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About 10,000 papers for “coverage area”

Sensor Area Coverage

Hai Liu, Amiya Nayak, Ivan Stojmenović · 2010

This chapter contains sections titled: Problems, Models, and Assumptions Coverage and Connectivity Criteria Area-Dominating Set Based Sensor Area Coverage Algorithm Asynchronous Sensor Area Coverage Synchronous Sensor Area Coverage Multicoverage By Sensors Physical Layer-Based Sensing, Protocols, and Case Studies Operation Range Assignment in WSANs References ]]>

Cited by 1

Accuracy compared to area coverage.

Jia Li (160557), Alice C. Hughes (839224), David Dudgeon (2923374) · Figshare · 2019

<p>MaxEnt modelled ranges are more restricted (6.6% of the EAAF) but with high accuracy (average 95%), whereas BirdLife designates a much larger area as suitable (up to 60% of the region and with a mean of 21.1%) but has a much lower accuracy (76.5% on average, but as low as 2%).</p>

Cited by 0Open access

Coverage area vs. beam divergence.

Meriem Salhi (21601246), Maha Sliti (21601249), Noureddine Boudriga (21601252) et al. · Figshare · 2025

<div> Identifying unmanned aerial vehicles (UAVs) is critical to protecting vital locations and infrastructures from potential attacks. The literature suggests a variety of detection methods, including conventional radar systems, acoustic detection, radio frequency signal detection, LiDAR, and camera-based techniques. LiDAR systems, in particular, offer high-resolution 3D mapping and precise distance measurements, which prove to be highly effective for detecting and tracking UAVs under various environmental conditions. This study presents two innovative LiDAR systems for UAV detection: a multi-array static LiDAR system and a one-array rotating LiDAR system. The multi-array static LiDAR employs arrays of laser light sources and concentrators arranged along a spherical shape. A central photodiode receives the transmittance of the reflected optical energy captured by the concentrators, enabling the precise identification of UAVs. The system’s design focuses on achieving continuous, high-resolution coverage with minimal delay, making it suitable for monitoring wide areas. In contrast, the one-array rotating LiDAR utilizes a single array with rotational motion to scan the surveillance area. This approach prioritizes compactness and energy efficiency, which makes it advantageous for cost-sensitive applications. However, the rotational mechanism introduces trade-offs, such as increased mechanical wear and scanning latency. By conducting a comprehensive analysis of the design characteristics, this study evaluates the practicability and efficiency of these LiDAR solutions. Parameters such as the dimensions of the monitored region, sensor characteristics, component arrangement, and interspacing are considered to assess the effectiveness of both systems in identifying potential UAV threats. </div>

Cited by 0Open access

VillageLink: Wide-Area Wireless Coverage

2015

Abstract—White spaces promise to revolutionize the way wire-less connectivity is delivered over wide areas. However, large-scale white space networks face the problem of allocating channels to multiple contending users in the wide white space band. To tackle the issue, we first examine wireless propagation in a long-distance outdoor white space testbed and find that a complex combination of free-space loss and antenna effects impacts transmission in white spaces. Thus, a need arises for a strategy that goes beyond simple channel utilization balancing, and uses frequency probing to profile channels according to their propagation properties. We devise VillageLink, a Gibbs sampling-based method that optimizes channel allocation in a distributed manner with a minimum number of channel switching events. Through exten-sive simulations we demonstrate that VillageLink results in a significant capacity improvement over alternative solutions. I.

Cited by 0

On Multi-Robot Area Coverage

Alireza Davoodi, Pooyan Fazli, Alan K. Mackworth · 2013

This paper presents an approach allowing a team of robots each with limited visibility to cover an area in the presence of different types of static obstacles. We introduce Reduced-CDT, an environment representation method based on Constrained Delaunay Triangulation. A new graph segmentation method called Multi-Prim’s is used to decompose the Reduced-CDT and construct a forest of partial spanning trees (PSTs). Each PST is then modified through a mechanism called the Constrained Spanning Tour (CST) to build a cycle which is assigned to an explorer robot. Subsequently, robots start navigating the cycles and consequently cover the whole area. The proposed approach is guaranteed to be complete and robust. 1.

Cited by 13

Prajitkk1/Swarm-Area-Coverage: v1.0

Prajit, Krisshna Kumar · Zenodo (CERN European Organization for Nuclear Research) · 2024

This project implements a comprehensive robot path planning system for efficiently covering a polygonal area while avoiding no-go zones. The system partitions the operational area, accounts for predefined obstacles, and determines the shortest path through valid cells using a nearest neighbor algorithm. It is designed for multi UAV path planning.

Cited by 0Open access

Robot Formations for Area Coverage

Jürgen Leitner · SUPSI ARIS · 2009

Abstract. Two algorithms for area coverage (for use in space applications) were evaluated using a simulator and then tested on a multi-robot society consisting of LEGO Mindstorms robots. The two algorithms are (i) a vector force based implementation and (ii) a machine learning approach. The second is based on an organizational-learning oriented classifier system (OCS) introduced by Takadama in 1998. 1

Cited by 0Open access

Case Study 6: Area Coverage

R. Russell Rhinehart · ASME Press eBooks · 2018

Consider a square parking lot. Where should one place overhead street lamps to provide light to best cover the area? Or overhead cameras to best monitor the area. If there are five devices, the location pattern could be a pentagon, or that of the five patterns on a die.

Cited by 0

Prajitkk1/Swarm-Area-Coverage: v1.0

Prajit, Krisshna Kumar · Zenodo (CERN European Organization for Nuclear Research) · 2024

This project implements a comprehensive robot path planning system for efficiently covering a polygonal area while avoiding no-go zones. The system partitions the operational area, accounts for predefined obstacles, and determines the shortest path through valid cells using a nearest neighbor algorithm. It is designed for multi UAV path planning.

Cited by 0Open access

The Maximum Coverage Set Calculated Algorithm for WSN Area Coverage

Xin He, Hua Yang, Xiaolin Gui · Journal of Networks · 2010

The Coverage Control Technology is one of the basic technologies of wireless sensor network, and is mainly concerned about how to prolong the network lifetime on the basis of meeting users’ perception demand. Among this, in the study of area coverage, the set K-cover algorithm is broadly accepted because that it can prolong network lifetime rather well. However, maximum set covers problem is proved to be NP-Complete. At the same time, the existing set K-cover algorithms are centralized, and can not adapt to the large-scale sensor network applications and expansion. So, how to get the maximum coverage set number and realize node set division by distribut ed algorithm is becoming the problem of people attention. Thus, this paper firstly utilizes node minimum layer overlapping subfield to find out area minimum coverage value, as the upper limit of coverage node set’s number. On the basis of this maximum, it put forward to way of dividing node set. Secondly, the maximum coverage set number calculated algorithm is proposed. Simulation result shows the distributed algorithm MCNCA is very effective.

Cited by 8

Coverage Contribution Area Based $k$ -Coverage for Wireless Sensor Networks

Jiguo Yu, Shengli Wan, Xiuzhen Cheng et al. · IEEE Transactions on Vehicular Technology · 2017

Coverage is a primary metric for ensuring the quality of services provided by a wireless sensor network (WSN). In this paper, we focus on the k-coverage problem, which requires a selection of a minimum subset of nodes among the deployed ones such that each point in the target region is covered by at least k nodes. We present both centralized and distributed protocols to tackle this fundamental problem. Our protocols are based on a novel concept of Coverage Contribution Area, which helps to get a lower sensor spatial density. Furthermore, our protocols take the residual energies of the sensors into consideration. This consideration combined with the low sensor spatial density ensures that our protocols can prolong the network lifetime to a greater extent, which is crucial to WSNs due to the limited energy supply and the difficulties of energy recharging. We also conduct extensive simulations to verify our proposed algorithms, and the results show that they are superior over existing ones.

Cited by 128