Coverage Strategy Research Articles

An energy-efficient UAV deployment scheme for emergency communications in air-ground networks with joint trajectory and power optimization

The space-air-ground integrated network (SAGIN) has gained widespread attention from academia and industry in recent years. It is widely applied in many practical fields such as global observation and mapping, intelligent transportation systems, and military missions. As an information carrier of air platforms, the deployment strategy of unmanned aerial vehicles (UAVs) is essential for communication systems' performance. In this paper, we discuss a UAV broadcast coverage strategy that can maximize energy efficiency (EE) under terrestrial users' requirements. Due to the non-convexity of this issue, conventional approaches often solve with heuristics algorithms or alternate optimization. To this end, we propose an iterative algorithm by optimizing trajectory and power allocation jointly. Firstly, we discrete the UAV trajectory into several stop points and propose a user grouping strategy based on the traveling salesman problem (TSP) to acquire the number of stop points and the optimization range. Then, we use the Dinkelbach method to dispose of the fractional form and transform the original problem into an iteratively solvable convex optimization problem by variable substitution and Taylor approximation. Numerical results validate our proposed solution and outperform the benchmark schemes in EE and mission completion time.

HPR54 International Coverage and Financing Strategies for the Treatment of Obesity: A Scoping Review

Policies aimed to reduce the burden of disease associated with obesity can reduce up to 76,000 new cases of non-communicable diseases per year. For every dollar (USD) invested in obesity prevention, up to $ 5.6 in financial benefits will be returned. Most of the care is comorbidity-centered instead of obesity-centered, and gaps are observed.

Area Coverage Strategy in IoT Networks Based on Redeployment, Descriptive Statistics, Correlation and Regression Parameters

Area Coverage Strategy in IoT Networks Based on Redeployment, Descriptive Statistics, Correlation and Regression Parameters

Long-term trials for improvement of autonomous area coverage with a Tetris inspired tiling self-reconfigurable system

In the past two decades, robotics have invested tremendous research effort to deploy long-term autonomous robots to ensure a smart hygienic manufacturing environment in the food and drink industry and translated such attempts into successful robotic products. However, most such systems were developed with fixed morphological design, which highly constrains their navigation and access in constraint spaces. To this end, we have developed hTetro, Tetris-inspired self-reconfigurable floor-sweeping system capable of performing autonomously in a constrained environment for an extended period to maximize the cleaning area. This paper presents the hTetro robot’s improved system design, control system, and autonomous coverage strategy that supports achieving long-term deployment. We validated the performance of the proposed system by conducting trials in a complex food court environment as our case study. Our trials at SUTD Lab, SUTD Singapore canteen, and Tampines Singapore food center are divided into three phases from Jan 2020 until the end of Sep 2020. We tracked the robot’s movement every day during each trial while cleaning to generate the coverage map, which helps compute the total area covered. Also, we systematically benchmarked the robot’s coverage performance with a commercially available fixed morphology robot cleaning robot in the same environment. To our best knowledge, this is the first time the reconfigurable robot has been deployed to validate the feasibility in terms of mechanical designs, electronics, and software for long-term autonomy in the real environment. The result exhibits that after fixing the issues during the platform development state, our hTetro robot could achieve maximum area coverage performance every day during the long-term trial in a real environment than the commercial robot due to its shape-shifting ability. With the successful deployment of the reconfigurable cleaning robot, a further important step towards service robotics for daily use has been taken.

Strategic Resource Allocation and Implementation of Universal Health Coverage Policy in NHIF Northern Kenya Region

Universal health coverage (UHC) ensures that all people can access effective, good-quality health services when they need them, without experiencing financial hardship. A recent Kenya Household Health Expenditure and Utilization Survey (KHHEUS) on health insurance found that majority of the counties in the Northern Region, most of who rely on the NHIF, registered less than 10% coverage on average. Lack of adequate health coverage for most of the population means most will still need to meet their health needs using out-of-pocket payments. Therefore, the main objective of the study is to establish the influence of strategic resource allocation on implementation of universal health coverage strategy focusing on NHIF, Northern Kenya Region. Descriptive research design was used in the study that also targets six NHIF Northern Kenya region branches, that is, Meru, Maua, Embu, Chuka, Isiolo and Marsabit branches. Data collection was done through questionnaires distributed to a sample size of 70 management and staff members of the six NHIF branches selected through a census. Data was analyzed using both descriptive such as frequencies and percentages and inferential statistical methods specifically bivariate regression analysis. The findings revealed that resource allocation practices were negatively affecting the implementation of universal health coverage policy in Northern Kenya region. The study, therefore, recommends that the organization review its resource allocation practices. The resource allocation practices should be strategic and guided by the resource based view at the branch level.

Platelet-Rich Fibrin Versus Connective Tissue Graft Using Vestibular Incision Subperiosteal Tunnel Access (VISTA) Technique in Multiple Gingival Recessions: Randomized Controlled Trial

Background: One of the most common esthetic concerns in dentistry is gingival recession (GR), and despite the various treatment strategies for root coverage, multiple recessions still present a great challenge, especially Miller Class III/RT2. Thus, this study aimed to compare the effect of platelet-rich fibrin (PRF) versus connective tissue graft (CTG) using vestibular incision subperiosteal tunnel access (VISTA) in patients with Miller class III/RT2 multiple recessions for root coverage. Methods: Twenty-eight patients with multiple Class III/RT2 gingival recessions were randomly allocated to two equal groups – group 1 (VISTA+PRF) and group 2 (VISTA+CTG). Recession depth (RD) and width (RW), probing depth (PD), clinical attachment level (CAL), gingival thickness, keratinized tissue width, and root coverage esthetic score (RES) were measured at 0, 3, and 6 months. Statistical analysis was performed using repeated measures analysis of variance (ANOVA). Bonferroni’s post-hoc test was used for pair-wise comparisons when ANOVA was significant. For non-parametric data, the Mann-Whitney U test was used to compare between the two groups. Results: Within each group, a significant difference from baseline to six months was found. However, between groups, the results for the VISTA+CTG group significantly surpassed the VISTA+PRF group in most clinical outcomes; gingival recession depth (0.5 [0.25-1.75] and 1.33 [0.75-2], respectively), and width (1 [0.38-3.75] and 2.33 [1.33-3], respectively), gingival thickness at three and six months (2.62±0.36 and 2.63±0.36, respectively) and (1.85±0.2 and 1.87±0.18, respectively), and keratinized tissue width (3.98±0.72 and 3.33±0.56, respectively). However, CAL and PD showed a statistically insignificant difference when comparing both groups. Conclusion: The use of CTG is superior to PRF in root coverage of Miller Class III/RT2 when the VISTA technique is used. Connective tissue grafts can be considered the gold standard for root coverage.

Sustainable Development Goals and childhood measles vaccination in Ekiti State, Nigeria: Results from spatial and interrupted time series analyses

Measles remains an important cause of childhood mortality in many resource-limited countries. With Sustainable Development Goals (SDG), there has been increasing emphasis on measles vaccination as a key strategy to remarkably improve child survival. While progress has been made towards measles vaccination coverage due to SDG in some settings, there has been no prior study evaluating its impact in Nigeria. To assess the effectiveness of SDG policy implementation on measles vaccination coverage, we examined the changes in first dose of measles vaccination coverage rates among children aged 9–15 months following the implementation of SDG, and changes in spatial patterns of measles vaccination from 2014 to 2019 in Ekiti State, Southwest Nigeria. Using state and local government area-level District Health Information data from January 2014 to December 2019, we conducted interrupted time series (ITS) and spatiotemporal analyses. The ITS evaluated the immediate and continuous effects of SDG policy implementation on the monthly childhood measles vaccination coverage by comparing longitudinal changes in rates between pre-intervention period (January 2014-December 2015) and during-intervention period (January 2016-December 2019). The low and high coverage clusters across the years were detected with spatial cluster analysis. The average state-level measles vaccination coverage rates from 2014 to 2019 was 70.67%. In 2019, coverage rate was 49%—a 35.53% decline from 76% in 2014 and a state-level gap of 46%. The geographical distribution of measles vaccination varied considerably across the local government areas from 2014 to 2019. There was an initial acceleration of vaccination rates (β^ = 24.07, p-value = 0.012), but a significant decrease in coverage rates after implementation of SDG policy in Ekiti State (β^ = −1.08, p-value < 0.001). No local government area had accelerated monthly coverage rates following SDG-implementation. Evidence suggests immediate acceleration in coverage rates which could not be sustained during SDG-era and calls for a rethink measles immunization coverage strategy in the state and other resource-limited jurisdictions to ensure vaccination scale-up.

Multiobjective Optimization Strategy of WSN Coverage Based on IPSO-IRCD

The nonuniform distribution characteristic of randomly deployed mobile nodes will lead to the coverage hole and redundancy in wireless sensor networks (WSNs). To solve this problem, we propose a multiobjective optimization algorithm for WSN based on Improved Particle Swarm Optimization-Increment of the Ratio of Coverage Rate to Move Distance (IPSO-IRCD), and a network node coverage optimization model is formulated to maximize the coverage rate of the target area while reducing the moving distance of nodes. In each iteration of IPSO, the population fitness value is calculated and compared with the historical optimal value, when the arbitrary dimensional location information of each node is updated, which can avoid the standard PSO algorithm loses the optimal solution, and IPSO will determine the candidate deployment location of nodes. Based on which, IRCD node coverage scheduling optimization algorithm is proposed, so that the final deployment location can be determined iteratively by calculating IRCD of nodes. Simulation results indicate that, for the nodes initial coverage state follows random distribution and Gaussian distribution, IPSO-IRCD can, respectively, improve 4.6% and 7.4% coverage ratio compared with the suboptimal algorithm in other five similar algorithms and reduce 809.59 m and 626.63 m nodes moving distance.

System-Level Performance Analysis of Cooperative Multiple Unmanned Aerial Vehicles for Wildfire Surveillance Using Agent-Based Modeling

In this paper, we propose an agent-based approach for the evaluation of Multiple Unmanned Autonomous Vehicle (MUAV) wildfire monitoring systems for remote and hard-to-reach areas. Emerging environmental factors are causing a higher number of wildfires and keeping these fires in check is becoming a global challenge. MUAV deployment for the monitoring and surveillance of potential fires has already been established. However, most of the scholarly work is still focused on MUAV operations details. In wildfire surveillance and monitoring, evaluations of the system-level performance in terms of the analysis of the effects of individual behavior on system surveillance has yet to be established. Especially in an MUAV system, the individual and cooperative behaviors of the team affect the overall performance of the system. Such systems are dynamic and stochastic because of an ever-changing environment. Quantifying the emergent system behavior and general performance measures of such a system by analytical methods is challenging. In our work, we present an agent-based model for MUAV surveillance missions. This paper focuses on the overall system performance of cooperative UAVs performing forest fire surveillance. The principal theme is to present the effects of three behaviors on overall performance: (1) the area allocation and (2) dynamic coverage, and (3) the effects of forest density on team allocation. For area allocation, three behaviors are simulated: (1) randomized, (2) two-layer barrier sweep coverage, and (3) full sweep coverage. For dynamic coverage, the effects of communication and resource unavailability during the mission are studied by analyzing the agent’s downtime spent on refueling. Last, an extensive simulation is carried out on wildfire models with varying forest density. It is found that cooperative complete sweep coverage strategies perform better than the rest and the performance of the team is greatly affected by the forest density.

Modelling the impact of perfect and imperfect vaccination strategy against SARS CoV-2 by assuming varied vaccine efficacy over India

BackgroundThe outbreak of Coronavirus disease (COVID-19) has swiftly spread globally and caused public health and socio-economic disruption in many countries. An epidemiological modelling studies in the susceptible-infectious-removed (SIR) has played an important role for making effective public health policy to mitigate the spread of COVID-19. The aim of the present study is to investigate the optimal vaccination strategy to control the COVID-19 pandemic in India. MethodsWe have applied compartment mathematical model susceptible-vaccination-infectious-removed (SVIR) with different range of vaccine efficacy scenarios and predicted the population to be covered for vaccination per day in India as well as state level was performed. ResultsThe model assumed that a vaccine has 100% efficacy, predicted that >5 million populace to be vaccinated per day to flatten the epidemic curve in India. Similarly, different vaccination mechanisms such as ‘all-or-nothing’ (AoN) and leaky vaccines does not have potential discordance in their effectiveness at higher efficacies (>70%). However, AoN vaccine was found to be marginally effective than leaky at lower efficacies (<70%) when administered at the higher coverage strategies. Further state level analyses were performed and it was found that 0.3, 0.3, 0.2 and 1 million vaccinations required per day in Andhra Pradesh, Gujarat, Kerala and Maharashtra as it assumes that the vaccine efficacy is 70%. ConclusionThe proposed modelling approach shows a range of assumptions on the efficacy of vaccine which helps the health authorities to prioritize the vaccination strategies to prevent the transmission as well as disease.

Designing freemium with usage limitation: When is it a viable strategy?

• This study models the usage-limiting variants of freemium operations. • Two freemium strategies emerge from analyzing users’ response to usage insufficiency. • A full coverage strategy results in a high free-usage limit and price but low demand. • A partial coverage strategy results in low free-usage limit and price but high demand. • Market parameters determining the optimal strategy are identified. The freemium business model has seen wide adoptions to acquire new users quickly and inexpensively in recent decades. Its effectiveness lies with the promise of a particular form of free usage that is available indefinitely. This paper focuses on the freemium model that limits usage for free users and allows unlimited usage for paying users. We formulate a two-stage model that incorporates the responses of users who are heterogeneous in both their total usage and corresponding valuations. Two freemium strategies with distinct market-coverage approaches emerge, where the first strategy aggressively attempts to acquire the whole market while the second strategy selectively targets heavy users. When benchmarked against a conventional subscription strategy, we find that the dominance of a freemium strategy relies on users’ intolerance towards insufficient usage and the proportion of high-valuation users. High users’ intolerance to insufficient usage compels the firm to increase the free usage limit. The proportion of high valuation users determines the dominance between a selective freemium strategy and a conventional subscription strategy. We also find that a firm should expect a lower conversion rate when implementing an aggressive freemium strategy. Finally, we extend our study to consider the implications of new users’ forward-looking behavior.

Toward Improved Outcomes for Patients With Lung Cancer Globally: The Essential Role of Radiology and Nuclear Medicine.

PURPOSEKey to achieving better population-based outcomes for patients with lung cancer is the improvement of medical imaging and nuclear medicine infrastructure globally. This paper aims to outline why and spark relevant health systems strengthening.METHODSThe paper synthesizes the global lung cancer landscape, imaging referral guidelines (including resource-stratified ones), the reliance of TNM staging upon imaging, relevant multinational health technology assessments, and precisely how treatment selection and in turn patient outcomes hinge upon imaging findings. The final discussion presents data on current global gaps in both diagnostics (including imaging) and therapies and how, informed by such data, improved population-based outcomes are tangible through strategic planning.RESULTSImaging findings are central to appropriate lung cancer patient management and can variably lead to life-prolonging interventions and/or to life-enhancing palliative measures. Early-stage lung cancer can be treated with curative intent but, unfortunately, most patients with lung cancer still present at advanced stages and many patients lack access to both diagnostics and therapies. Furthermore, half of lung cancer cases occur in low- and middle-income countries. The role of medical imaging and nuclear medicine in lung cancer management, as outlined herein, may help inform strategic planning.CONCLUSIONLung cancer is the number one cancer killer worldwide. The essential role that medical imaging and nuclear medicine play in early diagnosis and disease staging cannot be overstated, pivotal in selecting the many patients for whom measurably improved outcomes are attainable. Prevention synergized with patient-centered, compassionate, high-quality lung cancer management provision mandate that strategic population-based planning, including universal health coverage strategies, should extend well beyond the scope of disease prevention to include both curative and noncurative treatment options for the millions afflicted with lung cancer.

Examining the unit costs of COVID-19 vaccine delivery in Kenya

BackgroundVaccines are considered the path out of the COVID-19 pandemic. The government of Kenya is implementing a phased strategy to vaccinate the Kenyan population, initially targeting populations at high risk of severe disease and infection. We estimated the financial and economic unit costs of procuring and delivering the COVID-19 vaccine in Kenya across various vaccination strategies.MethodsWe used an activity-based costing approach to estimate the incremental costs of COVID-19 vaccine delivery, from a health systems perspective. Document reviews and key informant interviews(n = 12) were done to inform the activities, assumptions and the resources required. Unit prices were derived from document reviews or from market prices. Both financial and economic vaccine procurement costs per person vaccinated with 2-doses, and the vaccine delivery costs per person vaccinated with 2-doses were estimated and reported in 2021USD.ResultsThe financial costs of vaccine procurement per person vaccinated with 2-doses ranged from $2.89-$13.09 in the 30% and 100% coverage levels respectively, however, the economic cost was $17.34 across all strategies. Financial vaccine delivery costs per person vaccinated with 2-doses, ranged from $4.28-$3.29 in the 30% and 100% coverage strategies: While the economic delivery costs were two to three times higher than the financial costs. The total procurement and delivery costs per person vaccinated with 2-doses ranged from $7.34-$16.47 for the financial costs and $29.7-$24.68 for the economic costs for the 30% and 100% coverage respectively. With the exception of procurement costs, the main cost driver of financial and economic delivery costs was supply chain costs (47–59%) and advocacy, communication and social mobilization (29–35%) respectively.ConclusionThis analysis presents cost estimates that can be used to inform local policy and may further inform parameters used in cost-effectiveness models. The results could potentially be adapted and adjusted to country-specific assumptions to enhance applicability in similar low-and middle-income settings.

Solution Idea of MSMEs Based on Cluster in East Java During the Covid-19 Crisis: Can Survive or Not?

Based on history, MSMEs were able to survive the Asian economic crisis. With the COVID-19 pandemic crisis that is currently happening in the world and in the State of Indonesia, especially East Java, it is also affected. This study will explain whether MSMEs will continue to be hero in restoring the economic conditions of the East Java Region. Solutions and strategic ideas that may be carried out by East Java MSMEs in order to be able to survive on COVID-19 pandemic, one of which is a cluster based approach. Solution ideas related to the development and growth of MSMEs clusters in East Java need to be supported by innovation business based on incubation proces. Activities with incubators system for MSMEs that are still premature. Strategic ideas in the context of sustainable economic recovery due to the pandemic depend on the ability of East Java MSMEs to increase innovation. It was concluded that East Java MSMEs could implement a cluster based system to strengthen the network and supply of resources needed in the business. By forming clusters and implementing a marketing strategy expansion, geographic coverage, wide distribution and cost products efficiency strategies. So, it can be maintaining production and increasing productivity to optimization resource channels as to expand domestic and international markets.

Minimally invasive modified tunnel approach for the treatment of gingival recession: A case report

Gingival recession is a common incidence and its occurrence will increase with age. It can lead to clinical problems, reduced cosmetic appeal and therefore esthetic concern. There are numerous strategies for root coverage. The preference for improved esthetics has elevated distinctly over the years. The idea of minimal invasive approach has received significance within the latest years and is changing the open surgical approaches. The treatment of gingival recession has continually been technique sensitive along with the related patient morbidity due to the invasive nature. This article presents a report of a case treated with a minimally invasive modified tunnel approach.

Discursive Strategies for Climate Change Reporting: A Case Study of The Mercury News

ABSTRACT This paper examines how journalists use discursive strategies when covering the complex issue of climate change in The Mercury News, a large regional U.S.A. newspaper in California, a state deeply impacted by this problem. Quantitative content analysis of published texts and semi-structured interviews of journalists uncovered common use of formative discursive elements and the principles of constructive journalism, consistent with the journalists’ expressed priorities to help educate readers and make climate change interesting, relevant, and easily readable. The demands for speedy reporting in the digital environment and cuts to newsroom staff affect the use of discursive strategies for climate change coverage and limits opportunities for journalists to specialize. Journalists noted the challenge of conveying topics that are abstract, technical, and embedded with uncertainty to readers who demand definitive and instantaneous information. Such challenges are accentuated by poor connections between academic experts on climate change and the public and the press.

Service coverage and health workforce allocation strategies for geriatric and palliative care in low- and middle-income countries: A protocol for a systematic review and meta-analysis.

Background:Advances in medical science coupled with increased people's income results an elevated average of life expectancy even in the resource poor countries. The growing number of aged population, however, has drawn little attention in health system discourse of low- and Middle-Income Countries (LMICs). Nevertheless, ensuring availability of appropriate service and properly trained and skilled health workforce is an absolute necessity for a functional geriatric and palliative healthcare. Given the lack of specialist geriatricians in LMICs contexts, there are other health workforce strategies that might be effective in building a proper health system response to this growing demand. Therefore, we aimed to identify and synthesize evidence on the existing health workforce-related strategies taken to provide geriatric and palliative care in LMICs.Methods:We will follow the recommendations provided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Following the PRISMA guidelines, we will search the Medline/PubMed, Scopus, Web of Science and Cochrane database from January 2011 to December 2021 using a comprehensive search strategy. Two independent reviewers will screen the title and abstracts text using the specified inclusion and exclusion criteria. For the finally included articles, full manuscripts will be retrieved, and reviewers will appraise and extract data using standardized form independently. The third reviewer will resolve any disagreements appear in the process. The findings of the review be synthesized using the narrative synthesis approach to analyse descriptive quantitative and qualitative data. Furthermore, meta-analysis will be done provided that the data meet certain requirement as per Cochrane guideline. Rayyan software will be used to manage and synthesize data. Revman software will be used to do meta-analysis, if data support.Results:Findings of this review will be published in a peer-reviewed journal.Conclusion:This systematic review will identify the existing effective strategies taken to provide geriatric and palliative care, in LMICs.

Construction of an Innovative Development Model of Intelligent Media under the Coverage of a Wireless Sensor Network

A distributed network composed of sensor nodes with limited computing and communication capabilities is a wireless sensor network, which is a system that can autonomously and intelligently complete target tasks according to the surrounding environment. With its wide application in the fields of smart medical care, smart home, networks of vehicles, and smart media, its communication performance requirements are also increasing. According to the needs of different application scenarios, the first key problem to be solved in wireless sensor networks is what optimization coverage strategy to adopt, which will have a direct impact on the optimal allocation of very limited resources such as node energy, communication bandwidth, computing power, and other network services’ quality. Nodes adopt a probability-based joint perception model, and its algorithm is a node scheduling mechanism based on the connected dominating set to construct a tree. Each node sets the waiting time and becomes a candidate node priority according to the remaining energy and the distance from the parent node. In this paper, the issue of energy fairness is considered in heterogeneous wireless sensor networks. In order to prevent the occurrence of “energy holes,” this paper proposes a node deployment model similar to cellular networks. By deploying heterogeneous sensor nodes in this way, energy saving can be achieved. Based on this model, game theory is used to simulate the data packet transmission process between sensor nodes, an energy consumption mechanism suitable for each stage of data transmission is proposed, and Nash equilibrium is finally obtained by rationally designing the measurement function. The node deployment scheme proposed in this paper not only balances the energy consumption of the network but also prolongs the life cycle of the network. Aiming at the three-dimensional (3D) space environment, this paper studies a node deployment mechanism that guarantees connectivity and has a perceptual coverage degree of k with the help of the Reuleaux tetrahedron model. In this paper, a node deployment strategy is proposed and compared with the node deployment algorithm for 3D sensor network based on truncated octahedron. The simulation experiment results show that the wireless sensor network with artificial intelligence can not only optimize the production process of intelligent media but also improve each link of the media industry chain and further catalyze the development of new formats in the media industry. The experimental results also show that the algorithm can effectively meet the requirements of sensing coverage and connectivity coverage, the number of working nodes is small, the network life cycle is significantly prolonged, and the overall energy consumption of the network is reduced. The study results of this paper provide a reference for follow-up research on the construction of innovative development model of intelligent media under the coverage of wireless sensor network.

Study on Technical Focuses and Sampling Coverage Strategy of Airborne Software Reviews

Study on Technical Focuses and Sampling Coverage Strategy of Airborne Software Reviews

Energy-Efficient Barrier Coverage Based on Nodes Alliance for Intrusion Detection in Underwater Sensor Networks

The barrier coverage problem is generally considered for intrusion detection in underwater sensor networks (UWSNs). In conventional barrier coverage strategies in UWSNs, there is no cooperation between sensors. The information fusion is used to construct barrier coverage for higher detection probability by enhancing the sensor’s interaction capability. However, more energy is consumed for information fusion, which will shorten network lifetime. In this paper a novel high-energy-efficient barrier coverage based on nodes alliance is proposed. Based on the UWSN’s detection mode and energy consumption mode adopting nodes alliance, the relationship between the number of virtual sensors and the energy consumption is discovered. Based on this relationship, the problem of high energy efficiency is transformed into an optimization problem. By solving the optimization problem, the optimal number of physical sensors forming virtual sensors is achieved. Based on the optimal number, high detection probability and low energy consumption are taken into account simultaneously to construct barrier coverage. Both analytical and simulation studies demonstrate that the proposed strategy can provide high-energy-efficient barrier coverage.