Combining Micro Technologies and Unmanned Systems to Support Public Safety and Homeland Security

Previously, the military establishment has been the primary developer and user of micro technologies associated with unmanned systems. As these technologies become available commercially, a need exists to integrate the use of the technology into local or regional public safety and homeland security incidents. The purpose of this presentation is to explain several key factors to consider when using micro technologies and unmanned systems in support of public safety and homeland security officials. Real time information is critical to the decision making process for public safety and homeland security officials to make assessments and quickly resolve crisis situations. Unmanned micro-vehicles and micro technologies are well suited to remotely observe, gather essential information, and immediately relay it to incident responders. These technologies can provide extremely important support during responses to hostage situations, hazardous environments, search and rescue, natural disasters, border patrol and many others. The true benefit is having remote resources providing real time support to incident responders. This paper discusses the use of several different types of micro-vehicle platforms in public safety scenarios and their use of associated technologies such as GPS （Global Positioning System） autopilot, communication, and sensor devices.

Study on Emphases and Trend of Tianjin Urban Public Safety Planning from the View of Bohai Rim Megalopolis

Nowadays urban public safety has been an important subject of study in urban planning study. And planners realized that a safe city is very important for sustainable development. Traditional urban public safety planning begins to perfect the contents and method. And regional research is an important aspect in the improvement of new era urban public safety planning. This paper chooses Tianjin, the important city in Bohai rim area as the example for research. Tianjin urban public safety planning includes not only comprehensive disaster prevention and reduction, effectively preventing and reducing disasters, ensuring the safety of the life and property of the residents, but also sharing resources and facilities from the view of megalopolis, eliminating hidden area troubles, reducing whole environment risks and so on.

How Does the Government Facilitate the Co-Production of Digital Public Safety Services?——Based on Empirical Evidence from Shenzhen

The application of big data technology provides support for the co-production of public safety services.Existing research often focuses on how technology influences co-production,but lacks attention to the key actors that drive co-production and the mechanisms that facilitate it.This study examines the role of government in the digital co-production of public safety services,using the practice of Shenzhen as a case study.Shenzhen has built 125 information systems based on over 100 billion pieces of big data,forming a model of digital safety service co-production.The study reveals three types of digital co-production,characterized by"government-business joint planning,passive participation of businesses and the public,and active cooperation among government,businesses,and the public"in the"design-production-application"stages.The study shows that the government is not only a co-producer but also a proactive actor in activating the willingness of non-governmental entities to participate.Local governments mobilize non-governmental participation through three mechanisms:empowerment,profit enhancement,and value co-creation.The"power-interest-value"paradigm is applicable for analyzing the co-production of public services and helps to explain the transformation mechanisms of co-production behavior.

AIGC challenges and opportunities related to public safety:A case study of ChatGPT

Artificial intelligence generated content(AIGC)is a production method based on artificial intelligence(AI)technology that finds rules through data and automatically generates content.In contrast to computational intelligence,generative AI,as exemplified by ChatGPT,exhibits characteristics that increasingly resemble human-level comprehension and creation processes.This paper provides a detailed technical framework and history of ChatGPT,followed by an examination of the challenges posed to political security,military security,economic security,cultural security,social security,ethical security,legal security,machine escape problems,and information leakage.Finally,this paper discusses the potential opportunities that AIGC presents in the realms of politics,military,cybersecurity,society,and public safety education.

Blockchain for public safety:A survey of techniques and applications

As an emerging technology,blockchain provides a range of advantages,such as decentralized and transparent data storage,secure access control,and enhanced data traceability.However,it is rarely applied in the field of public safety.This paper presents an in-depth survey of blockchain technology,focusing on its potential applications and implications within the field of public safety research.We explore the practical needs of multi-party data collaboration in emergency management and discusses the applicability and value of blockchain technology in this context.Additionally,this paper introduces and compares several popular blockchain platforms.By providing a comprehensive examination of blockchain technology and its potential benefits for public safety,this paper seeks to enhance understanding of the technology’s capabilities,encourage further research,and inspire innovation in this domain.

BLE Mesh： A Practical Mesh Networking Development Framework for Public Safety Communications

Owing to advanced storage and communication capabilities today, smart devices have become the basic interface between individuals and their surrounding environment. In particular, massive devices connect to one other directly in a proximity area, thereby enabling abundant Proximity Services（Pro Se）, which can be classified into two categories： public safety communication and social discovery. However, two challenges impede the quick development and deployment of Pro Se applications. From the viewpoint of networking, no multi-hop connectivity functionality component can be directly operated on commercially off-the-shelf devices, and from the programming viewpoint, an easily reusable development framework is lacking for developers with minimal knowledge of the underlying communication technologies and connectivity. Considering these two issues, this paper makes a twofold contribution. First, a multi-hop mesh networking based on Bluetooth Low Energy（BLE） is implemented,in which a proactive routing mechanism with link-quality（i.e., received signal strength indication） assistance is designed. Second, a Pro Se development framework called BLE Mesh is designed and implemented, which can provide significant benefits for application developers, framework maintenance professionals, and end users. Rich application programming interfaces can help developers to build Pro Se apps easily and quickly. Dependency inversion principle and template method pattern allow modules in BLE Mesh to be loosely coupled and easy to maintain and update. Callback mechanism enables modules to work smoothly together and automation processes such as registration, node discovery, and messaging are employed to offer nearly zero-configuration for end users.Finally, based on the designed Pro Se development kit, a public safety communications app called Quote Send App is built to distribute emergency information in close area without Internet access. The process illustrates the easy usability of BLE Mesh to develop Pro Se apps.

Urban design based on public safety-Discussion on safety-based urban design

Because of public safety problems in construction of urban surroundings,this paper expounds the necessity of the study on public safety-based urban design in perspective of modern city.It brings forward the concept of safety-based urban design and attempts to explore the basic connotation and contents with framework for studies.

WARA-PS:a research arena for public safety demonstrations and autonomous collaborative rescue robotics experimentation

A research arena(WARA-PS)for sensing,data fusion,user interaction,planning and control of collaborative autonomous aerial and surface vehicles in public safety applications is presented.The objective is to demonstrate scientific discoveries and to generate new directions for future research on autonomous systems for societal challenges.The enabler is a computational infrastructure with a core system architecture for industrial and academic collaboration.This includes a control and command system together with a framework for planning and executing tasks for unmanned surface vehicles and aerial vehicles.The motivating application for the demonstration is marine search and rescue operations.A state-of-art delegation framework for the mission planning together with three specific applications is also presented.The first one concerns model predictive control for cooperative rendezvous of autonomous unmanned aerial and surface vehicles.The second project is about learning to make safe real-time decisions under uncertainty for autonomous vehicles,and the third one is on robust terrain-aided navigation through sensor fusion and virtual reality tele-operation to support a GPS-free positioning system in marine environments.The research results have been experimentally evaluated and demonstrated to industry and public sector audiences at a marine test facility.It would be most difficult to do experiments on this large scale without the WARA-PS research arena.Furthermore,these demonstrator activities have resulted in effective research dissemination with high public visibility,business impact and new research collaborations between academia and industry.

A Game-Theoretic Approach to Safe Crowd Evacuation in Emergencies

Obstacle removal in crowd evacuation is critical to safety and the evacuation system efficiency. Recently, manyresearchers proposed game theoreticmodels to avoid and remove obstacles for crowd evacuation. Game theoreticalmodels aim to study and analyze the strategic behaviors of individuals within a crowd and their interactionsduring the evacuation. Game theoretical models have some limitations in the context of crowd evacuation. Thesemodels consider a group of individuals as homogeneous objects with the same goals, involve complex mathematicalformulation, and cannot model real-world scenarios such as panic, environmental information, crowds that movedynamically, etc. The proposed work presents a game theoretic model integrating an agent-based model to removethe obstacles from exits. The proposed model considered the parameters named: (1) obstacle size, length, andwidth, (2) removal time, (3) evacuation time, (4) crowd density, (5) obstacle identification, and (6) route selection.The proposed work conducts various experiments considering different conditions, such as obstacle types, obstacleremoval, and several obstacles. Evaluation results show the proposed model’s effectiveness compared with existingliterature in reducing the overall evacuation time, cell selection, and obstacle removal. The study is potentially usefulfor public safety situations such as emergency evacuations during disasters and calamities.

Multi-Period Resilient Model for VSC-Based AC-DC HDS Considering Public-Safety Power Shutoff to Mitigate Wildfires

This paper proposes a voltage source converter (VSC) -based AC-DC hybrid distribution system (HDS) resilient model to mitigate power outages caused by wildfires. Before a wildfire happens, the public-safety power shutoff (PSPS) strategy is applied to actively cut some vulnerable lines which may easily cause wildfires, and reinforce some lines that are connected to critical loads. To mitigate load shedding caused by active line disconnection in the PSPS strategy, network reconfiguration is applied before the wildfire occurrence. During the restoration period, repair crews (RCs) repair faulted lines, and network reconfiguration is also taken into consideration in the recovery strategy to pick up critical loads. Since there exists possible errors in the wildfire prediction, several different scenarios of wildfire occurrence have been taken into consideration, leading to the proposition of a stochastic multi-period resilient model for the VSC-based AC-DC HDS. To accelerate the computational performance, a progressive hedging algorithm has been applied to solve the stochastic model which can be written as a mixed-integer linear program. The proposed model is verified on a 106-bus AC-DC HDS under wildfire conditions, and the result shows the proposed model not only can improve the system resilience but also accelerate computational speed.

Human behaviour detection dataset (HBDset) using computer vision for evacuation safety and emergency management

During emergency evacuation,it is crucial to accurately detect and classify different groups of evacuees based on their behaviours using computer vision.Traditional object detection models trained on standard image databases often fail to recognise individuals in specific groups such as the elderly,disabled individuals and pregnant women,who require additional assistance during emergencies.To address this limitation,this study proposes a novel image dataset called the Human Behaviour Detection Dataset(HBDset),specifically collected and anno-tated for public safety and emergency response purposes.This dataset contains eight types of human behaviour categories,i.e.the normal adult,child,holding a crutch,holding a baby,using a wheelchair,pregnant woman,lugging luggage and using a mobile phone.The dataset comprises more than 1,5o0 images collected from various public scenarios,with more than 2,9oo bounding box annotations.The images were carefully selected,cleaned and subsequently manually annotated using the Labellmg tool.To demonstrate the effectiveness of the dataset,classical object detection algorithms were trained and tested based on the HBDset,and the average detection accuracy exceeds 90%,highlighting the robustness and universality of the dataset.The developed open HBDset has the potential to enhance public safety,provide early disaster warnings and prioritise the needs of vulnerable individuals during emergency evacuation.

Analysis of Types and Causes of Traumatic Dental Injuries to Permanent Dentition among Patients Attending Tertiary Care Hospital of Pakistan

Objective: This study aimed to evaluate the age, gender, causes, place of trauma, and type of crown fracture in permanent dentition among patients attending Liaquat University of Medical and Health Sciences Hospital (LUMHS), Jamshoro, Pakistan. Methodology: This cross-sectional study was conducted at the Operative Dentistry Department of LUMHS hospital over a period of six months. All patients (6 - 40 years of age) who had a history of dental trauma and attending dental OPD were included in this study. The data for all patients were recorded in a predesigned proforma. Data were collected on age, gender, place of trauma (playground, road, home), cause of trauma (fall, playing, road accident, bicycle accident, collisions, fighting) and associated symptoms. The data were analyzed using SPSS 22.0. Mean and the standard deviation was computed for a quantitative variable like age. Frequency and percentage were calculated for qualitative variables like gender, risk factors, and pattern of trauma. Results: A total of 82 patients were enrolled. The most frequent age group involved was 13 - 20 years (46%) with males (58.5%) predominance. The majority of trauma cases were due to fall (36.6%) while playing and 19.5% were bicycle accidents. The most commonly affected tooth was right maxillary central incisor (46.6%) followed by left maxillary central incisor (28.4%). Of the 116 teeth examined, 56.0% had a complicated crown fracture and 44.0% had an uncomplicated crown fracture. Conclusion: Safety measures should be implemented where dental traumatic accidents occur most frequently like at home and on the roads.

Perceptions of People on Police Efficiency and Crime Prevention in Urban Areas in Malaysia

Crime cases from snatch thefts to murders, are becoming increasingly common in Malaysia according to the database of the Royal Malaysian Police （RMP）, the current overall Crime Index in Malaysia was 147,062 for 2013 compared with 65,237 in 1977. The database also revealed that the number of property crimes reported in this country has always exceeded the number of violent crimes. Although in 2013, crimes related to property are higher （117,687） than violent crime （29,375）, the gradual increase in the latter does worry Malaysians. Likewise, Malaysian Government had implemented a ＂safe community＂ concept, inspired by the Malaysian Crime Prevention Foundation （MCPF）, a non-government organization, as they were concerned that the threat of violent crime and non-violent crime would eventually reduce the quality of life for many individuals. The concept is very important to the public as it is perceived as improved safety for the public with less crime. This study analyzes the public safety through their perceptions on the effectiveness of the policeman and suggesting few prevention actions against crime. The data were collected using a self-administered survey questionnaire. Specifically, this study focuses on the more developed states in this country. From the cross tabulation analysis, the majority of respondents agreed that the police are effective in controlling crime. Approximately, 72.1% of respondents felt that the police are efficient in controlling crime.

Prospects for the Development and Application of the Earthquake Monitoring Network

With the rapid development of the economy in China, the seismic network has been changing rapidly, in that the capability of instruments, technological systems and network density are approaching those of developed countries and a large quantity of observation data has been accumulated. How to apply these resources to economic construction and public safety has become an important issue worth studying. In order to improve earthquake prediction and earthquake emergency response, it is suggested in this paper that extracting valuable precursor information, improving earthquake rapid reporting ability and extending rapid intensity reporting function are key issues. Integrating network resources, building unified standards and a multifunction seismic monitoring network are preconditions of establishing a public safety service platform and earthquake observation resources will contribute significantly to the fields of engineering, ocean, meteorology, and environmental protection. Thus, the future directions of the development of the seismic network are exploring monitoring resources, enhancing independent innovation, constructing a technological platform and enlarging the service field.

Measurement Analysis of Specific Absorption Rate in Human Body Exposed to a Base Station Antenna by Using Finite Difference Time Domain Techniques

The system analysis of specific absorption rate(SAR)in human body ex­posed to a base station antenna by using finite difference time domain tech­niques was presented in this research works.The objectives of this work are to evaluate the knowledge and awareness about SAR among human body and mobile base station.The paper investigates the electromagnetic wave absorption inside a human body.The human body has been identified us­ing dataset based on 2D object considering different electrical parameters.The SAR convinced inside the human body model exposed to a radiating base station antenna(BSA)has been considered for multiple numbers of carrier frequencies and input power of 20 W/carrier at GSM 900 band.The distance(R)of human body from BSA is varied in the range of 0.1 m to 5.0 m.For the number of carrier frequency equal to one and R=0.1 m,the concentrated value of whole-body average SAR obtained by FDTD technique is found to be 0.68 W/kg which decreases either with increase of R or decrease of number of carrier frequencies.Safety distance for general public is found to be 1.5 m for number of carrier frequencies equal to one.The performance accuracy of this analysis meets the high level condition by comparing with the relevant system development in recent time.

Confluence of Encryption,Absorption and Sensation-Well Almost Nearly

In this issue,manuscripts have been published on a wide variety of topics,which demonstrates the large scope of Semiconductor Science&Information Devices.Even the authors are from diverse geographical areas!We con­tinue to encourage such submissions on varied topics.In fact,much of the engineering today is multi-disciplinary involving close cooperation&collaboration among many fields&specializations.

Early smoke and flame detection based on transformer

Fire-detection technology plays a critical role in ensuring public safety and facilitating the development of smart cities.Early fire detection is imperative to mitigate potential hazards and minimize associated losses.However,existing vision-based fire-detection methods exhibit limited generalizability and fail to adequately consider the effect of fire object size on detection accuracy.To address this issue,in this study a decoder-free fully transformer-based(DFFT)detector is used to achieve early smoke and flame detection,improving the detection performance for fires of different sizes.This method effectively captures multi-level and multi-scale fire features with rich semantic information while using two powerful encoders to maintain the accuracy of the single-feature map prediction.First,data augmentation is performed to enhance the generalizability of the model.Second,the detection-oriented transformer(DOT)backbone network is treated as a single-layer fire-feature extractor to obtain fire-related features on four scales,which are then fed into an encoder-only single-layer dense prediction module.Finally,the prediction module aggregates the multi-scale fire features into a single feature map using a scale-aggregated encoder(SAE).The prediction module then aligns the classification and regression features using a task-aligned encoder(TAE)to ensure the semantic interaction of the classification and regression predictions.Experimental results on one private dataset and one public dataset demonstrate that the adopted DFFT possesses high detection accuracy and a strong generalizability for fires of different sizes,particularly early small fires.The DFFT achieved mean average precision(mAP)values of 87.40%and 81.12%for the two datasets,outperforming other baseline models.It exhibits a better detection performance on flame objects than on smoke objects because of the prominence of flame features.

Key Technology Research for Mobile Police Terminal Fingerprint Collection for Quick Comparison Using Automated Fingerprint Identification System

When the face of the inspected person and the photograph on their identification(ID)card cannot be clearly matched,the individual is undocumented,or the ID is forged,it is often difficult for the on‑site police to respond in time.This study proposes a number of key technologies for collecting fingerprints at mobile terminals for fast comparison using an automated fingerprint ID system(AFIS).These technologies ensure intelligent mobile fingerprint collection and allow the transmission of fingerprint information from the terminal to AFIS,over a wireless public security network for real‑time fingerprint comparison.This study also analyzes the feasibility and effectiveness of the proposed technologies for system design and the applicability of fingerprint ID algorithms.The system achieved good results in a test by the Shanghai Public Security Bureau Criminal Investigation Corps.