Stitching Approach for PV Panel Detection

Ismail, Hesham; Rahmani, Abdulrahman; Aljasmi, Nawal; Quadir, Jabirul

doi:10.1109/aset48392.2020.9118386

Cited by 7 publications

(4 citation statements)

References 15 publications

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“…In the inspection area, some applications use the SIFT mosaicing approach for inspecting photovoltaic systems (PVs) using UAVs with thermal cameras to record videos using GPS for the trajectory. These images will be used to generate a high-resolution image of a PV zone by using SIFT [88]. A measurable aerial panorama based on panoramic images and multiview oblique images is proposed in [89], and it is divided into major stages: projection, matching, and back projection.…”

Section: Siftmentioning

confidence: 99%

Image Mosaicing Applied on UAVs Survey

et al. 2022

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The use of UAV (unmanned aerial vehicle) technology has allowed for advances in the area of robotics in control processes and application development. Such is the case of image processing, in which, by the use of aerial photographs taken by these aircrafts, it is possible to perform surveillance and monitoring tasks. As an example, we can mention the use of aerial photographs for the generation of panoramic images through the process of stitching images without losing image resolution. Some applications are photogrammetry and mapping, where the main problems to be solved are image alignment and ghosting images, for which different stitching techniques can be applied. These methodologies can be categorized into direct methods or feature-based methods. This paper aims to show an overview of the most frequently applied mosaicing techniques in UAVs by providing an introduction to those interested in developing in this area. For this purpose, a summary of the most applied techniques and their applications is given, showing the trend of the research field and the contribution of different countries over time.

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Section: Siftmentioning

confidence: 99%

Image Mosaicing Applied on UAVs Survey

et al. 2022

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“…Grimaccia et al [94], Aghaei et al [27] and Ismail et al [107] have proposed methods for the orthomosaicking of visual images of PV power plants using DIP techniques. Tsanakas et al [108] used the method of aerial triangulation, and Lafkih and Zaz [109] and Zefri [102,110] used the SIFT technique to perform the task.…”

Section: Orthomosaickingmentioning

confidence: 99%

Automatic Inspection of Photovoltaic Power Plants Using Aerial Infrared Thermography: A Review

2022

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In recent years, aerial infrared thermography (aIRT), as a cost-efficient inspection method, has been demonstrated to be a reliable technique for failure detection in photovoltaic (PV) systems. This method aims to quickly perform a comprehensive monitoring of PV power plants, from the commissioning phase through its entire operational lifetime. This paper provides a review of reported methods in the literature for automating different tasks of the aIRT framework for PV system inspection. The related studies were reviewed for digital image processing (DIP), classification and deep learning techniques. Most of these studies were focused on autonomous fault detection and classification of PV plants using visual, IRT and aIRT images with accuracies up to 90%. On the other hand, only a few studies explored the automation of other parts of the procedure of aIRT, such as the optimal path planning, the orthomosaicking of the acquired images and the detection of soiling over the modules. Algorithms for the detection and segmentation of PV modules achieved a maximum F1 score (harmonic mean of precision and recall) of 98.4%. The accuracy, robustness and generalization of the developed algorithms are still the main issues of these studies, especially when dealing with more classes of faults and the inspection of large-scale PV plants. Therefore, the autonomous procedure and classification task must still be explored to enhance the performance and applicability of the aIRT method.

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“…Results infer the effectiveness of aerial cleaning where the enhancement in the average power output of solar panels cleaned was around 7%. A fully autonomous UAV is utilized in [21] to fly over solar panels for complete inspections. The drone is associated with a thermal camera to collect thermal and regular video that can be postprocessed via a stitching algorithm.…”

Section: Related Studymentioning

confidence: 99%

Utilizing Artificial Intelligence and Lotus Effect in an Emerging Intelligent Drone for Persevering Solar Panel Efficiency

Almalki

Albraikan

Soufiene

et al. 2022

Wireless Communications and Mobile Computing

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Solar energy has been receiving increasing attention due to the wide range of functionality it now supports and the promise of reduced environmental pollution. However, there are a few ongoing challenges, one of which relates to regular maintenance, especially for those high roof-mounted solar panels whose efficiency might have been degraded because of dust and dirt particle deposits. This paper is aimed at developing an autonomous drone which is equipped with a camera, a GPS sensor, a transceiver, and a pump conical tank to hold water with lotus effects, for the purpose of maintenance cleaning of solar panels which have been mounted on the roof top of buildings. The proposed system considers the combination of MobileNet and VGG-16 CNN techniques together for object detection and recognition that will enable assessment of solar panels, alongside the lotus effect physical technique that will enable maintenance of the solar panels. This would also put out of danger those human lives who have previously risked carrying out such high installation inspections and maintenance. A pump tank is designed and fabricated using a 3D printer to hold water with the lotus effect and is fitted on the drone. The proposed intelligent drone has been prototyped and deployed on-site at Taif University. The experimental results confirm the ability to detect dust and dirt particle deposits on solar panels while flying autonomously before proceeding to maintain them. The cleaning process with the use of the lotus effect has led to an increase in the power efficiency of the solar panels by approximately 31%, while the accuracy of the MobileNet framework for detecting particle deposits on the solar panels and thereafter making maintenance decisions rose to approximately 99%.

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Stitching Approach for PV Panel Detection

Cited by 7 publications

References 15 publications

Image Mosaicing Applied on UAVs Survey

Image Mosaicing Applied on UAVs Survey

Automatic Inspection of Photovoltaic Power Plants Using Aerial Infrared Thermography: A Review

Utilizing Artificial Intelligence and Lotus Effect in an Emerging Intelligent Drone for Persevering Solar Panel Efficiency

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