if the user is indoor or outdoor and then defining a customized threshold for improving the accuracy of social distancing applications. © 2022, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

An Accurate Point Cloud-Based Human Identification Using Micro-Size LiDAR

The demand for safety-boosting systems is increasing, especially nowadays, to limit the rapid spread of COVID-19. Real-time life-logging is an essential application towards tracking infected cases and thus containing the pandemic outbreak. This application raises the need for an accurate human identification technology where cameras cannot be adopted due to privacy. Recently, LiDAR sensor has attracted attention due to its ability to represent the surrounding environment in the form of 3D point cloud. In this paper, we introduce a novel wearable device of a micro-size LiDAR to build an onboard human identification system for life-logging. The system acquires 3D point cloud data of the surrounding environment from which subject-discriminative signatures are extracted. This is achieved by removing noise and background using Spatio-temporal density clustering and fisher vector representations. The extracted features are then used to train a random forest classifier for subject identification. We have implemented and evaluated the proposed system on six different subjects. The results show that the proposed system can effectively remove noise and background and accurately identify subjects with 99.9% accuracy. © 2022 IEEE.

The Role of Big Data and Smart Technologies in Autonomous Vehicles

This paper presents a definition of what Autonomous Vehicle and their functions are, how they operate, gather data and what threats they have to encounter-with throughout their operations. As explained later in the article, we can observe that there are a handful of ways by which a self-driving vehicle can gather information about it's surrounding environment beside the sensors it is equipped with. These methods of gathering data are thoroughly explained in the article alongside their advantages and disadvantages. This article also tries to have a look at the methods an AV can overcome the computing challenges it is facing while guiding and controlling the vehicle, as well as staying in communication with other vehicles or any object that can provide useful information to the vehicle. © 2021 ACM.

IoT-Based Autonomous Baby Monitoring System Using Mobile App Control

In this modern world, almost 80% of parents have to work in order to balance their financial demands. The probability of providing better childcare, especially for babies is reducing. Although hiring a guardian or sending babies to daycare centers can temporarily solve the issue, it does not reduce the anxiety and stress of the parents due to more and more child abuses being reported every year. During this Covid19 pandemic, the need for an alternative better solution is urgent when some parents are forced to undergo quarantine for at least a few weeks. In this paper, we propose to develop a long-ranged baby monitoring and controlling system. The system consists of hardware architecture that is inter-connected with an IoT network to monitor the real-time condition of the baby such as crying, awakening and cleanliness, and its surrounding environment such as temperature, humidity and motion. In the proposal, the overall system operation involves four different phases: data collection, information sharing and processing, output display and notification, and user control. At the end of the project, a prototype has been successfully constructed to collect the monitoring data, and then share and display them to the users accurately via mobile app. In addition, users can also remotely perform basic control over any components or devices that are connected to the system. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Anonymously tracking covid-19 patient using labeling graph approach and GPS tracking technology

The increasing number of patient infected by Covid-19 viruses in Indonesia, causing each personal to be more vigilant in doing activities outside. Many patients who are positively exposed to the corona viruses are self isolating in their own house because the hospital is full. Patiens who have recovered and tested negative from the corona viruses can work outside the house. The purpose of this study is to provide information regarding patients infected with Covid-19 in certain area through a tracing application. This apllication can help public to find out how many individuals are infected with Covid-19 in the surrounding environment by priorizing patient privacy and in real time anonymously. The method used is a combination of labelling graph theory and the GPS tracing system applied to the gadget. The programming language use in this gadget cases is flutter. The stages that will be carried out are starting from tracing patients infected with Covid-19 based on the position of tracing area, then predicted through a graph model approach based on distance and percentage of transmission. The result of this research is the percentage of prediction about personal vulnerability. The initiation of prediction divide into saveral categories, including vulnerable, moderate, or safe. © 2022 Institute of Physics Publishing. All rights reserved.