Public Safety Systems Research Articles

YOLO-ABD: A Multi-Scale Detection Model for Pedestrian Anomaly Behavior Detection

Public safety and intelligent surveillance systems rely on anomaly detection for effective monitoring. In real-world pedestrian detection scenarios, Pedestrians often exhibit various symmetrical features such as body contours, facial features, posture, and clothing. However, the accuracy of pedestrian anomaly detection is affected by factors such as complex backgrounds, pedestrian obstruction, and small target sizes. To address these issues, this study introduced YOLO-ABD, a lightweight method for anomaly behavior detection that integrated small object detection and channel shuffling. This approach enhanced the YOLOv8n baseline model by integrating a small-object detection mechanism at the head and employing the symmetric GSConv convolutional module in the backbone network to improve perceptual capabilities. Furthermore, it incorporated the SimAM attention mechanism to mitigate complex background interference and thus enhance target detection performance. Evaluation on the IITB-Corridor dataset showed mAP50 and mAP50-95 scores of 89.3% and 60.6%, respectively. Generalization testing on the street-view-gdogo dataset further underscored the superiority of YOLO-ABD over advanced detection algorithms, demonstrating its effectiveness and generalization capabilities. With relatively fewer parameters, YOLO-ABD provided an excellent lightweight solution for pedestrian anomaly detection.

Bias‐adjusted and downscaled humidex projections for heat preparedness and adaptation in Canada

AbstractTo help with preparedness efforts of Canadian public health and safety systems for adaptation to climate change, the humidity index (humidex) and three threshold‐based humidex indices (annual number of days with humidex greater than 30, 35 and 40) were computed for a multi‐model ensemble of climate change projections, over Canada. The ensemble consists of one run from each 19 Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models and offers historical simulations starting in 1950 and future projections out to 2100 following Shared Socioeconomic Pathways (SSPs): SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5. Each ensemble member was bias‐adjusted and statistically downscaled using the Multivariate bias correction—N‐dimensional probability density function transform (MBCn) with hourly data from ERA5‐Land as the target dataset and following a method proposed by Diaconescu et al. (2023; International Journal of Climatology, 43, 837) to calculate humidex from daily climate model outputs. This paper details the steps for data production including evaluation of the target historical gridded data and selection of downscaling method and presents some of the resulting humidex projections at the end of the century.

The impacts of governing agency: A comparison of resources in the patchwork of medicolegal death investigation systems

In the United States, medical examiners and coroners (MECs) fill critical roles within our public health and public safety systems. These professionals are primarily charged with determining the cause and manner of death as they investigate deaths and respond to associated scenes and mass fatalities and can also help identify trends in public health crises through medicolegal death investigations. Despite their instrumental role, they are organized in disparate systems with varying governing structures, functions, staffing, caseload, budget, and access to resources. This paper examines data from the 2018 Census of Medical Examiner and Coroners to evaluate MEC operations in the United States. The findings show that MEC offices’ organizational and operational governance structures greatly influence resources, workloads, and access to information and services. Standalone MEC offices were generally better resourced than those affiliated with law enforcement, public health, forensic science, district attorneys, or other agencies.1

HUMAN RESOURCES MANAGEMENT IN THE MUNICIPAL GUARD

Nowadays, local government employees have become a key capital of public organisations and a factor in their success. In the modern conditions of the economy, determined by the variability of regulations, the environment, and the development of knowledge and technology, local government institutions can achieve their goals thanks to appropriate management of human resources. In this case, the management of Municipal and City Guards, which are an important element in the public safety system, is of particular importance. The author attempts to answer the question whether in the case of Municipal and City Guards, assumptions related to the concept of human resources management are identified. The reason for taking up this issue is also the fact that acquiring em-ployees with specific competencies in the case of Municipal and City Guards is currently one of the main challenges of the management staff of these organisations.

Our public safety system is a perfect storm.

Public safety results from an effective interaction of three separate systems - public health, mental health, and policing. In too many communities today, the crisis in our mental health system creates the perfect storm. Solving the issues of silo-based care necessitates creating an oversight data management structure supporting cross-sector data integration on all levels ensuring that both operational and technical frameworks exist to maintain the security of client data. Safer communities isn't just about being sophisticated, technologically advanced but using an intensifying laser-focus analysis on harmful criminality, and on stakeholders responsible for delivering to those in need of mental health services. The recommendations note that no one agency can solve the crisis in public safety alone. There is an urgent need for one new coordinating agency - a department in government - to eliminate the silos and act like a well-coordinated and effective service delivery network, with public commitment to outcomes and corresponding public accountability.

China after COVID-19

Background:
 The COVID-19 pandemic has seriously affected global public health security and economic development, and is a huge test for China and other countries around the world. Among the factors affecting the outbreak of the epidemic, human abuse of wildlife appears to be the most important. Under the influence of relevant factors, China has formulated and implemented policies, laws and regulations on a comprehensive ban on wildlife.
 Objectives:
 Through the integration and impact analysis of China's comprehensive wildlife fasting policy and relevant laws and regulations, this paper aims to provide reference for other countries in epidemic prevention and control and the improvement of public health governance.
 Methods:
 Through the integration of relevant policies and regulations and detailed introduction, the author studied from three aspects: policies and regulations related to people's life, health and safety, improvement of public health and safety risk prevention and promotion of environmental protection and human civilization development, and analyzed its impact on all aspects of human society, especially public health safety and emergency management system and management capacity, to remind people to change the habit of over eating wild animals.
 Results:
 The article is of reference and guiding significance in promoting the global implementation of comprehensive fasting for wild animals, and in the current epidemic prevention and control of other countries, maintaining social public health and security governance, and safeguarding human health.
 Main Contribution to Evidence-Based Practice:
 The article demonstrates that the relevant policies, laws and regulations of China's comprehensive prohibition of wildlife have reference and guiding significance for epidemic prevention, maintenance of social public health and safety management, and protection of human health. In addition, it has promoted the global implementation of a comprehensive ban on wildlife.

Research on Video Anomaly Detection Based on Cascaded Memory-augmented Autoencoder

<p>Video anomaly detection (VAD) is crucial in public safety and intelligent video surveillance systems and has been widely researched and applied in academia. This paper proposes a video anomaly detection method based on the Cascaded Memory-augmented Autoencoder (CMAAE). CMAAE stores feature prototypes of standard samples in a memory pool and embed multiple memory-enhancing modules in the encoder-decoder structure. SE attention is introduced into memory modules to improve their performance, and skip connections are used to share attention weights among memory modules, enabling the model to learn more comprehensive feature information and enhance the quality of reconstructed video frames. Multiple loss constraint models are used during training to improve anomaly detection accuracy. CMAAE achieves outstanding performance of 99.2% on the UCSD Ped2 dataset and 89.4% on the CUHK Avenue dataset, demonstrating the effectiveness of our approach.</p> <p> </p>

Crowd counting algorithm based on face detection and skin color recognition

This paper introduces an innovative crowd counting algorithm using skin color information. Through stages of color space transformation, threshold segmentation, morphological processing, and region filtering, the algorithm successfully conducts crowd counting in images. The study encompasses analyses of images with diverse crowd densities, skin colors, backgrounds, and lighting intensities, revealing the algorithm's robustness to various factors. It remains unaffected by skin color and crowd size and exhibits minimal sensitivity to background and lighting intensity. Furthermore, the paper explores image feature analysis and uses MATLAB programming for simulation and initial crowd counting, considering images with different actual crowd sizes. Despite minor issues such as the insufficient separation of faces from clothing and the influence of lighting intensity, the algorithm performs reliably in most scenarios, demonstrating high crowd counting accuracies. To bolster the accuracy and robustness of the algorithm, optimization of the separation step and control of the lighting effect on images is suggested. The key focus of this study is the application of the Gaussian model in the YCbCr color space for face detection and examining its impact on the efficiency and accuracy of crowd counting algorithm. The research not only provides a novel approach for crowd counting in images but also offers insightful perspectives for future studies and potential improvements. Thus, the study proves to be a significant contribution to face detection and recognition technology, enhancing its application in fields like public safety, crowd management, and surveillance systems.

Firebug Optimized Modified Bee Colony Algorithm for Trusted WSN Routing

Wireless sensor networks (WSNs) have become a crucial technology because they are used in several contexts, such as public safety, environmental monitoring, healthcare, military operations, and surveillance systems. The applications of WSNs have increased because they can be deployed in areas where cable and power supply are difficult to use. However, a variety of security assaults can easily penetrate these networks. To solve this problem, a Firebug Optimized Modified Bee Colony algorithm (FOMBC) has been proposed, which achieves the maximum network security goal with lower energy consumption in WSN. The proposed method is carried out into two phases namely Secure node selection and Orthogonal Routing (OR). In the first phase, secure node among the WSN’s initial nodes is selected based on characteristics such as trust, delay, and Quality of Services. In the second phase, Firebug Optimized Modified Bee Colony (FOMBC) Optimization technique is used to find optimal route based on factors like trust, distance, latency, and quality of service. The effectiveness of the proposed FOMBC approach is evaluated against existing techniques like Trust-Aware Routing Framework (TARF), SOAR (Simple Opportunistic Adaptive Routing Protocol), Particle Swarm Optimization, and Whale Optimization Algorithm for Secure Routing (PSWOSR). According to the experimental findings, the proposed FOMBC technique achieves high detection, maximum throughput, least latency, and minimum range. The proposed method achieves network lifetime of 4.7%, 5.8%, and 9.87% than the existing TARF, SOAR, and PSWOSR, respectively.

A thorough examination of smart city applications: Exploring challenges and solutions throughout the life cycle with emphasis on safeguarding citizen privacy

With the increasing use of artificial intelligence (AI) and the Internet of Things (IoTs), it is crucial to acknowledge the potential security and privacy issues that arise from these advanced technologies in smart cities. This article provides overview of these concerns, highlighting the various ways in which smart city technologies can be vulnerable to cyber-attacks and other security threats. Additionally, the paper examines the privacy risks associated with the collection and use of personal data in smart cities. Effective security measures and privacy protection policies are crucial in ensuring the safety and security of smart cities. Cooperation between governments, private companies and citizens is essential to implement such measures and policies, allowing smart cities to continue developing while guaranteeing the security and privacy of their citizens. Likewise, smart city public safety systems that utilize AI-powered surveillance technologies may be predisposed to hacking, leading to privacy breaches and data misuse. Moreover, smart city energy systems, which rely on IoT devices to regulate power grids, are susceptible to cyber-attacks that can result in power outages or significant damage to vital infrastructure. The adoption of information and communication technology for smart city development has increased the risk of cyber threats, emphasizing the need for a review cybersecurity governance model. In addition, smart city water systems that rely on AI-powered sensors to monitor water quality may also be at risk of hacking, which could result in the contamination of the water supply. Further research is required to better understand the potential risks associated with smart city technologies and develop new solutions to address them. This article shows as a valuable resource for city administrators, policymakers and researchers interested in the security and privacy concerns of smart cities.

A Cohort Study of Occupational Fatalities among Paramedicine Clinicians: 2003 through 2020.

Emergency medical technicians (EMTs) and paramedics respond to 40 million calls for assistance every year in the United States; these paramedicine clinicians are a critical component of the nation's health care, disaster response, public safety, and public health systems. The study objective is to identify the risks of occupational fatalities among paramedicine clinicians working in the United States. To determine fatality rates and relative risks, this cohort study focused on 2003 through 2020 data of individuals classified as EMTs and paramedics by the United States Department of Labor (DOL). Data provided by the DOL and accessed through its website were used for the analyses. The DOL classifies EMTs and paramedics who have the job title of fire fighter as fire fighters and so they were not included in this analysis. It is unknown how many paramedicine clinicians employed by hospitals, police departments, or other agencies are classified as health workers, police officers, or other and were not included in this analysis. An average of 206,000 paramedicine clinicians per year were employed in the United States during the study period; approximately one-third were women. Thirty percent (30%) were employed by local governments. Of the 204 total fatalities, 153 (75%) were transportation-related incidents. Over one-half of the 204 cases were classified as "multiple traumatic injuries and disorders." The fatality rate for men was three-times higher than for women (95% confidence interval [CI], 1.4 to 6.3). The fatality rate for paramedicine clinicians was eight-times higher than the rate for other health care practitioners (95% CI, 5.8 to 10.1) and 60% higher than the rate for all United States workers (95% CI, 1.24 to 2.04). Approximately 11 paramedicine clinicians are documented as dying every year. The highest risk is from transportation-related events. However, the methods used by the DOL for tracking occupational fatalities means that many cases among paramedicine clinicians are not included. A better data system, and paramedicine clinician-specific research, are needed to inform the development and implementation of evidence-based interventions to prevent occupational fatalities. Research, and the resulting evidence-based interventions, are needed to meet what should be the ultimate goal of zero occupational fatalities for paramedicine clinicians in the United States and internationally.

Association between EMS Workforce Density and Population Health Outcomes in the U.S.

Background The prehospital care provided by emergency medical services (EMS) personnel is a critical component of the public health, public safety, and health care systems in the U.S.; however, the population-level value of EMS care is often overlooked. No studies have examined how the density of EMS personnel relates to population-level health outcomes. Our objectives were to examine the geographic distribution and density of EMS personnel in the U.S.; and quantify the association between EMS personnel density and population-level health outcomes. Methods We conducted a cross-sectional evaluation of county-level EMS personnel density using estimates from the National Registry of Emergency Medical Technicians in nine states that require continuous national certification (Alabama, Louisiana, Massachusetts, Minnesota, New Hampshire, North Dakota, South Carolina, Vermont, and Washington, D.C.). Outcomes of interest included life expectancy, all-cause mortality, and cardiac arrest mortality. We used quantile regression models to examine the association between a 10-person increase in EMS personnel density and each outcome at the 10th, 50th (median), and 90th percentiles, controlling for population characteristics and area health resources. Results There were 356 counties included, with a mean EMS density of 223 EMS personnel per 100,000 population. Density was higher in rural compared to urban counties (247 versus 186 per 100,000 population; p = 0.001). In unadjusted models, there was a significant association between increase in EMS personnel density and an increase in life expectancy at each examined percentile (e.g., 50th percentile, increase of 52.9 days; 95% CI 40.2, 65.5; p < 0.001), decrease in all-cause mortality at each examined percentile, and decrease in cardiac arrest mortality at the 50th and 90th percentiles. These associations were not statistically significant in the adjusted models. Conclusions EMS personnel density differs between urban and rural areas, with higher density per population in rural areas. There were no statistically significant associations between EMS density and population-level health outcomes after controlling for population characteristics and other health resources. The best approach to quantifying the community-level value that EMS care may or may not provide remains unclear.

Co-Communication Graph Convolutional Network for Multi-View Crowd Counting

We study and address the multi-view crowd counting (MVCC) problem which poses more realistic challenges than single-view crowd counting for better facilitating crowd management / public safety systems. Its major challenge lies in how to fully distill and aggregate useful, complementary information among multiple camera views to create powerful ground-plane representations for wide-area crowd analysis. In this paper, we present a graph-based, multi-view learning model called Co-Communication Graph Convolutional Network (CoCo-GCN) to jointly investigate intra-view contextual dependencies and inter-view complementary relations. More specifically, CoCo-GCN builds a view-agnostic graph interaction space for each camera view to conduct efficient contextual reasoning, and extends the intra-view reasoning by using a novel Graph Communication Layer (GCL) to also take between-graph (cross-view), complementary information into account. Moreover, CoCo-GCN uses a new Co-Memory Layer (CoML) to jointly coarsen the graphs and close the &#x2018;representational gap&#x2019; among them for further exploiting the compositional nature of graphs and learning more consistent representations. Finally, these jointly learned features of multiple views can be easily fused to create ground-plane representations for wide-area crowd counting. Experiments show that the proposed CoCo-GCN achieves state-of-the-art results on three MVCC datasets, i.e., PETS2009, DukeMTMC, and City Street, significantly improving the scene-level accuracy over previous models.

Problems and Directions of Cooperation of the National Rescue and Firefighting System with the Structures of Local Self-Government

Cel: The aim of the article is to identify directions for improving cooperation between the national rescue and firefighting system (KSRG) and local government units. The authors of this article have analysed the structure of KSRG and the powers of local government in the area of public safety, with particular emphasis on issues relating to the principles of operation, potential and tasks of the rescue and firefighting system, as well as the organizational structure of local government and its tasks in maintaining public safety. The discussion of the cooperative strategy of KSRG and local government units was also a contribution to formulating conclusions and postulates that can be used to set new directions for improving cooperation between the two entities. This is important due to the fact that they play an important role in building a security system for citizens and their property. Wprowadzenie: Ensuring security is one of the top priorities in every country’s policy. In the area of public safety, in addition to national units (State Fire Service, State Medical Rescue) and local government units, properly prepared, organized and specialized formations such as OSP, ZHP, WOPR, GOPR, TOPR and others also participate. Regardless of the type of security units, in any case, the identification of potential hazards is the basis for planning preventive measures, it allows to define the areas that involve the greatest risk of natural disasters and technical failures. Metodologia: The article uses theoretical research methods, including an analysis of the provisions of the Act on Fire Protection, the Regulation on the Detailed Organization of the National Rescue and Firefighting System, the provisions of the Constitution of the Republic of Poland, the Act on Volunteer Fire Brigades and the acts regulating the status and tasks of local government. The article discusses the structure and tasks of the national rescue and firefighting system, with particular emphasis on the cooperation of KSRG with the local government units. The publication also formulates de lege ferenda postulates. While presenting proposals to improve the cooperation of entities operating within KSRG, the authors also used their knowledge and experience gained during many years of work and service for fire protection. Wnioski: The national rescue and firefighting system is an integral part of our country’s public safety system. The experience of recent years has confirmed that it is an effective guarantee of the safety of people and property, while its structure forms a coherent system of rescue forces and resources centred around various entities. Constant technological and political-economic changes impose the need to improve the system and adapt it to current social needs. Therefore, the development of KSRG still requires setting new tasks and looking for solutions to effectively achieve the goals of the system. An important element to improve the operation of KSRG is the construction of the best possible form of cooperation between the rescue formations of the PSP and OSP and local government, since effective security protection is not possible without the cooperation of government and local administration. Słowa kluczowe: public safety, rescue and firefighting system, local government, fire protection

Police system reform in China after the Sino-Japanese War

The modern police system was first introduced in China at the beginning of the 20th century through the late Qing Reform. The Qing government sought to reform China’s traditional public safety system by modeling it after civil law standards in the world and especially after Japan’s police system—a tendency later also inherited by the Republic of China. However, there also existed a tendency of modeling after common law. This second tendency, which was manifested more in the Nationalist government period and was mainly orientated towards copying the police system of the US, was a topic not yet sufficiently dealt with in previous research. This paper examines the topic by referencing the so-called the system of “police management zones” (警管区制) implemented after the Sino-Japanese War. As postwar China was planning a radical shift towards constitutional government, this new system caused great public dispute, questioning the significance of concepts such as constitutional rule and freedom.

Public safety analysis and safety system using arduino

Today, personal security has become a major issue for both men & women. Women have endured carnal harassment these days which is shocking every day. The circumstances are much worse in growing and less developed countries. Women’s safety is an hour-long necessity these days. In India, there are many cases of violence against women. Important saftey measures for men & women should be there at home, outside or in their workplace. In this paper an attempt has been made to make a smart machine that can help women when they feel unsafe. Women can get faster support and higher security by pressing the device’s emergency button. In the event of an incident, this device can trace the location of the user in actual time and send it to the nearest police station and volunteers [5]. The user can find a secure area nearby with this device as well. Additionally, this gadget works on both online and offline modes. Whether no internet is available, the user can still use the gadget to access the nearest police station and volunteer support. The device contains Raspberry pie, GSM, PIR sensors, Bluetooth, GPS, etc [2]. The sum of all these features together makes this gadget affordable and easy to navigate.

Design of public safety and health system in the context of epidemic

Designing the public safety and health system in the context of epidemic is critical to public safety. This paper conducts modeling and analysis on the basis of the SIR model, establishes the “big prevention” system and the “grassroots” grid system. The purpose is to improve the response speed of the public safety and health system respectively, and play a reverse detection role on the epidemic data reported by the grassroots and reduce the possibility of under-reporting. The big data and computer network are used in the public safety and health system, which is the main tool of information transmission and analysis of the public safety and health system. Finally, the feasibility of the design is demonstrated by a case study.

Koncepcja rozwiązania modelowego dla systemu bezpieczeństwa publicznego dużej aglomeracji miejskiej

The subject of this study is to present the concept of a model solution for the public security system of monocentric and polycentric agglomeration. Taking into account the security conditions of a large urban agglomeration, one universal scheme of police organization has been adopted. Its func-tioning on the basis of specific forms and methods to some extent limits the autonomy of police chiefs in shaping safety in accordance with the specificity and internal social and organizational conditions of the agglomeration. Among the available research methods, the participatory observation method was used in particular. Nevertheless, the basic scientific method for obtaining empirical data was a diagnostic survey. Furthermore, the article presents the opinion of police officers on the transfer of solutions from the Warsaw agglomeration to other agglomerations in Poland. The author’s conceptual proposal of a model solution for the public safety system of a large urban agglomeration was presented.

Sensor Cloud Frameworks: State-of-the-Art, Taxonomy, and Research Issues

In recent times, Wireless Sensor Network (WSN) technology has received significant attention owing to its numerous applications in various mission critical services, such as healthcare, military monitoring, public safety systems, and forest monitoring. However, sensor node’s low computational power and inadequate advancements in battery design hinder resource-rigorous applications from fully exploiting WSN capabilities. The trend of shifting computations and storage to remote clouds offers the opportunity to integrate WSNs into the cloud to mitigate their limitations. The Sensor Cloud augments WSN capabilities of remote sensing and monitoring while exploiting resource-rich cloud infrastructure. To date, numerous solutions have been proposed to handle the integration concerns of WSNs with the cloud. However, a comprehensive study that covers various Sensor Cloud aspects in terms of architecture, network dynamics, heterogeneity, communication patterns, data management, and security, is still lacking. To fill this gap, state-of-the-art sensor cloud integration frameworks are analyzed in this article. Moreover, a detailed thematic taxonomy is presented to classify existing sensor cloud frameworks while focusing in service oriented and client server architectures. Related features and critical aspects of existing frameworks are inspected through a qualitative analysis based on the parameters selected from the literature and extracted from the taxonomy. Several research opportunities in this research domain are suggested to assist researchers in identifying and designing optimal resource sensor cloud integration frameworks to host emerging applications.

Features of Identification of Hybrid Projects of Public Security Systems and Their Process Management

An analysis of scientific works defining methodologies, methods and models of managing development projects and the functioning of security systems concerning separate branches and territories, as well as approaches to the implementation of hybrid projects of public security systems has been performed. It has been established that there is a need to conduct research on the development of scientific and methodological identification of hybrid projects of public security systems and their management processes. Nine identifying features of hybrid public safety projects are outlined. The proposed characteristics identifying hybrid projects of public security systems are based on their initiation and implementation of management processes. The hierarchical model of the structure of hybrid projects of public security systems is substantiated. It provides for the consideration of hybrid projects of public security systems at three levels which outline the purposeful and continuously managed interaction between individual processes and their elements. It is substantiated that the purposefulness and manageability properties of hybrid projects of public safety systems significantly affect the indicators of their value and underlie the development of tools for determining the value of these projects. Further research requires the development of tools to determine the value of hybrid projects of public safety systems.