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Article
Publication date: 18 May 2015

Oualid Araar, Nabil Aouf and Jose Luis Vallejo Dietz

This paper aims to present a new vision-based approach for both the identification and the estimation of the relative distance between the unmanned aerial vehicle (UAV) and power…

Abstract

Purpose

This paper aims to present a new vision-based approach for both the identification and the estimation of the relative distance between the unmanned aerial vehicle (UAV) and power pylon. Autonomous power line inspection using small UAVs, has been the focus of many research works over the past couple of decades. Automatic detection of power pylons is a primary requirement to achieve such autonomous systems. It is still a challenging task due to the complex geometry and cluttered background of these structures.

Design/methodology/approach

The identification solution proposed, avoids the complexity of classic object recognition techniques. Instead of searching the whole image for the pylon template, low-level geometric priors with robust colour attributes are combined to remove the pylon background. The depth estimation, on the other hand, is based on a new concept which exploits the ego-motion of the inspection UAV to estimate its distance from the pylon using just a monocular camera.

Findings

An algorithm is tested on a quadrotor UAV, using different kinds of metallic power pylons. Both simulation and real-world experiments, conducted in different backgrounds and illumination conditions, show very promising results.

Research limitations/implications

In the real tests carried out, the Inertial Navigation System (INS) of the vehicle was used to estimate its ego-motion. A more reliable solution should be considered for longer distances, by either fusing INS and global positioning system data or using visual navigation techniques such as visual odometry.

Originality/value

A simple yet efficient solution is proposed that allows the UAV to reliably identify the pylon, with still a low processing cost. Considering a monocular solution is a major advantage, given the limited payload and processing power of such small vehicles.

Details

Industrial Robot: An International Journal, vol. 42 no. 3
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 19 July 2019

Sana Bougharriou, Fayçal Hamdaoui and Abdellatif Mtibaa

This paper aims to study distance determination in vehicles, which could allow an in-car system to provide feedback and alert drivers, by either prompting the driver to take…

Abstract

Purpose

This paper aims to study distance determination in vehicles, which could allow an in-car system to provide feedback and alert drivers, by either prompting the driver to take preventative action or prepare the vehicle’s safety systems for an imminent collision. The success of a new system's deploying allows drivers to oppose the huge number of accidents and the material losses and costs associated with car accidents.

Design/methodology/approach

In this context, this paper presents estimation distance between camera and frontal vehicles based on camera calibration by combining three main steps: vanishing point extraction, lanes detection and vehicles detection in the field of 3 D real scene. This algorithm was implemented in MATLAB, and it was applied on scenes containing several vehicles in highway urban area. The method starts with the camera calibration. Then, the distance information can be calculated.

Findings

Based on experiment performance, this new method achieves robustness especially for detecting and estimating distances for multiple vehicles in a single scene. Also, this method demonstrates a higher accuracy detection rate of 0.869 in an execution time of 2.382 ms.

Originality/value

The novelty of the proposed method consists firstly on the use of an adaptive segmentation to reject the false points of interests. Secondly, the use of vanishing point has reduced the cost of using memory. Indeed, the part of the image above the vanishing point will not be processed and therefore will be deleted. The last benefit is the application of this new method on structured roads.

Details

Engineering Computations, vol. 36 no. 9
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 22 October 2020

Yongseung Han, Thomas Littlefield and Myeong Hwan Kim

This paper proposes the use of a gauge function as a measure of technical efficiency. The measure of technical inefficiency from a gauge function is desirable as the estimation of…

Abstract

Purpose

This paper proposes the use of a gauge function as a measure of technical efficiency. The measure of technical inefficiency from a gauge function is desirable as the estimation of a gauge function is not subject to the endogeneity problem under the behavioral assumption of profit maximization in the competitive market.

Design/methodology/approach

The authors address three important properties of a gauge function, i.e. linear homogeneity, monotonicity and convexity in inputs and outputs, and show how such properties are utilized in its estimation. Then, the authors apply the estimation of a gauge function to US Blacksmiths in 1850 and 1880 to show that a failure to satisfy such properties may lead to an incorrect inference on the technical efficiency.

Findings

The authors find that the Blacksmiths in the 1850s were technically more efficient than the ones in the 1880s, indicating technical regress in Blacksmithing when the properties are satisfied.

Originality/value

This paper introduces a measure of technical inefficiency from a gauge function and shows how to estimate the gauge function parametrically for the measure. The authors show McFadden's gauge function and its properties, which differ from the properties of other distance functions. The authors emphasize linear homogeneity as well as monotonicity and convexity in inputs and outputs, which must be satisfied in the estimation of a gauge function.

Details

Journal of Economic Studies, vol. 48 no. 6
Type: Research Article
ISSN: 0144-3585

Keywords

Article
Publication date: 22 June 2012

Kerri Stone and Tracy Camp

Localization is a fundamental problem in wireless sensor networks. In many applications, sensor location information is critical for data processing and meaning. While the global…

Abstract

Purpose

Localization is a fundamental problem in wireless sensor networks. In many applications, sensor location information is critical for data processing and meaning. While the global positioning system (GPS) can be used to determine mote locations with meter precision, the high hardware cost and energy requirements of GPS receivers often prohibit the ubiquitous use of GPS for location estimates. This high cost (in terms of hardware price and energy consumption) of GPS has motivated researchers to develop localization protocols that determine mote locations based on cheap hardware and localization algorithms. The purpose of this paper is to present a comprehensive review of wireless sensor network localization techniques, and provide a detailed overview for several distance‐based localization algorithms.

Design/methodology/approach

To provide a detailed summary of wireless sensor network localization algorithms, the authors outline a tiered classification system in which they first classify algorithms as distributed, distributed‐centralized, or centralized. From this broad classification, the paper then further categorizes localization algorithms using their protocol techniques. By utilizing this classification system, the authors are able to provide a survey of several wireless sensor network localization algorithms and summarize relative algorithm performance based on the algorithms' classification.

Findings

There are numerous localization algorithms available and the performance of these algorithms is dependent on network configuration, environmental variables, and the ranging method implemented. When selecting a localization algorithm, it is important to understand basic algorithm operation and expected performance. This tier‐based algorithm classification system can be used to gain a high‐level understanding of algorithm performance and energy consumption based on known algorithm characteristics.

Originality/value

Localization is a widely researched field and given the quantity of localization algorithms that currently exist, it is impossible to present a complete review of every published algorithm. Instead, the paper presents a holistic view of the current state of localization research and a detailed review of ten representative distance‐based algorithms that have diverse characteristics and methods. This review presents a new classification structure that may help researchers understand, at a high‐level, the expected performance and energy consumption of algorithms not explicitly addressed by our work.

Details

International Journal of Pervasive Computing and Communications, vol. 8 no. 2
Type: Research Article
ISSN: 1742-7371

Keywords

Article
Publication date: 5 September 2008

Yung‐Chien Shih, Yuan‐Ying Hsu, Chien‐Hung Chen, Chien‐Chao Tseng and Edwin Sha

The accuracy of sensor location estimation influences directly the quality and reliability of services provided by a wireless sensor network (WSN). However, current localization…

Abstract

Purpose

The accuracy of sensor location estimation influences directly the quality and reliability of services provided by a wireless sensor network (WSN). However, current localization methods may require additional hardware, like global positioning system (GPS), or suffer from inaccuracy like detecting radio signals. It is not proper to add extra hardware in tiny sensors, so the aim is to improve the accuracy of localization algorithms.

Design/methodology/approach

The original signal propagation‐based localization algorithm adopts a static attenuation factor model and cannot adjust its modeling parameters in accordance with the local environment. In this paper an adaptive localization algorithm for WSNs that can dynamically adjust ranging function to calculate the distance between two sensors is presented. By adjusting the ranging function dynamically, the location of a sensor node can be estimated more accurately.

Findings

The NCTUNs simulator is used to verify the accuracy and analyze the performance of the algorithm. Simulation results show that the algorithm can indeed achieve more accurate localization using just a small number of reference nodes in a WSN.

Research limitations/implications

There is a need to have accurate location information of reference nodes.

Practical implications

This is an effective low‐cost solution for the localization of sensor nodes.

Originality/value

An adaptive localization algorithm that can dynamically adjust ranging function to calculate the distance between two sensors for sensor network deployment and providing location services is described.

Details

International Journal of Pervasive Computing and Communications, vol. 4 no. 3
Type: Research Article
ISSN: 1742-7371

Keywords

Article
Publication date: 1 September 2001

Tracey Harrison‐Hill

Compares and contrasts the perceptions of travel distance held by tourists from Australia and the USA, two cultures often regarded as similar by marketers and researchers…

Abstract

Compares and contrasts the perceptions of travel distance held by tourists from Australia and the USA, two cultures often regarded as similar by marketers and researchers. Investigates the relationship of cognitive distance, actual distance and prior travel experience. Collects data from 224 US respondents and 230 Australian respondents. Reports that the US tourist has a significantly more unrealistic perception of long haul travel than Australians. Suggests that this should lead to localized strategies for such groups, especially when the results are combined with a high importance placed on travel time by the US tourists.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 13 no. 3
Type: Research Article
ISSN: 1355-5855

Keywords

Article
Publication date: 28 October 2014

Yuzhong Chen, Yang Yu and Guolong Chen

Shortest distance query between a pair of nodes in a graph is a classical problem with a wide variety of applications. Exact methods for this problem are infeasible for…

Abstract

Purpose

Shortest distance query between a pair of nodes in a graph is a classical problem with a wide variety of applications. Exact methods for this problem are infeasible for large-scale graphs such as social networks with hundreds of millions of users and links due to their high complexity of time and space. The purpose of this paper is to propose a novel landmark selection strategy which can estimate the shortest distances in large-scale graphs and clarify the efficiency and accuracy of the proposed strategy in comparison with currently used strategies.

Design/methodology/approach

Different from existing strategies, the landmark selection problem is regarded as a binary combinational optimization problem consisting of two optimization objectives and one constraint. Further, the original binary combinational optimization problem with constraints is transformed to a proper form of optimization objectives without any additional constraints and the equivalence of solutions is proved. Finally the solution of the optimization problem is performed with a modified multi-objective particle swarm optimization (MOPSO) integrating the mutation operator and crossover operator of genetic algorithm.

Findings

Four real networks of large scale are used as data sets to carry out the experiments and the experiment results show that the proposed strategy improves both of the accuracy and time efficiency to perform shortest distance estimation in large scale graph compared to other currently used strategies.

Originality/value

This paper proposes a novel landmark selection strategy which regards the landmark selection problem as a binary combinational optimization problem. The original binary combinational optimization problem with constraints is transformed to a proper form of optimization objectives without constraints and the equivalence of these two optimization problems is proved. This novel strategy also utilizes a modified MOPSO integrating the mutation operator and crossover operator of genetic algorithm.

Details

Engineering Computations, vol. 31 no. 8
Type: Research Article
ISSN: 0264-4401

Keywords

Article
Publication date: 30 August 2022

Devika E. and Saravanan A.

Intelligent prediction of node localization in wireless sensor networks (WSNs) is a major concern for researchers. The huge amount of data generated by modern sensor array systems…

51

Abstract

Purpose

Intelligent prediction of node localization in wireless sensor networks (WSNs) is a major concern for researchers. The huge amount of data generated by modern sensor array systems required computationally efficient calibration techniques. This paper aims to improve localization accuracy by identifying obstacles in the optimization process and network scenarios.

Design/methodology/approach

The proposed method is used to incorporate distance estimation between nodes and packet transmission hop counts. This estimation is used in the proposed support vector machine (SVM) to find the network path using a time difference of arrival (TDoA)-based SVM. However, if the data set is noisy, SVM is prone to poor optimization, which leads to overlapping of target classes and the pathways through TDoA. The enhanced gray wolf optimization (EGWO) technique is introduced to eliminate overlapping target classes in the SVM.

Findings

The performance and efficacy of the model using existing TDoA methodologies are analyzed. The simulation results show that the proposed TDoA-EGWO achieves a higher rate of detection efficiency of 98% and control overhead of 97.8% and a better packet delivery ratio than other traditional methods.

Originality/value

The proposed method is successful in detecting the unknown position of the sensor node with a detection rate greater than that of other methods.

Details

International Journal of Pervasive Computing and Communications, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1742-7371

Keywords

Article
Publication date: 7 April 2015

Adnan Mahmood, Hushairi Zen and Al-Khalid Othman

The paper aims to propose an optimized handover necessity estimation scheme for a mobile terminal (MT) traversing from a third-generation (3G) cellular network into the wireless…

Abstract

Purpose

The paper aims to propose an optimized handover necessity estimation scheme for a mobile terminal (MT) traversing from a third-generation (3G) cellular network into the wireless local area network (WLAN) cell for reducing the number of handover failures and unnecessary handovers.

Design/methodology/approach

The proposed optimized handover necessity estimation scheme comprises of two algorithms – a “travelling time prediction” reliant on consecutive received signal strength (RSS) measurements and MT’s velocity, and a “time threshold estimation” depending on the handover latency, WLAN’s cell radius, tolerable handover failure probability and the tolerable unnecessary handover probability.

Findings

Our performance analysis reveals that the suggested mechanism effectively minimizes the number of handover failures and unnecessary handovers by 60 per cent as compared to the already proposed schemes in the literature.

Originality/value

The convergence of Internet and wireless mobile communication accompanied by a massive increase in the number of cellular subscribers has led mobility management to emerge as a significant and challenging domain for wireless mobile communication over the Internet. Mobility management enables serving networks to locate roaming terminals for the call delivery (location management) and ensures a seamless connection as MT enters into the new service area (handover management). In this manuscript, an optimized handover necessity estimation scheme has been envisaged for reducing the probability of handover failures and unnecessary handovers from 3G cellular networks to WLANs to provide optimal network utilization along with an enhanced user satisfaction. Performance analysis reveals that the suggested scheme yields enhanced results as compared to the schemes already proposed in the literature.

Details

International Journal of Pervasive Computing and Communications, vol. 11 no. 1
Type: Research Article
ISSN: 1742-7371

Keywords

Open Access
Article
Publication date: 15 September 2021

Qun Lim, Yi Lim, Hafiz Muhammad, Dylan Wei Ming Tan and U-Xuan Tan

The purpose of this paper is to develop a proof-of-concept (POC) Forward Collision Warning (FWC) system for the motorcyclist, which determines a potential clash based on…

1332

Abstract

Purpose

The purpose of this paper is to develop a proof-of-concept (POC) Forward Collision Warning (FWC) system for the motorcyclist, which determines a potential clash based on time-to-collision and trajectory of both the detected and ego vehicle (motorcycle).

Design/methodology/approach

This comes in three approaches. First, time-to-collision value is to be calculated based on low-cost camera video input. Second, the trajectory of the detected vehicle is predicted based on video data in the 2 D pixel coordinate. Third, the trajectory of the ego vehicle is predicted via the lean direction of the motorcycle from a low-cost inertial measurement unit sensor.

Findings

This encompasses a comprehensive Advanced FWC system which is an amalgamation of the three approaches mentioned above. First, to predict time-to-collision, nested Kalman filter and vehicle detection is used to convert image pixel matrix to relative distance, velocity and time-to-collision data. Next, for trajectory prediction of detected vehicles, a few algorithms were compared, and it was found that long short-term memory performs the best on the data set. The last finding is that to determine the leaning direction of the ego vehicle, it is better to use lean angle measurement compared to riding pattern classification.

Originality/value

The value of this paper is that it provides a POC FWC system that considers time-to-collision and trajectory of both detected and ego vehicle (motorcycle).

Details

Journal of Intelligent and Connected Vehicles, vol. 4 no. 3
Type: Research Article
ISSN: 2399-9802

Keywords

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