Wi-Fi Hotspots Research Articles

An Investigation of AI-Enabled Comprehensive Survey of Phishing Attacks detection techniques

Phishing is an online criminal activity which traps regular online customers to reveal their sensitive information into fake destinations by disguising themselves as original website. Because of the short life expectancy of phishing sites and the fast progression of phishing systems the current anti- phishing solutions are either unfit to manage the rising changes or in fit for assuming a successful part against this attack.Natural language handling and machine learning – these are the centre usage of the multi-stage approach proposed to identify phishing attacks and to perceive the substance/association that has been misused by the attackers to execute the phishing attacks. In this technique the primary stage is the revelation of named elements (names of areas, individuals and associations) and afterward the disclosure of concealed topics and for this the strategies that backings both phishing and non-phishing information therefore, Conditional Random Field (CRF) and Latent Dirichlet Allocation (LDA) is utilized. Next stage is the AdaBoost arrange where the named elements and the concealed subjects are dealt as features and the messages are ordered into phishing or non-phishing. proposed techniques are planned to alleviate the effect of phishing attack. The principal strategy proposes is to identify Wi-Fi phishing utilizing Association Rule mining. A Wi-Fi hotspot which associates such hand held gadgets has turned into a transitory archive of delicate data, in this way giving an open door for programmers to gather money related gain .Consequently data security arrangements tending to Wi-Fi hotspots (Wi-Fi phishing attack) has turned into the need of great importance. The conceivable approaches to attack the security of Wi-Fi hotspots and counter-attack methodologies have been tended to in this strategy. Key works: Phishing, LDA,AI

Indoor fingerprint localization algorithm based on WKNN and LightGBM-GA

Abstract WiFi-based indoor fingerprint localization is widely used in indoor localization owing to its high accuracy and low deployment costs. Changes in the indoor signal environment directly affect localization accuracy. To improve localization accuracy and stability, this paper proposes a novel indoor fingerprint localization algorithm based on Weighted K-Nearest Neighbors (WKNN) and an enhanced Light Gradient Boosting Machine (LightGBM). First, in the offline phase, Gaussian filtering and K-Nearest Neighbors-Random Forest information completion algorithm with fusion of Euclidean and Manhattan distances are used to remove outliers from the fingerprint database dataset and fill in missing fingerprint information, ensuring the integrity of the fingerprint database. During the online phase, the fingerprint database is divided into training and testing sets. The LightGBM algorithm is used for modeling. Additionally, Genetic Algorithm (GA) is use d to optimize the parameters of LightGBM algorithm to find the best parameters by fitness evaluation. Then, the nearest neighbor set found by the WKNN algorithm is introduced into the LightGBM-GA model. Combining the predictions from the standalone LightGBM algorithm and performing weighted fusion yields the final predicted coordinates. The experiments are conducted in 8 m × 10 m laboratory containing 5 access points and 80 reference points to collect the Received Signal Strength Indication values of 5 WiFi hotspots. The experimental results show that the average localization error of the proposed algorithm is 1.11 m, which is reduced by 6.7%–38.3% compared to K-Nearest Neighbors (KNN), Extreme Gradient Boosting (XGBoost), LightGBM, KNN + XGBoost, WKNN + LightGBM, and WKNN + XGBoost-GA localization algorithms. The localization curve is smoother, and the cumulative distribution function converges faster. Moreover, the localization time is reduced by 13.3%–36.7%, effectively enhancing localization accuracy and decreasing localization time.

Libraries Are Resilience Hubs

Problem, research strategy, and findings We explored the contributions of local public libraries to community resilience in the face of economic hardships, extreme weather events, and the COVID-19 pandemic using a survey of 415 library directors distributed through state library listservs in 13 Midwestern states, community-level census and presidential elections data, and library-specific data from the Institute of Museum and Library Services annual Public Libraries Survey. We found that public libraries provide invaluable resilience-boosting community services. They help patrons find jobs and access social services, often with one-on-one support. They act as daytime shelters during extreme heat and cold events, which is particularly important for unhoused and underhoused individuals. During the COVID-19 pandemic, they innovated to provide delocalized services and information access, such as installing WiFi hotspots. The provision of these essential resilience-boosting services is largely independent from library resources and community contexts and appear grounded in librarians’ ethos. Our research was limited to Midwestern public libraries and thus results are not generalizable to other regions, private, academic, and specialized libraries. We did not explore the possible relationships between local political majorities that could affect local government funding and priorities and local libraries’ funding sources, levels, and services. Takeaways for practice Beyond collections and information access, public libraries provide many services relevant to community and economic development and to disaster response. In addition, local public libraries act as resilience hubs in the face of economic stressors and extreme weather events, as well as during the COVID-19 pandemic, and are ready, flexible, adaptable, and willing to support patrons in times of need. Planners seeking to enhance community resilience can work with their local public libraries to build disaster preparedness and response capacity.

No Patient Left Behind: A Novel Paradigm to Fulfill Hepatitis C Virus Treatment for Rural Patients.

This study evaluates a novel multidisciplinary program providing expanded access to hepatitis C virus (HCV) treatment for rural Appalachian patients in South Carolina. This program identified patients via an opt-out emergency department screening program, and it aimed to achieve HCV cure by using community paramedics (CPs) to link and monitor patients from treatment initiation through 12-week sustained virologic response (SVR). Patients aged ≥18 years who were HCV RNA positive were eligible for enrollment if they failed to appear for a scheduled HCV appointment or reported barriers to accessing office-based treatment. CPs provided home visits (initial and 4, 12, and 24 weeks) using a mobile Wi-Fi hotspot to support telemedicine appointments (compliant with the Health Insurance Portability and Accountability Act) and perform focused physical assessments, venipuncture, and coordinated home delivery of medications. Statistics described participant characteristics, prevalence of SVR, and patient satisfaction results at 12 weeks posttreatment. Thirty-four patients were eligible for SVR laboratory tests by 31 August 2023; the majority were male (61.7%) and White (64.7%) with an average age of 56 years (SD, 11.7). Twenty-eight (82.4%) completed treatment and achieved 12-week SVR. Six (17.6%) were lost to follow-up. Two-thirds strongly agreed that they were satisfied with the overall care that they received, and half strongly agreed that their overall health had improved. This CP-augmented treatment program demonstrated success curing HCV for rural patients who lacked access to office-based treatment. Other health care systems may consider this novel delivery model to treat hard-to-reach individuals who are HCV positive.

A Tutorial on Cross-layer Optimization Wireless Network System Using TOPSIS Method

Wireless network system. Introduction: The availability and rising demand of ubiquitous connectivity has been one of the most revolutionary technological trends of the last ten years. Today, we anticipate being able can access these internet services at any time, from everywhere, for a variety of purposes, including checking email, using the phone, browsing the web, and a plethora of other uses, such as when travelling by car, subway, airline, or anywhere else. Although we still need to actively seek out connections today (by looking for a Wi-Fi hotspot nearby), the future will undoubtedly feature ubiquitous connectivity and Internet access. Central to this movement are wireless networks. A wireless network is any network that is not linked by cables and provides the user with the comfort and mobility they need. We may anticipate that dozens of various wireless technologies will be available to satisfy the demands, each with distinct performance requirements and each tailored for a particular task and environment, given the enormous variety of use cases and applications. Research signification: The densest wireless network deployments up until recently took place in campus-like settings, with the cell architecture being meticulously planned by professionals. The wireless environment is evolving quickly due to the increasing adoption of low-cost 802.11 equipment as well as other personal wireless devices (2.4 GHz cordless telephones, Bluetooth devices). There are two significant differences between dense installations of wireless networking hardware in locations like neighborhoods, shopping centers, and apartment buildings and campus-type deployments. First, numerous separate people or devices, each installing one or a small number of APs, result in complicated installations that are meticulously planned to enhance coverage and reduce cell overlap. The concentration of wireless sensor nodes and APs produced by this kind of haphazard, unplanned deployment is widely varied (and sometimes quite high). Methodology: Alternative: 1G, 2G, 3G, and 4G. Evaluation Preference: Multiplexing, Implementation, Services, Standards, Core Network. Results: from the result it is seen that Core Network is got the first rank where as is the Services is having the lowest rank. Conclusion: The value of the dataset for Wireless network system in TOPSIS method shows that it results in Core Network and top ranking.

An Investigation of AI-Enabled Comprehensive Survey of Phishing Attacks detection techniques

Phishing is an online criminal activity which traps regular online customers to reveal their sensitive information into fake destinations by disguising themselves as original website. Because of the short life expectancy of phishing sites and the fast progression of phishing systems the current anti- phishing solutions are either unfit to manage the rising changes or in fit for assuming a successful part against this attack.Natural language handling and machine learning – these are the centre usage of the multi-stage approach proposed to identify phishing attacks and to perceive the substance/association that has been misused by the attackers to execute the phishing attacks. In this technique the primary stage is the revelation of named elements (names of areas, individuals and associations) and afterward the disclosure of concealed topics and for this the strategies that backings both phishing and non-phishing information therefore, Conditional Random Field (CRF) and Latent Dirichlet Allocation (LDA) is utilized. Next stage is the AdaBoost arrange where the named elements and the concealed subjects are dealt as features and the messages are ordered into phishing or non-phishing. proposed techniques are planned to alleviate the effect of phishing attack. The principal strategy proposes is to identify Wi-Fi phishing utilizing Association Rule mining. A Wi-Fi hotspot which associates such hand held gadgets has turned into a transitory archive of delicate data, in this way giving an open door for programmers to gather money related gain .Consequently data security arrangements tending to Wi-Fi hotspots (Wi-Fi phishing attack) has turned into the need of great importance. The conceivable approaches to attack the security of Wi-Fi hotspots and counter-attack methodologies have been tended to in this strategy.

EMPOWERING CITIZENS THROUGH DIGITAL INDIA:AN OVERVIEW

Digital India is a campaign launched by the Government of India to ensure that the Government's services are made available to citizens electronically through improved online infrastructure and by increasing Internet connectivity or making the country digitally empowered in the field of technology. The initiative includes plans to connect rural areas with high-speed internet networks. It consists of three core components: the development of secure and stable digital infrastructure, delivering government services digitally, and universal digital literacy. Launched on 1 July 2015, by Indian Prime Minister Narendra Modi, it is both enabler and beneficiary of other key Government of India schemes, such as Bharat Net, Make in India, Startup India, Stand up India, industrial corridors, Bharat Mala and Sagar Mala. Digital India has 3 core components: - 1. Delivering Government Services Digitally 2. Universal Digital Literacy 3. Development of Secure and Stable Digital Infrastructure Digital technologies including mobile applications and cloud computing are considered as catalysts for rapid growth of a nation’s economy and empowering citizens across the globe. These technologies are used by us daily, from government offices to retail stores. They help us to share information on concerns or issues faced by us and connect us with each other. Technology giants from all over the world paid attention to the Digital India campaign and are readily and happily supporting the initiative. Even Mark Zuckerberg, the CEO of Facebook, had changed his profile picture to support Digital India. He started a trend on Facebook and promised to get the Wi-Fi Hotspots in rural India working. Google started on its commitment to providing broadband connectivity at 500 railway stations in India. Microsoft agreed on providing broadband connectivity to 5,00,000 villages in the country. Microsoft is also making India its cloud hub via the Indian data centres. Oracle planned on investing in 20 states to work on Smart City initiatives and Paymentech. A digitally connected India is aimed at the growth of the social and economic status of the masses in the country. The development of non-agricultural economic activities could pave the path for such an achievement, for providing access to financial services, health, and education. Information and Communication Technology alone cannot directly impact the overall development of a country. Basic digital infrastructure could help achieve overall development. Last but not the least, the paper also discusses the policies and initiatives of Digital India to empower the Citizens .

An analytical approach to network with IoT security using NodeMCU access point-prevention technique

This paper focuses on a very pertinent issue in the field of cybersecurity, particularly concerning the increased use of public Wi-Fi and the proliferation of IoT devices. The scenario, where an attacker captures user details through a malicious access point set up through a NodeMCU, is a practical illustration of a Man-in-the-Middle (MitM) attack. These attacks are especially concerning in the context of smart homes and smart cities, where security breaches can lead to severe privacy invasions and disruptions of essential services. The NodeMCU, being a low-cost, open-source IoT platform, is accessible for creating such malicious access points. It can be programmed to mimic legitimate Wi-Fi hotspots to intercept the data of unsuspecting users. This type of attack can enable unauthorized access to sensitive information such as login credentials, personal data, and even control over connected IoT devices. This approach is user-friendly and can significantly reduce the risk of users unknowingly connecting to malicious websites. The contribution of this paper includes a demonstration and analysis of a common network and IoT attack and a novel method for detecting fraudulent URLs, particularly those used in phishing attacks. By addressing these aspects, the paper makes a significant contribution to the field of cybersecurity and helps foster a more secure and resilient network and IoT ecosystem.

Sistem Pembatasan Jaringan Internet Wi-Fi berbasis Voucher menggunakan Perangkat MikroTik

The high mobility in this information technology era has led many people to use wireless (Wi-Fi) internet access media instead of wired media. Devices such as laptops, tablets, PCs, and gadgets are inseparable from wireless technology. This study aims to limit Wi-Fi users and improve the efficiency and performance of the hotspot network. This study implements a voucher system using MikroTik devices and AAA (Authentication, Authorization, and Accounting) functions. The research development method uses a waterfall model consisting of 5 stages: requirements analysis, topology design, system implementation, performance testing, and maintenance. Data collection techniques involve direct observation of hotspot users who use vouchers, recording data on voucher duration, the number of users, and usage time. The collected data is analyzed quantitatively to evaluate the efficiency and performance of the voucher system and to gain insights into user experiences. The research results show successful implementation with 1, 3, 5, 8, 15, and 20 users using vouchers for 30-, 60-, and 120 minutes during morning, afternoon, and evening testing periods. Based on the testing and data analysis, this voucher-based Wi-Fi user restriction system successfully improves the efficiency of the Wi-Fi hotspot network by reducing the risk of illegal access and data theft.

Decentralized fault tolerant source localization without sensor parameters in wireless sensor networks

In this paper, we study the source (event) localization problem in decentralized wireless sensor networks (WSNs) under faulty sensor nodes without knowledge of the sensor parameters. Source localization has many applications, such as localizing WiFi hotspots and mobile users. Some works in the literature localize the source by utilizing the knowledge or estimates of the fault probability of each sensor node or the region of influence of the source. However, this paper proposes two approaches: the hitting set and feature selection for estimating the source location without any knowledge of the sensor parameters under faulty sensor nodes in WSN. The proposed approaches provide better or comparable source localization performances. For the hitting set approach, we also derive a lower bound on the required number of samples. In addition, we extend the proposed methods for localizing multiple sources. Finally, we provide extensive simulations to illustrate the performances of the proposed methods against the centroid, maximum likelihood (ML), fault-tolerant ML (FTML), and subtract on negative add on positive (SNAP) estimators. The proposed approaches significantly outperform the centroid and maximum likelihood estimators for faulty sensor nodes while providing comparable or better performance to FTML or SNAP algorithm. In addition, we use real-world WiFi data set to localize the source in comparison to the support vector machine based estimator in the literature, where the proposed methods outperformed the estimator.

Fair Communications in UAV Networks for Rescue Applications

We study the deployment of a UAV network to provide urgent communications to people trapped in a disaster zone, where each UAV is an aerial base station in the air. Unlike most existing studies that assumed that each user communicates with a UAV directly, we introduce D2D communications, in which a user within the communication range of a UAV can serve as a hotspot (e.g., WiFi hotspot), and provide communication services to his nearby users who are out of the communication range of any UAV. More users thus can have the communication service provided by the UAV network. To ensure that the users within and out of the communication ranges of deployed UAVs have fair communication quality, we study a novel UAV deployment and resource allocation problem under the D2D communication model, which is to deploy K given UAVs in the top of a disaster zone, allocate the bandwidth of each UAV to its served users, allocate the bandwidth of each hotspot to his served users, determine the data rate of each user, and find the routing paths for data transmissions, such that the accumulative utility of all users is maximized. We also propose a novel ( 1-1/e-)-approximation algorithm algMaxUtility for the problem, where e is the base of the natural logarithm, and is a given constant with 0 < < 1-1/e. We finally evaluate the performance of the algorithm. Experimental results show that accumulative utility by the algorithm is up to 18% larger than those by existing algorithms. In addition, more than 16% users are served in the deployed UAV network by the proposed algorithm.

“It's one of the most important things we carry for us”: How mobile hotspots support people experiencing homelessness

Previous studies have examined the benefits and challenges of using mobile phones to support people experiencing homelessness. However, few studies have considered how mobile Wi-Fi hotspots support unhoused individuals and couples through public library lending programs. This paper seeks to address a gap in mobile communication scholarship by contributing insights from a qualitative study of library patrons who checked out mobile hotspots from the Boston Public Library in Massachusetts, USA. The findings show that although mobile hotspots provided many benefits for public library patrons in general, these devices facilitated mobile communication with a different sense of urgency for six people experiencing homelessness who also happened to be in romantic relationships. More concretely, the study found that mobile Wi-Fi hotspots reduced stress and anxiety for unhoused patrons because without the devices, patrons without fixed residences worried they could not be found; that hotspots kept unhoused patrons more connected, and therefore safer, in their tents despite the cold weather and a lack of electricity; and that unhoused patrons were concerned about their devices getting stolen because of their precarious situation. Although the unhoused patrons who participated in this study also shared their recommendations regarding how mobile hotspot lending programs in public libraries could be improved, they also mentioned that the benefits of hotspot availability far outweighed their challenges. The findings have implications for those working to address homelessness, including community-based organizations, government agencies, and policymakers who seek further insights into the positive role that mobile hotspot devices can play in supporting positive health outcomes for individuals and couples experiencing homelessness.

Camera-Based Short Physical Performance Battery and Timed Up and Go Assessment for Older Adults with Cancer.

This paper presents an automatic camera-based device to monitor and evaluate the gait speed, standing balance, and 5 Times Sit-Stand (5TSS) tests of the Short Physical Performance Battery (SPPB) and the Timed Up and Go (TUG) test. The proposed design measures and calculates the parameters of the SPPB tests automatically. The SPPB data can be used for physical performance assessment of older patients under cancer treatment. This stand-alone device has a Raspberry Pi (RPi) computer, three cameras, and two DC motors. The left and right cameras are used for gait speed tests. The center camera is used for standing balance, 5TSS, and TUG tests and for angle positioning of the camera platform toward the subject using DC motors by turning the camera left/right and tilting it up/down. The key algorithm for operating the proposed system is developed using Channel and Spatial Reliability Tracking in the cv2 module in Python. Graphical User Interfaces (GUIs) in the RPi are developed to run tests and adjust cameras, controlled remotely via smartphone and its Wi-Fi hotspot. We have tested the implemented camera setup prototype and extracted all SPPB and TUG parameters by conducting several experiments on a human subject population of 8 volunteers (male and female, light and dark complexions) in 69 test runs. The measured data and calculated outputs of the system consist of tests of gait speed (0.041 to 1.92 m/s with average accuracy of >95%), and standing balance, 5TSS, TUG, all with average time accuracy of >97%.

Sistem Monitoring dan Deteksi Dini Pencemaran Udara Berbasis Internet Of Things (IOT)

The problem of environmental pollution has been a concern for a long time and continues to be an important issue today. One form of pollution that is very detrimental is air pollution, which causes a decrease in air quality and disrupts its normal function. . The ISPU Scale usually consists of several categories that describe the level of air quality, such as the range 1-50 is said to be "Good", the range 51-100 is said to be "Moderate", the range 101-200 is said to be "Unhealthy", the range 201-300 is said to be "Very Unhealthy", and a range of 301+ is said to be "Dangerous". To monitor the level of air pollution, it is necessary to use a tool that can measure air quality accurately. Indoor pollution, as is often the case in office environments, is one of the most serious threats to the health of modern society. A worker can spend up to eight hours a day in the room. The air we breathe everyday comes from the building's air duct system. However, these duct systems not only circulate air, they can also spread contaminants from one room to another. Therefore, it is important to maintain indoor air quality for the comfort and health of workers, because this has a direct impact on their productivity. Based on this, an idea emerged to develop a prototype detector of carbon monoxide gas that is sensitive to indoor air pollution using a microcontroller and web-based. This research begins with analyzing and designing the system, both in terms of hardware and software. After that, the next step involves coding and programming configuration and setup on the Thingspeak web. The last stage is testing tools and systems to ensure that they operate according to the plan that has been set. This system is designed to be able to detect and monitor the level of air pollution, as well as provide a graphical display on Thingspeak. This tool works by using a microcontroller to read the MQ-135 sensor attached to the Ardino Wemos ESP8266. This sensor is used to measure gas levels in a predetermined room. The tool will connect to the Wi-Fi hotspot on the Android device to provide notifications via Thigspeak based on a graph

Personal exposure from free Wi-Fi hotspots in downtown Mexico City.

In 2019, the Government of Mexico City implemented actions that allowed citizens to approach a free Wi-Fi hotspot, where more than 13000 points have been installed throughout the city. In this work, we present the results of the measurements of personal exposure to Radiofrequency Electromagnetic Fields carried out in Plaza de la Constitución, better known as Zócalo located in the center of Mexico City. The measurements were taken by one of the researchers while walking on a weekday morning and afternoon, in different microenvironments (on the street, on public transport: subway, at the Zócalo, and finally, at home). We also carry out spot measurements in the center of the Zócalo. Subsequently, we carried out a comparative analysis of the different microenvironments, through box plot and violin plot, and we elaborate georeferenced and interpolated maps with intensity levels through the Kriging method, using the Geographic Information System. The Kriging interpolation gives us a good visualization of the spatial distribution of RF-EMF exposure in the study area, showing the highest and lowest intensity levels. The mean values recorded at the measured points in the Zócalo were 326 μW/m2 in the 2.4- to 2.5-GHz Wi-Fi band and 2370 μW/m2 in the 5.15- to 5.85-GHz Wi-Fi band. In the case of the mean values recorded on the street, they were 119 μW/m2 in the 2.4- to 2.5-GHz frequency band and 31.8 μW/m2 in the 5.15- to 5.85-GHz frequency band, like the values recorded at home, 122 μW/m2 and 33.9 μW/m2, respectively. All values are well below the reference levels established by the International Commission on Non-Ionizing Radiation Protection.

Blind-trust: Raising awareness of the dangers of using unsecured public Wi-Fi networks

The use of public wireless access points (APs) has likely increased with the rise of wireless devices such as smartphones, tablets, smartwatches, etc. These devices make it easy for people to access the internet while on the go, and public Wi-Fi hotspots can provide a convenient way to do so. Even though public Wi-Fi networks provide free access to the internet as opposed to mobile data plans or data roaming, the use of public Wi-Fi hotspots can also pose risks to the security and privacy of users. Public Wi-Fi hotspots are often unsecured, meaning that anyone on the same network can potentially see the data being transmitted. This paper serves two main goals — to determine the risk awareness among users of public Wi-Fi networks and whether they still decide to connect to these networks when they are made aware of the possible risks to their data. For this purpose, we set up an experimental free wireless AP across three different locations for a total of 10 non-consecutive days and found that people mostly connected to use social media apps and search engines. After conducting these experiments and gathering sufficient data, we informed the users about their leaked credentials, and private data and observed their risk awareness and behavioral changes after being exposed to these risks. We found out that our findings align with the protection motivation theory (PMT) and heuristic approach.

Sensing Mechanism and Real-Time Bridge Displacement Monitoring for a Laboratory Truss Bridge Using Hybrid Data Fusion

Remote and real-time displacement measurements are crucial for a successful bridge health monitoring program. Researchers have attempted to monitor the deformation of bridges using remote sensing techniques such as an accelerometer when a static reference frame is not available. However, errors accumulate throughout the double-integration process, significantly reducing the reliability and accuracy of the displacement measurements. To obtain accurate reference-free bridge displacement measurements, this paper aims to develop a real-time computing algorithm based on hybrid sensor data fusion and implement the algorithm via smart sensing technology. By combining the accelerometer and strain gauge measurements in real time, the proposed algorithm can overcome the limitations of the existing methods (such as integration errors, sensor drifts, and environmental disturbances) and provide real-time pseud-static and dynamic displacement measurements of bridges under loads. A wireless sensor, SmartRock, containing multiple sensing units (i.e., triaxial accelerometer and strain gauges) and a Micro Controlling Unit (MCU) were utilized for remote data acquisition and signal processing. A remote sensing system (with SmartRocks, an antenna, an industrial computer, a Wi-Fi hotspot, etc.) was deployed, and a laboratory truss bridge experiment was conducted to demonstrate the implementation of the algorithm. The results show that the proposed algorithm can estimate a bridge displacement with sufficient accuracy, and the remote system is capable of the real-time monitoring of bridge deformations compared to using only one type of sensor. This research represents a significant advancement in the field of bridge displacement monitoring, offering a reliable and reference-free approach for remote and real-time measurements.

Policy Patterns and The Application of Digital Literacy in Increasing Students' Religious Motivation

This article explains the implementation of digital school management through the Smart Classroom (SCR) program. This qualitative research approach uses descriptive analysis—data collection techniques through observation, documentation, and in-depth interviews. The study results show that a digital school is an educational institution with a learning process using digital equipment, books, and applications. Digital school management is establishing and implementing IT-based programs through the Smart Classroom program using software and hardware products. Second, Smart Classroom Learning at Al-Azhar 37 Islamic Middle School Pekanbaru uses an iPad. Educators create web-based, Google, and application-based learning materials. They were giving assignments/homework through tests and quizzes. Assessment of exam results through the Google form, students make important notes equipped with photo and video features that can be shared using the notes application as a collaboration with friends. This implementation has received support from the school by facilitating internet access via Wi-Fi hotspots within 24 hours. Third, the urgency of Smart Classrooms in educational institutions will make learning more effective, innovative, fun, comprehensive, and time efficient. The implications of this research are very beneficial for all elements of the school because it can facilitate the current student-centered learning process.

Manajemen Sekolah Digital Melalui Program Smart Classroom (SCR)

This article explains the implementation of digital school management through the Smart Classroom (SCR) program. This qualitative research approach uses descriptive analysis—data collection techniques through observation, documentation, and in-depth interviews. The study results show that a digital school is an educational institution with a learning process using digital equipment, books, and applications. Digital school management is establishing and implementing IT-based programs through the Smart Classroom program using software and hardware products. Second, Smart Classroom Learning at Al-Azhar 37 Islamic Middle School Pekanbaru uses an iPad. Educators create web-based, Google, and application-based learning materials. They were giving assignments/homework through tests and quizzes. Assessment of exam results through the Google form, students make important notes equipped with photo and video features that can be shared using the notes application as a collaboration with friends. This implementation has received support from the school by facilitating internet access via Wi-Fi hotspots within 24 hours. Third, the urgency of Smart Classrooms in educational institutions will make learning more effective, innovative, fun, comprehensive, and time efficient. The implications of this research are very beneficial for all elements of the school because it can facilitate the current student-centered learning process.

Service coverage optimization for facility location: considering line-of-sight coverage in continuous demand space

The reliable service coverage of many facilities or sensors used in smart city infrastructure is highly susceptible to obstructions in urban environments. Optimizing the line-of-sight (LOS) service coverage is essential to locating these facilities for smarter city services. Despite progression in the maximal coverage location problem (MCLP) model for locating facilities, maximizing the LOS service coverage in continuous demand space for facility location problems remains challenging. This study defined the LOS-constrained MCLPs (LOS-MCLPs) and proposed a service coverage optimization model to solve these LOS-MCLPs. We employed a computational geometry algorithm named the visibility polygon (VP) algorithm to simulate the LOS coverage in two-dimensional (2D) continuous demand space. We then coupled this algorithm with a robust heuristic algorithm to search for the optimal solutions to maximize effective LOS service coverage. An experiment applied the developed model to a Wi-Fi hotspot planning problem. The experimental results demonstrated that the proposed model can obtain optimal solutions for LOS-MCLPs according to the distribution of obstacles. Comparative results show that ignoring the LOS effect in the optimization of LOS-MCLPs might lead to large areas of service dead zones.