Emergency Communication Research Articles

Understanding community resilience during the drinking water contamination event on Oahu, Hawaii, 2021–2022: a mixed mode approach

Abstract Background A petroleum leak into the Joint Base Pearl Harbor-Hickam water system on Oahu, Hawaii in November 2021 contaminated the drinking water of approximately 93,000 users, causing many to relocate for months. Perceptions of health and wellbeing were captured using the Centers for Disease Control/Agency for Toxic Substances and Disease Registry (CDC/ATSDR) Assessment of Chemical Exposures (ACE) cross-sectional survey in collaboration with the Hawaii Department of Health (HDOH). Methods Responses from the ACE online survey of community members, businesses, schools, health care and veterinary care organizations during the contamination event, containing quantitative questions and qualitative information from an open text field, were analyzed. Separately, a qualitative key informant questionnaire was administered to community establishments. Thematic content analysis was used to analyze and identify prominent themes from the ACE open text field and the key informant responses that were triangulated by the quantitative data when the themes aligned. Results Six major themes of disruption, communication, trust, stress, support, and ongoing needs were identified. Burdensome logistics from obtaining alternate water, negative financial impacts from relocation or losing business, distrust of information, perceived lack of support from response entities and uncertainty of long-term health impact caused significant disruption, stress and mental health. Individuals reported needing water, shelter, and mental health care while establishments wanted financial reimbursement and a resolution. Conclusions The findings show that environmental disasters have significant disruptive and mental health impacts from stress. Identified themes can inform and improve emergency response and communication strategies and increase trust with community members during and after large chemical exposure events.

Abstract Su407: Implementing An Effective Standardized Bystander CPR Protocol For US Golf Courses

Background: A golf course is the fifth most common public place for cardiac arrest (CA). Informal interviews with golfers and golf course personnel revealed striking incomplete and variable knowledge about what to do in the event of a CA on a golf course in accordance with most current bystander resuscitation guidelines. Hypothesis: We hypothesized that the development and implementation of a standardized protocol (called “911-CPR-AED”) for the three most critical first steps to assure aperson’s survival of an on-golf course CA will improve chances of surviving if playing partners, caddies and club staff are well prepared to respond urgently and appropriately to such an emergency. Aim: To successfully implement the standardized “911-CPR-AED” protocol for 4 different golf clubs. Approach: We achieved full support and involvement of the Club Boards, professional staff, club management, grounds crew and membership as well as coordination with local Emergency Medical Systems (EMS) and communications to all golfers and caddies. We created a specific four-panel laminated infographic customized for each club and designed to fit easily into every golfer’s bag and caddy vest, assuring a readily available “911-CPR-AED” guide for lay bystanders to notify EMS and Club staff, immediately initiate chest compressions, ensure rapid delivery of an AED and BLS certified persons to the arrest site, and safely guide EMS on their arrival. We also staged live “dry run’ simulations on the golf courses with all key team members and timed each and every step of the simulation from start to finish. All aspects of this process were shared with leaders of the closest EMS and hospital emergency departments (EDs). Results: Within the past 2 years, we have successfully implemented a standardized emergency resuscitation protocol we call “911-CPR-AED” at 4 different golf clubs for immediate initiation of bystander CPR in the event of full CA on a golf course. Since implementation, we have witnessed 3 CA events and achieved successful full “on course” resuscitations that deployed this protocol for all three survivors who are now back to playing golf. We intend to share the details and many lessons learned for these ongoing efforts. Conclusion: An effective, standard bystander CPR protocol now exists for use at any US golf course. We intend to expand Implementation to 3 new golf courses and will continue to raise awareness and encourage widespread local implementation across the US.

Research on path planning in UAV-assisted emergency communication

The rapid development of UAV communication technology makes it have application potential in wireless systems. However, for the optimization problem of UAV base station providing communication for ground personnel in the disaster area under special natural disasters, traditional deep reinforcement learning is used. Algorithms cannot solve such problems well. This article proposes the AD3QN algorithm combined with the attention mechanism, which can communicate with disaster victims on the ground better and more quickly, providing better information collection for rescue missions and completing the task of communication optimization. In the mission simulation environment, in order to make the environment more realistic, we innovatively designed the ground user distribution model, air-to-ground communication model, and electromagnetic interference model. Finally, the effect of the proposed algorithm is evaluated by comparing different deep reinforcement learning algorithms. The results show that the algorithm we proposed can provide communication services faster and has higher practicability in terms of algorithm.

Innovative navigation: a smart cane solution with GPS, GSM, and real-time image capture

Our article presents the design, study, and implementation of a smart cane aimed at enhancing the autonomy and safety of individuals who are blind or visually impaired. The solution is built around an Arduino board, integrated with various sensors and modules, to provide real-time tactile and auditory feedback to the user. Utilizing a combination of basic and advanced technologies, this smart cane detects obstacles at varying distances, triggering sound and vibration alerts to assist the user in navigation. Beyond these essential functions, the cane offers advanced features such as real-time image capture and obstacle recognition through the ESP32-CAM module. Additionally, the system is equipped with a GSM module that facilitates emergency communication by sending SMS messages with the user’s GPS location, obtained via the Neo-6M GPS module. These technological enhancements improve user safety by streamlining obstacle detection and enabling remote assistance when needed. The primary objective is to create a comprehensive solution that not only detects and avoids obstacles but also provides visual information and supports communication with caregivers or emergency services. By doing so, the smart cane contributes to a higher degree of independence and an improved quality of life for blind and visually impaired individuals.

Systematic review and meta-analysis on the mental health of emergency and urgent call-handlers and dispatchers.

Call-handlers and dispatchers (CHDs) working in specialized emergency and urgent communication centres are essential in supporting public safety and health. Evidence suggests that these professionals are at increased risk of mental health conditions, including post-traumatic stress disorder (PTSD), depression, anxiety and alcohol abuse among other conditions; however, reliable prevalence estimates remain undetermined. We provide the estimated pooled prevalence for PTSD, depression, anxiety and hazardous drinking among emergency and urgent CHDs globally. We searched 10 electronic databases, grey literature and the Annals of Emergency Dispatch and Response. Eligible studies reported original quantitative data and used validated self-reported measures on the prevalence of mental health conditions of interest (i.e. PTSD, depression, anxiety and alcohol use) within CHD professionals. Three reviewers independently screened results for eligibility. Prevalence estimates were pooled using random-effects meta-analyses. In total, 16857 references were retrieved. From these, 183 full-text articles were assessed for eligibility, of which 37 articles were included in this systematic review, and 13 articles provided necessary quantitative information for meta-analyses. In total, 7759 CHDs were considered across nine different countries. The overall pooled prevalence for PTSD was 17.8% (95% confidence interval [CI] 12.4-24.0%), depression was 28.2% (95% CI 20.7-36.2%), anxiety was 17.2% (95% CI 6.6-31.5%) and hazardous drinking was 17.8% (95% CI 6.9-32.2%). These findings indicate CHDs are at significant risk of mental health problems. Further quantitative and qualitative research is warranted to help understand the psychological risks of working as a CHD and guide appropriate psychological support.

How to improve the effectiveness of the cooperation networks of emergency science communication for public health emergencies

Emergency science communication is an important emergency activity that can enhance public safety awareness and risk perception ability, optimize health-protective behaviors, and reduce losses from emergencies. Certainly, emergency science communication needs to be multisource information and cross-organization. Moreover, increasing cooperation in emergency science communication is the key to improving the effectiveness of science communication in public health emergencies. To clarify the cooperation relationships among emergency organizations in emergency science communication, emergency science communication cooperation networks (ESCCNs) are constructed on the basis of the social network analysis method, and the practice of emergency science communication in response to COVID-19 in China is taken as the case. Through an interpretation of the characteristics of ESCCNs in the emergency response phase and the ongoing emergency phase, the differences in the cooperation modes of public health emergencies in different phases are analyzed. Moreover, the influence of different emergency phases on the formation of the ESCCN of the whole phase is discussed. With the evolution of the emergency phase, the network tightness, equilibrium and connectivity of the ESCCN all tend to increase, whereas network agglomeration decreases. In the emergency response phase, the core-edge features of the ESCCN are obvious, and emergency science communication organizations (ESCOs) are more inclined to form emergency science communication cooperation with other ESCOs of the same type. However, in the ongoing emergency phase, the cooperation relationships between ESCOs are more balanced, and more diversified cross-group cooperation relationships are formed. The diversification of ESCO types, the closeness of ESCO relationships and the connectivity of ESCCNs are the main factors that promote the formation of the ESCCN of the whole phase. Furthermore, implications for strengthening the efficiency of science popularization cooperation in public health emergencies are proposed in connection to matching dynamic characteristics, optimizing resource allocation and strengthening institutional guarantees.

Impact of AI on public health emergency communication in Europe and Central Asia: A Delphi study

Abstract Background Artificial Intelligence (AI) holds the potential to fundamentally transform public health communication - presenting promising opportunities alongside profound challenges and risks. This two-wave Delphi study therefore invited practitioners and scholars to assess the potential impact of AI on the risk communication, community engagement, and infodemic management (RCCE-IM) of public health authorities in European and Central Asian countries. Methods In two successive online surveys, 54 experts - both RCCE-IM practitioners and scholars with expertise in (digital) health communication, risk communication, and AI - from 28 countries provided their assessment of the following analytical dimensions: (1) opportunities, challenges, and risks of AI, (2) conditions for the responsible use of AI, (3) potential future scenarios, and (4) prioritized actions. The first Delphi wave followed an open and exploratory approach, while the second wave sought to prioritize and rank key findings from the previous round. The survey instruments included open-ended and closed-ended questions that were analyzed through statistical analysis, inductive and deductive coding. Results Results showed that AI holds various opportunities for the RCCE-IM of public health communicators. Challenges and risks, such as algorithmic bias or concerns about inclusivity, equally affect RCCE-IM efforts. Experts identified seven principles for the responsible use of AI (e.g., fair, human-centered) and predicted optimistic (e.g., optimized workflows) and pessimistic (e.g., flood of (mis)information) scenarios for the future impact of AI. Prioritized actions range from regulation, resource allocation, and feedback to capacity building, public trust, and education. Conclusions To responsibly navigate the opportunities, challenges, and risks of AI for public health emergency communication, clear guiding principles, ongoing critical evaluation, and multi-sectoral collaboration are needed. Key messages • AI is likely to transform public health emergency communication. • A set of agreed-upon principles will support public health authorities in the responsible management of the opportunities, challenges, and risks of AI.

Information to the Population About COVID-19 in the First Year of the Pandemic: Case Study on the Portal of the Health Department of Campina Grande, Paraíba, Brazil

Objective: To analyze the risk communication about the COVID-19 pandemic carried out on the website of the Health Department of Campina Grande, Paraíba, Brazil. Theoretical Framework: Risk communication in public health emergencies, according to the WHO guideline for policy and practice of this health communication in crises. Method: Qualitative study, focused on the content analysis of the publications made on the website of the Health Department of Campina Grande, Paraíba, from March 2020 to December 2021. Results and Discussion: The Health Department of Campina Grande, Paraíba, effectively used its website to disseminate information about the COVID-19 pandemic, such as social isolation measures and partial lockdown in areas with a high incidence of cases; sanitary barriers to monitor symptoms and control circulation; the installation of a field hospital, expansion of testing in Basic Health Units and distribution of masks and hygiene kits in vulnerable areas. The most frequent words on the portal in 2022 were “pandemic”, “mask” and “coronavirus”, in daily updates, guidelines on prevention measures, service protocols, decrees and restrictions, education and awareness and vaccination campaign at the end of the year. Research Implications: There was publication of accurate and accessible information, publication of administrative acts, positive culture in public health and, therefore, these actions demonstrate a significant effort by the Campina Grande Health Department to use digital communication to face the COVID-19 pandemic in accordance with the UN guideline. However, it was observed that in terms of clarity, some messages used technical terms that may have made it difficult for less educated audiences to understand. The portal did not provide accessible versions for people with visual impairments. Originality/Value: This study contributes to demonstrating that during the pandemic, the Campina Grande Health Department portal was an essential tool for residents of Campina Grande-PB in a practical and accessible way, with constant updates, disseminating information on the progress of the disease, vaccination campaigns and preventive measures, such as the use of masks and social distancing, with potential contribution to the implementation of preventive measures and adherence to vaccination. It is suggested that there could be greater accessibility for people with less education and sensory disabilities.

Multifeatured Electronic Helmet to Enhance Road Safety and Rider’s Comfort

This paper presents a multi-featured electronic helmet designed to tackle critical road safety issues, including accidents, drunk driving, and over-speeding. The design incorporates a global system for mobile communications (GSM) and global positioning system (GPS) modules to accurately capture driver’s current location and send messages to predefined contacts. When encountering an accident, the helmet promptly notifies designated contacts and authorities, ensuring swift assistance. By integrating features for detecting over-speeding, accidents, and drunk driving, the helmet renders real-time alerts to both the driver’s family and traffic police, enhancing accountability and safety measures. Additionally, the helmet includes solar charging functionality for mobile devices receive 100% charged in 3.37 hours, thereby optimizing usability and emergency communication. A rain detection system protects mobile devices, while an internal warming mechanism caters to adverse weather conditions, and proffers enhanced comfort by maintaining internal form temperature between 26-27 ℃ and safety, especially in cold regions or for military personnel.

Ethiopian Emergency Medical services: Bridging up the Gaps in Prehospital Services

Abstract This review identified the critical gaps in pre-hospital emergency medical services (EMS) in Ethiopia, highlighting their detrimental impact on health outcomes, particularly among vulnerable populations. There are significant barriers to timely access to care, contributing to elevated morbidity and mortality rates from preventable conditions. Establishment of a structured pre-hospital care framework, emphasizing the need for trained emergency medical technicians, national EMS guidelines, and an effective emergency communication system is recommended. These findings advocate for enhanced community awareness and collaboration among stakeholders to address logistical challenges. As result, there is urgency of implementing systemic improvements in pre-hospital care to mitigate health disparities and foster economic development in Ethiopia.

LPG Gas Leak Detection System and LPG Fire Classification Based on Internet of Things and Artificial Intelligence with Telegram Bot as a Monitoring Tool

LPG gas leaks pose a serious threat in industrial kitchens as they can cause costly fires, both in terms of material and safety. To improve safety, an accurate detection system is required. This research focuses on developing an LPG gas leak detection system and LPG fire classification with Internet of Things and Artificial Intelligence technology. Supported by Telegram Bot as an emergency notification monitoring tool, this system uses MQ-2 sensors to detect LPG gas leaks and ESP32-Cam to classify LPG fires along with Pretrained-model technology such as Cascade Fire Detection on OpenCV Cloud Server. As the output of this system, the use of PWM control and automation oversees regulating the Exhaust Fan according to the detected leakage. FreeRTOS is also used for system task efficiency, and Port Forwarding with Ngrok Local Server allows public access to the ESP32-Cam. System testing was conducted by Black-Box testing, then evaluating the performance of the MQ-2 sensor against 400 ppm and 1500 ppm thresholds for LPG testing distances in open kitchens and closed kitchens, as well as analyzing system response and delay via HTTP protocol. The results demonstrated the system's success in detecting gas leaks, classifying LPG fires and facilitating emergency communication.

Jamming avoidance trajectory planning and load balancing user association in mmWave UAV-assisted HetECN

Emergency communication network (ECN) can provide fast, efficient and high-capacity communication services for specific areas by using mmWave transmission and unmanned aerial vehicles (UAVs) serving as aerial base stations (ABSs) or relay nodes. Now, in order to satisfy diverse demands, ECN should support different types of nodes, access methods, and traffic distributions, which is referred to as heterogeneous ECN (HetECN). Therefore, inappropriate trajectory planning and unbalanced traffic loading can lead to UAV flight collisions and network congestion. In this article, we jointly optimize UAV jamming avoidance trajectory and user association strategy aimed to load balancing, to maximize the utilization of HetECN. Specifically, an improved artificial potential field (APF) method along with mmWave beam forming technology is used to obtain the jamming avoidance trajectory of UAVs, and the optimal deployment location of UAVs are determined based on the distribution of ground users (GUs). Subsequently, the matching game and alliance game are comprehensively used to determine the load balancing based GU-UAV associated strategy under various GU demands, thereby ensuring traffic load balancing and resource optimization allocation. In addition, altitude fine-tuning have been made to further power consumption, thereby improving overall network efficiency. Simulation results demonstrate that the proposed method can achieve the expected performance in network utilities such as coverage rate, network capacity, load balancing effect of mmWave UAV-assisted HetECNs.

Burning through information: An investigation of information sources and information seeking behavior during 2020 Oregon wildfires

A series of wildfires in Oregon in 2020 resulted in severe human and property losses. Given the stressful and time-sensitive nature of such events, providing timely information to people during extreme weather events like wildfires can be challenging. Understanding individuals' most-frequently-used information sources along with their information seeking behaviors can help communicators to target audiences and effectively communicate emergency information. A quantitative study was conducted to explore the information sources Oregon residents frequently used during 2020 wildfire season along with the factors underlying their information seeking behaviors. The results indicated television news was the most frequently used information source by the respondents, followed by the National Weather Service. Rural and urban/suburban residents varied on their reliance on friends, family, and neighbors as information sources during the wildfires. Additionally, risk awareness, community type, emotional response to climate change, media trust, and age significantly predicted the information seeking behaviors of Oregon residents during the 2020 wildfire season. Those involved in communicating information during emergencies should be mindful of their audiences’ information source use and create messages for sources most likely to be relied upon. The implications of this research are useful for stakeholders dealing with emergency communication and management to better understand the public and their information needs and behaviors during emergencies.

Do not forget about transplant patients during disasters.

The frequency of natural disasters and man-made conflicts has risen significantly in the past two decades, coinciding with an increase in kidney transplant recipients globally. This review addresses the critical need for disaster preparedness to mitigate the severe impacts on this vulnerable patient cohort. Kidney transplant recipients are highly dependent on robust healthcare infrastructures for ongoing care, including specialized medical staff, advanced diagnostics, and a consistent supply of immunosuppressive medications. Disasters disrupt these essential services, leading to increased risks of organ rejection, infections, and other medical complications. Strategies at various levels, from government to individual patients, can help maintain care continuity during such crises. Effective disaster preparedness plans involving strategic medication stockpiling, emergency communication systems, and patient education are crucial to support kidney transplant recipients. By implementing these measures, healthcare systems can better protect the health and well being of transplant patients during and after disasters.

Enhanced Emergency Communication Services for Post–Disaster Rescue: Multi-IRS Assisted Air-Ground Integrated Data Collection

Enhanced Emergency Communication Services for Post–Disaster Rescue: Multi-IRS Assisted Air-Ground Integrated Data Collection

AI Governance in Healthcare: Best Practices, Solutions, and Unresolved Issues

What challenges are presented by AI adoption in healthcare? What role should AI governance play in regard to the opportunities and risks for generative AI (large language models like ChatGPT-4, etc.) in health? How do we responsibly evaluate new technology and ensure guardrails for its deployment, but without stifling innovation? How do we address societal fears and biases? What level of reliability and robustness should algorithms achieve before being adopted with confidence across healthcare? How can AI support health equity and expand access? We will explore these questions and more with some of the nation’s leading experts on these topics. Learning Objectives Understand key opportunities and challenges for AI governance in healthcare, particularly in regard to rapidly emerging generative AI applications Discuss various responsible AI and AI governance frameworks that seek to ensure safety and efficacy in AI adoption Explore the role of government, legislation, and regulators in supporting safe and equitable adoption of AI in healthcare Explore opportunities for government, industry, and academic partnerships to accelerate AI validation, development, and adoption of safety standards Consider the potential impact of AI on the healthcare workforce and provider and patient experiences Identify the risks we should be most concerned with and what approaches can we take to mitigate those risks? By the end of the presentation, participants should have a sense of the opportunities and challenges of adopting AI in healthcare, key risks and frameworks for mitigating them, and the potential role of government, academia, and industry in addressing these issues Generative AI application examples Patient Communication and Engagement Intelligent chatbots interacting with patients, answering their queries, providing health advice, and helping them manage their conditions Mental Health Support Provide psychological support to patients, helping them manage stress, anxiety, depression, and other mental health issues. Provide interventions based on CBT and other therapeutic techniques Automated Medical Documentation Note-taking can allowing doctors to focus more on patient care Education and Training Create educational content and personalized training for medical students and healthcare professionals, potentially simulating things like patient cases and providing guidance on diagnosis, etc. Synthesis and Summarization of Medical Research Make it easier for people to keep up with the latest developments Public Health Communication In a public health emergency, help craft health messages, FAQs, and timely and accurate updates for the public Generative AI challenges and limitations Ensuring the accuracy of AI-generated information Maintaining patient privacy Handling the ethical implications of AI and human-machine interactions in healthcare “Hallucinations” (false or inaccurate information) can occur when model has limited knowledge of a particular domain “Distraction” (losing track of earlier inputs) can occur when inputs go beyond allowable token count for model “context window” and models start to produce responses not relevant to queries and context.

Leveraging AI automated emergency response with natural language processing: Enhancing real-time decision making and communication

Artificial Intelligence (AI) and Natural Language Processing (NLP) technologies play an essential role in the ongoing development and advancements of emergency response systems. This paper explores the new opportunities and possibilities offered by the incorporation of AI-driven automated emergency response systems, and the benefits of using NLP to increase the efficiency of human language processing and communication in real time. Using case studies and applications, we analyse how integrating AI and NLP technologies can reduce response times, improve situational awareness and coordination between emergency services. We then explore how AI-driven models can be used to predict natural disasters, optimise emergency vehicle routes and identify areas of need in real time through the analysis of social media and emergency communications via NLP. However, we also discuss the issues that come with implementing these technologies, such as data-privacy challenges, technical limitations and the need for sustained retraining of AI systems. The conclusions of this research indicate that continued collaboration between stakeholders is necessary to overcome these barriers, and that substantial innovation is needed to maximise the potential of AI and NLP technologies in emergency management.

Challenges of Integrating ICD 11 into Automatic Alerting Systems.

Automatic alerting systems (AASs) can identify adverse health events but emergency communication relies on human operators and natural languages. For complete automation, we need to code the diversity of adverse events in a granularity that supports optimal dispatches. Hence, AAs shall integrate with the International Classification of Diseases (ICD). The ICD-11 coding system includes chapters for external causes of injury. However, ICD-11 supports coding injury incidents in electronic health records (EHRs) after they have occurred, while disregarding integrating real-time injury reporting within its framework. We explore the potential challenges associated with integrating ICD-11 into AAS by analyzing external causes of morbidity or mortality and the dimensions of external causes as potential areas of integration. We recognize the themes: (i) incident of injury, (ii) mode of transport, (iii) indoor location, (iv) outdoor location, and (v) type of building, and identify four challenges: (i) conceptual differences between the two systems, (ii) injury identification, (iii) presence of entities below the shoreline in ICD-11, and (iv) lack of specificity in certain ICD-11 codes related to AASs. For easy integration of ICD-11 into AASs, we recommend an AAS data dictionary and propose ICD-11 updates related to external causes of injury.

Developing Infectious Disease Outbreak Emergency Communications for Populations With Limited English Proficiency: Insights to Sustain Collaborations Between Local Health Departments and Community-Based Organizations.

State and local public health departments (LHDs) are encouraged to collaborate with community-based organizations (CBOs) to enhance communication and promote protective practices with communities made vulnerable during emergencies, but there is little evidence-based understanding of practical approaches to fostering collaboration in this context. This research focuses on how collaboration enhances LHD capacity for effective communication for people with limited English proficiency (LEP) during infectious disease outbreaks specifically and strategies to facilitate productive LHD-CBO collaboration. Qualitative, telephone interviews, conducted March-October 2021. Rural and urban jurisdictions with Chinese-speaking or Spanish-speaking populations across the United States. 36 LHD and 31 CBO staff working on outreach to Chinese and Spanish speakers during COVID-19. Interviews were audio-recorded, transcribed verbatim, and analyzed using a team-based, codebook approach to thematic analysis. During COVID-19, CBOs extended LHD capacity to develop and disseminate effective communication, meaning communication that is rapidly in-language, culturally resonant, locally relevant, and trusted. Practical strategies to enable and sustain effective collaboration were needed to address operational dimensions (eg, material and administrative) and relational dimensions (eg, promoting trust and respect). Policies and financing to support LHD-CBO collaborations are critical to improving communication with people with LEP and addressing long-standing inequities in outcomes during outbreaks.

Adaptive and low-cost resource synchronization based on data distribution service in high dynamic networks

In disaster-stricken areas monitoring, management, search, and rescue operations, unmanned aerial vehicles (UAVs) play a crucial role in disaster management and emergency communication due to their high mobility. To efficiently coordinate and plan UAVs and their carried sensor and base station resources, synchronization is essential to establish consistency, laying the foundation for high-level demands. In such scenarios, synchronization relies on request–response (RR) or publish–subscribe (PS) forms of information exchange. Existing research in the field typically focuses on higher-level applications and selects either RR or PS synchronization, thereby overlooking the potential advantages that could be gained from combining both methods to meet synchronization requirements. We propose a resource synchronization method based on the Data Distribution Service (DDS) and a linear time complexity subscription mechanism tailored to specific query demands, which considers the pros and cons of the above two information exchange forms and the bottom-layer network topology. Experimental results using open-source simulation tools demonstrate that the proposed method adapts to scene requirements and decreases bandwidth by at least 21.2% and packet rate by at least 3.7% compared to different baseline methods across three topologies, while satisfying delay and query success rate requirements. Furthermore, the method maintains robust performance in the face of dynamic changes in network topology, showcasing its robustness.