Abstract - Women's safety remains of paramount importance against the backdrop of rising incidents of harassment and violence. An attempt has been made to develop an IoT-Based Safety and Tracking System for Women, comprising a wearable smart device that is capable of detecting distress and sending emergency alerts automatically. It comprises sensors, namely heartbeat, inclinometer, microphone, and biometric modules, that detect abnormalities in physiological or movement patterns indicating threat situations. GPS and GSM/Wi-Fi modules enable location tracking in real time and wirelessly send alerts to emergency contacts or authorities instantly. A panic button, buzzer, and shock mechanism provide instant self-defense and draw public attention. Machine learning–based anomaly detection ensures that the proposed system achieves higher accuracy in recognizing threats. The device is small in size and power-efficient, intended for everyday wearable use, thus ensuring speedy assistance even when one is in a situation whereby manual handling of the mobile phone is not possible. This type of wearable device provides an active, trustworthy, and hands-free safety solution by empowering women and quickening the pace of emergency response. Key Words: IoT, Women Safety, Smart Wearable Device, GPS Tracking, GSM Module, Emergency Alert System, Machine Learning, Sensors, Distress Detection, Real-Time Monitoring.

Introduction: Informational Autocracy and the Moral Panic Button – Using Migration Discourse as Manipulation at Master Level

This study determined the extent to which ICT integration in school security management predicts principals’ job performance in private secondary schools in Akwa Ibom State, Nigeria. However, from the literature reviewed so far it was observed that the relationship between ICT integration in school security management and principals' job performance has not satisfactorily given adequate attention in the context of Closed Circuit Television (CCTV), entry metal detectors, social net watchers, panic buttons and school bus tracking system in private secondary schools in Akwa Ibom State, Nigeria. This study aimed to bridge this gap by examining the relationship between these variables. A correlational research design was adopted while the population consists of all 476 principals of the private secondary schools in Akwa Ibom State. Krejcie and Morgan Table was used to determine the sample size of 214, while purposive sampling was used to sample only schools that have the ICT facilities under study. Two research instruments were used to elicit data for the study. Regression analysis was used to answer research questions and to test all the null hypotheses at 0.05 level of significance. Findings of the study show that integration of Closed-Circuit Television (CCTV), entry metal detectors, social net watcher and panic buttons had low positive but no significant predictive influence on principals' job performance in private secondary schools in Akwa Ibom State. The result also indicated that integration of school bus tracking have moderate positive and significant predictive influence on principals' job performance in private secondary schools in Akwa Ibom State. Based on the findings, it was concluded that limited ICT security integration in private secondary schools in Akwa Ibom state represents a significant vulnerability, increasing risk to students and staff. Therefore, urgent prioritization of ICT integration is crucial. It was recommended among others, that private school administrators in collaboration with parents should invest in ICT tools in order to ward off potential threats, and that public schools in collaboration with the government should adopt and invest in ICT as a matter of urgency.

This paper is an account of the design and implementation of a versatile assistive robotic system, which is to be used to assist the elderly and the disabled in their daily activities. The most notable features are a mobility assistant and item transportation tracking mechanism based on Bluetooth, an emergency alert functionality activated by a panic button on the mobile device, and a medication reminder functionality that sends scheduled alerts and sends SMS notifications in case of abandonment. Due to its user-friendly and flexible interface, the robot will be able to address the needs of every user, promote independent living, enhance safety, and reduce the dependency of people on caregivers. The proposed solution improves the overall quality of life of the users and provides them with a respectable lifestyle.

This study is driven by the need to enhance the effectiveness of public communication between the police and the community. The Semarang City Police (Polrestabes Semarang) developed the LIBAS application (Polisi Hebat Semarang) as a service innovation aimed at improving the speed of access to information, reporting, and police response. The research employs a qualitative descriptive approach, with data collected through observation, in-depth interviews, and documentation. The study was conducted from January to February 2025, and data were analyzed using techniques of data reduction, presentation, and conclusion drawing. The findings indicate that LIBAS functions effectively as a medium for public communication. Features such as the 001 service, SOS, incident reporting, and the panic button facilitate rapid public access to police services. The impact of LIBAS is evident in three domains: cognitive (increased public understanding of police services), affective (enhanced sense of safety and trust in the police), and behavioral (greater public initiative in reporting incidents). The data show a total of 4,233 reports: 2,466 incident reports, 1,674 reports via SOS, and 93 complaints via the panic button. Overall, the findings demonstrate that LIBAS improves public communication effectiveness and contributes to a positive image of the police. Nevertheless, the application requires further development through broader socialization and ongoing evaluation to ensure sustained service effectiveness.

Background: Workplace violence against nurses is a critical global public health and occupational hazard. Ranging from verbal abuse to physical assault, the consequences of WPV are severe physical and psychological injuries, burnout, high staff turnover, and diminished quality of care for patients. High-risk areas include emergency and psychiatric units. Aim: This review aims to synthesise literature from 2015 to 2025 and establish the effectiveness of various security measures instituted in clinical environments with the aim of protecting nurses and patients from violence. Methods: A systematic search of PubMed, CINAHL, PsycINFO, and Scopus was conducted for peer-reviewed studies from 2015 to 2024 using keywords related to the topic, including "workplace violence," "nurses," "intervention," and "security measures." A total of 40 qualifying quantitative, qualitative, and mixed-methods studies were included and analyzed using the method of narrative synthesis. Results: Interventions were categorized as primary (prevention), secondary (response), and tertiary (post-event) strategies. The most effective primary measures included comprehensive violence prevention programs, de-escalation training, and environmental designs, such as panic buttons. Secondary measures, including emergency response teams, were effective when deployed promptly. Tertiary support, such as debriefing and counseling, was crucial for mitigating long-term effects. Major implementation barriers included inconsistent training, underreporting, and cultural acceptance of violence. Conclusions: What works is an integrated, multicomponent strategy that incorporates proactive, responsive, and supportive interventions. From the leadership perspective, a safety culture should be developed that emphasizes prevention, reporting, and support of staff. Recommendations for future research include standardization of outcomes, longitudinal analysis, and consideration of predictive technologies such as AI.

Abstract -. Time, safety, and navigation are critical challenges for visually impaired individuals, yet many assistive tools remain limited in capability, accuracy, or affordability. The objective of this project is to design and develop a Smart Cane Assistive System that enhances mobility, ensures safety, and provides real-time environmental awareness through a combination of sensor-based obstacle detection, computer vision, and emergency communication technologies. The system incorporates an IR sensor for short-range ground obstacle detection and an ultrasonic sensor for mid- and upper- level obstacle identification, both interfaced with an Arduino Uno that alerts the user through a buzzer. An ESP32-CAM module enables object identification and OCR, activated via dedicated switches, with results processed through a Python application and provided as audio feedback. An RFID reader supports automatic bus route identification without user input. For emergency situations, a second Arduino Uno is paired with a SIM800L GSM and NEO-6M GPS module, powered by a 3.7V Li-ion battery, to send an SMS containing the user’s live location when the panic button is pressed. The system follows a modular design covering core functions such as sensing, vision processing, RFID-based alerts, and emergency communication. Multi-level testing validated the system’s accuracy, performance, and user comfort. The results indicate that the smart cane significantly improves obstacle detection accuracy, enhances situational awareness, and provides reliable emergency communication support compared to conventional assistive devices. Future developments may include AI-based path prediction, Bluetooth connectivity for mobile integration, and onboard audio processing for fully offline operation Keywords:. Smart Cane, Assistive Technology, Obstacle Detection, Object Recognition, OCR, RFID Navigation, Emergency Alert System.

In recent decades, various assistive technologies have emerged to support visually impaired individuals. However, there remains a gap in terms of solutions that provide efficient, universal, and real-time capabilities by combining robust object detection, robust communication, continuous data processing, and emergency signaling in dynamic environments. In many existing systems, trade-offs are made in range, latency, or reliability when applied in changing outdoor or indoor scenarios. In this study, we propose a comprehensive framework specifically tailored for visually impaired people, integrating computer vision, edge computing, and a dual-channel communication architecture including low-power wide-area network (LPWAN) technology. The system utilizes the YOLOv5 deep-learning model for the real-time detection of obstacles, paths, and assistive tools (such as the white cane) with high performance: precision 0.988, recall 0.969, and mAP 0.985. Implementation of edge-computing devices is introduced to offload computational load from central servers, enabling fast local processing and decision-making. The communications subsystem uses Wi-Fi as the primary link, while a LoRaWAN channel acts as a fail-safe emergency alert network. An IoT-based panic button is incorporated to transmit immediate location-tagged alerts, enabling rapid response by authorities or caregivers. The experimental results demonstrate the system’s low latency and reliable operations under varied real-world conditions, indicating significant potential to improve independent mobility and quality of life for visually impaired people. The proposed solution offers cost-effective and scalable architecture suitable for deployment in complex and challenging environments where real-time assistance is essential.

The (Un)Changing Language and Sentiment Associated with the Moral Panic Button (MPB) in the Wake of the Russian–Ukrainian War: The Hungarian Case

As incidents of gendered violence and child abuse increase, there is a need for intelligent, real-time safety systems that autonomously detect distress and initiate emergency action without user activation. Q-SAFE (Quantum AI for Real-Time Women & Child Safety) is an open-source, multi-modal mobile app, utilizing quantum-enhanced machine learning models to detect panic situations based on audio cues (spoken and non-spoken) and motion. The system automatically generates an emergency broadcast that shares live location, messages alerts, and takes videos (in secure cloud storage) in the following ways: automatically detects predetermined distress words using existing Quantum /Indeterminate Natural Language Processing (NLP) classifiers, their corresponding visual module pending; and via accelerometer-based gesture recognition. Most importantly, due to employment of post-quantum cryptographic protocols, the emergency broadcasts use secure communication that does not depend on the users activating any manual processes. Q-SAFE departs from self-activated panic button approaches used in the past noting that fully autonomous systems that require no user activation have been absent for decades. Q-SAFE was developed using scalable technologies, while also conducting tests using multiple scenarios for future robustness, and emerges as an intelligent and privacy-respecting sentinel and caretaker for those that are most vulnerable.

Hungary as an Ideological Informational Autocracy (IA) and the Moral Panic Button (MPB) as its Basic Institution

WSafe is an innovative Android-based personal safety application specifically designed to address the critical need for women's security in today's society. This comprehensive mobile solution leverages modern smartphone capabilities to provide immediate assistance during emergency situations through a multi-faceted approach to personal safety. The application integrates advanced features including motion-based emergency triggers through shake detection, real-time GPS location tracking, automated SOS messaging, and an emergency siren system. What distinguishes WSafe is its holistic approach to women's safety, combining immediate emergency response features with preventive measures such as access to self-defense tutorials, legal resources regarding women's rights, and a curated directory of national helplines. The application's architecture is built on Java using Android Studio, ensuring robust performance and reliability across Android devicesBy incorporating both active security measures and educational resources, WSafe not only provides immediate assistance during emergencies but also empowers users with knowledge and tools for long-term safety awareness. The implementation of location-based services enables users to quickly locate nearby police stations and hospitals, while the panic button feature ensures one-touch access to emergency contacts. This project represents a significant step forward in leveraging mobile technology to create a more secure environment for women, offering both immediate emergency response capabilities and tools for long-term safety empowerment.

Introduction. The article explores the prospects of implementing the “Judge Under Protection” hardware-digital platform to ensure the personal safety of judges. It describes the platform’s concept, which includes a mobile application with a panic button that performs route monitoring, integrates with law enforcement databases, warns of potential risks of encountering threatening individuals, and, if necessary, records evidence. Results. Special attention is given to the application of artificial intelligence (AI) through “smart glasses”, “smart watches” and other gadgets for rapid response and evacuation, as well as the role of criminology and profiling in the preventive identification of threats. Discussion and Conclusion. Based on advanced experience, measures are proposed to enhance the security functions of judicial enforcement officers (bailiffs), contributing to judicial independence and strengthening trust in the justice system.

Village Guidance Non-Commissioned Officers (Babinsa) serve as the spearhead of the Indonesian Army (TNI AD) in fostering good relations between the TNI and the local community. The Babinsa's primary duty is to help maintain security and order within the community, as well as to develop village potential through development programs organized by the government and the TNI. Based on this duty, the Babinsa's rapid response in completing its main task is to conduct early detection by responding quickly and responsively to any problems that arise. This requires the Babinsa to be able to utilize internet-based science and technology for various purposes in the village, such as increasing communication and information efficiency, and supporting village development. For example, the use of instant messaging applications for coordination with residents, village websites for information transparency, and digital applications for village administration management. In addition, Babinsa can also use the internet to provide education and training to the community, as well as monitor potential threats in their assigned areas. The use of internet-based technology (IoT) namely Instant Messaging Applications (WhatsApp), Village Websites (SISKEUDES, Panic Button Applications), Social Media, CCTV can be used by Babinsa to support their monitoring and evaluation duties in their assigned villages.

BackgroundNumerous reviews have explored specific aspects of violence prevention apps, but given the rapid development of new apps, increased violence during COVID-19, and gaps in understanding functionalities and geographical distribution, an updated review is needed.ObjectiveTherefore, we aimed to systematically evaluate the trends, geographical distribution, functional categories, available features, and feature evolution of mobile apps designed to prevent violence against women and girls (VAWG).MethodsWe conducted a systematic search on app reselling platforms and search engines from April 24, 2024 to May 28, 2024, using terms related to VAWG in multiple languages. We included apps meeting our criteria for addressing VAWG, without restrictions on date or language. We conducted content analysis of app and apps were categorized by functionality and feature type. We performed descriptive analyses, trend analysis, co-occurrence network analysis, and geographical mapping.ResultsOut of 432 apps initially identified, 178 were included in the final analysis. Of these, 99 apps were available on both Google Play and the App Store, and 64 were exclusive to Google Play. Most apps were implemented in North America (48/178, 27%), followed by South Asia (31/178, 17%) and Europe and Central Asia (31/178, 17%). Emergency and support apps were most prevalent across regions. Most apps (132/178, 74%) originated from the private sector and were designed for survivor (121/178, 68%), were free without in-app purchases (100/178, 56%), had a website (148/178, 83%), and offered GPS features (142/178, 80%), but only 15% (27/178) provided offline functionality. App releases peaked in 2020 (33/178, 19%), followed by a decline. Regression analysis indicated a significant trend (P=.01) increase in app release, with a 2.40 unit increase per year before 2020 and a 7.01 unit decrease after, showing a post-2020 decline of 4.61 units per year. Apps were primarily categorized as emergency (n=110) or support (n=81), with most emergency apps in the 10,000 to ≥100,000 downloads range. Network analysis showed that emergency services (degree=10, clustering coefficient=0.911), location sharing (degree=10, clustering coefficient=0.911), SOS (Save Our Souls) alerts (degree=10, clustering coefficient=0.911), and educational resources (degree=10, clustering coefficient=0.911) features highly co-occurred in the same app. We found a gradual shift towards more sophisticated and comprehensive safety tools, evolving from basic GPS tracking and SOS alerts to advanced features such as real-time communication, panic buttons, peer support, and group communication, culminating in multifunctional platforms offering personalized safety, community engagement, and proactive risk identification.ConclusionsMost apps to prevent VAWG emphasize emergency and support functions, and although initial releases increased, there has been a recent decline, with a shift towards integrating more comprehensive safety solutions such as communication, reporting, and community engagement. Future app development should prioritize cross-platform availability, offline functionality, public sector collaboration, and the integration of advanced technologies like artificial intelligence.

Abstract -The safety of women, especially during nighttime, has become an increasingly pressing concern in modern society. Incidents of harassment and violence often occur in isolated or poorly monitored areas where timely human intervention may not be possible. Traditional surveillance systems, such as CCTV cameras or manual patrolling by security personnel, have limitations in terms of real-time responsiveness and operational consistency. To address these limitations, this project proposes the development of a women safety night patrolling robot powered by Raspberry Pi. The robot is capable of autonomous movement and real-time monitoring using PIR (Passive Infrared) sensors to detect human presence and ultrasonic sensors to avoid obstacles. The core innovation lies in its autonomous patrolling capability, where the robot navigates predefined or dynamically adjustable paths without human guidance. Additionally, the system is equipped with a panic button that, when pressed, sends an emergency SMS containing the GPS location of the robot to pre-configured emergency contacts via a GSM module. A loud alarm is simultaneously triggered to alert nearby individuals and deter potential threats. This multi- functional robot acts as a mobile surveillance unit and an immediate alert system, offering a proactive technological solution to enhance the safety of women in vulnerable locations.

Abstract— Women's safety is a pressing global issue, with increasing incidents of harassment and violence. Traditional safety tools, like personal alarms or manual panic buttons, often rely on user activation, which can be impractical in critical moments. This project seeks to overcome these challenges by creating an IoT-enabled wearable safety device that autonomously detects distress signals through screams, captures video evidence, and sends real-time alerts, including the user's location, to emergency contacts or local authorities. The device employs machine learning algorithms to differentiate between genuine distress sounds and background noise, ensuring accurate detection and reducing false alarms. Additional features include GPS tracking, automatic activation, and a user-friendly design, making the device practical and efficient in real-life situations. Data security and power management are key components of the system, with encryption safeguarding personal information and power-efficient components ensuring long-term functionality. This solution aims to improve women's safety by providing an intelligent, hands-free personal security option. By combining advanced IoT technologies with real-time communication capabilities, this project offers a robust, reliable, and proactive method to prevent harm, empower women, and enhance safety in public environments.

Women's safety is a pressing global issue, with increasing incidents of harassment and violence. Traditional safety tools, like personal alarms or manual panic buttons, often rely on user activation, which can be impractical in critical moments. This project seeks to overcome these challenges by creating an IoT-enabled wearable safety device that autonomously detects distress signals through screams, captures video evidence, and sends real-time alerts, including the user's location, to emergency contacts or local authorities. The device employs machine learning algorithms to differentiate between genuine distress sounds and background noise, ensuring accurate detection and reducing false alarms. Additional features include GPS tracking, automatic activation, and a user-friendly design, making the device practical and efficient in real-life situations. Data security and power management are key components of the system, with encryption safeguarding personal information and power-efficient components ensuring long-term functionality. This solution aims to improve women's safety by providing an intelligent, hands-free personal security option. By combining advanced IoT technologies with real-time communication capabilities, this project offers a robust, reliable, and proactive method to prevent harm, empower women, and enhance safety in public environments.

This article aims to reflect on the performance of the Military Police of Paraná in confronting domestic violence and femicide, highlighting actions such as the Maria da Penha Patrol, the 190PR Application – Panic Button and the PMPR Security Plan for victims of domestic violence. Based on the author's practical experience as a military police officer for almost a decade, with a postgraduate degree in Public Security and Criminal Analysis, and based on the successful methodology of the Educational Program for Resistance to Drugs and Violence (PROERD), it is proposed to create an educational program aimed at the prevention of domestic violence, focusing on the promotion of gender equality and strengthening family and community bonds. The interdisciplinary approach proposes an integration between public security, education and civil society, aiming at citizen education and the reduction of gender violence rates in the State of Paraná. The article uses qualitative and bibliographic methodology, based on legislation, doctrine and statistical data.

Visually impaired individuals face significant challenges in navigating their surroundings safely and independently. Traditional mobility aids such as canes provide limited assistance and lack real-time hazard detection. This paper presents a Smart Assistive Device for the Visually Impaired using IoT, designed to enhance mobility, safety, and emergency response. The system integrates two ultrasonic sensors—one for depth detection and another for obstacle avoidance—providing immediate feedback through a vibrating motor. A rain sensor detects moisture levels, warning users of wet surfaces. The device also includes a GPS module for real-time location tracking and a GSM module to send emergency SMS alerts. A panic button allows users to instantly send their location to predefined contacts in distress situations. The system is built around an Arduino Nano, ensuring efficient processing and communication. This assistive technology enhances the independence of visually impaired individuals by offering real-time alerts and automated emergency assistance. Future improvements may include AI-based object recognition, voice assistance, and machine learning algorithms for adaptive navigation. This innovation contributes to improving accessibility, safety, and overall quality of life for visually impaired users. KEYWORDS- Smart Assistive Device, Visually Impaired, IoT, Ultrasonic Sensors, GPS, GSM, Panic Button, Rain Sensor, Vibrating Feedback.