Evaluation of Drones for Inspection and Control in Industry 4.0

Moreno-Jacobo, Diego; Toledo-Nin, Gustavo; Ochoa-Zezzatti, Alberto; Argüelles, Vianey Torres; Estrada-Otero, Fernando

doi:10.1007/978-3-030-68655-0_29

Cited by 10 publications

(5 citation statements)

References 3 publications

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“…Using AI‐enabled drone systems for process audits helps organizations perform safe and secure auditing in unfavorable conditions such as high temperatures and pressure. Further, drones are comparably affordable, and hence, organizations receive conditional values in AI‐enabled drones for process audits (Moreno‐Jacobo et al, 2021). Qualitative study findings also suggest that the conditional value is important for AI‐enabled drone adoption.…”

Section: Findings Of Qualitative Study and Hypotheses Developmentmentioning

confidence: 99%

“…Regular audits help organizations identify and address issues promptly, fostering a culture of continuous improvement in the production environment. The AI‐enabled drone is one of the innovative technologies B2B manufacturing organizations use to evaluate the worksite's production process (Moreno‐Jacobo et al, 2021; Ogbeibu et al, 2023). The drones audit sites, inspect and examine machines, analyze damage and leakage, and repair and scan transmission lines at worksites (Rojas Viloria et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

“…The wider popularity of AI‐enabled drone and their emergence into business activities have triggered a surge in the development and use in business‐to‐business (B2B) settings (Hahn, 2020; Javaid et al, 2021; Kumar et al, 2023; Kumari & Kumar, 2023; Moreno‐Jacobo et al, 2021; Ogbeibu et al, 2021; Pereira et al, 2023; Shankar et al, 2024). Drones play a crucial role in the Industry 4.0 revolution; hence, B2B organizations have started exercising drone‐enabled tasks (Iazzi et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Exploring enablers and inhibitors of AI‐enabled drones for manufacturing process audits: A mixed‐method approach

Shankar,

Behl,

Pereira

et al. 2024

Bus Strat Env

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The objective of this study is to explore the enablers and inhibitors of AI‐enabled drone adoption for manufacturing process audit using a mixed‐method design. A qualitative study was performed to explore the enablers and inhibitors. Further, based on the findings of the qualitative studies, a framework was proposed, and proposed hypotheses were examined using a survey‐based study. The results indicated that function, environmental, and epistemic values are major enablers, whereas vulnerability and sunk cost barriers are major inhibitors to adoption intention. The initial trust and inertia were crucial mediators, and organizations' technological innovativeness played a crucial moderating role. This study enriches the literature on technological adoption for sustainability and helps audit service providers design strategies to enhance AI‐enabled drone adoption for process audits.

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Section: Findings Of Qualitative Study and Hypotheses Developmentmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Exploring enablers and inhibitors of AI‐enabled drones for manufacturing process audits: A mixed‐method approach

Shankar,

Behl,

Pereira

et al. 2024

Bus Strat Env

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“…According to Mazur et al [53], the estimated potential market value for drones in the infrastructure sector is 45.2 billion dollars. There are many uses for drones in infrastructure including inspection of power lines [54], [55], pipelines [56], [57], vertical structures [58], [59], damns [60], bridges [61], railways [62], and other areas. Drones can also be used for photogrammetry [63], sensing, and data collection [64].…”

Section: Current and Future Market Opportunitiesmentioning

confidence: 99%

Unmanned Aerial Vehicle Communications for Civil Applications: A Review

et al. 2022

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The use of drones, formally known as unmanned aerial vehicles (UAVs), has significantly increased across a variety of applications over the past few years. This is due to the rapid advancement towards the design and production of inexpensive and dependable UAVs and the growing request for the utilization of such platforms particularly in civil applications. With their intrinsic attributes such as high mobility, rapid deployment and flexible altitude, UAVs have the potential to be utilized in many wireless system applications. On the one hand, UAVs are able to operate as flying mobile terminals within wireless/cellular networks to support a variety of missions such as goods delivery, search and rescue, precision agriculture monitoring, and remote sensing. On the other hand, UAVs can be utilized as aerial base stations to increase wireless communication coverage, reliability, and the capacity of wireless systems without additional investment in wireless systems infrastructure. The aim of this article is to review the current applications of UAVs for civil and commercial purposes. The focus of this paper is on the challenges and communication requirements associated with UAV-based communication systems. This article initially classifies UAVs in terms of various parameters, some of which can impact UAVs' communication performance. It then provides an overview of aerial networking and investigates UAVs routing protocols specifically, which are considered as one of the challenges in UAV communication. This article later investigates the use of UAV networks in a variety of civil applications and considers many challenges and communication demands of these applications. Subsequently, different types of simulation platforms are investigated from a communication and networking viewpoint. Finally, it identifies areas of future research.

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“…Drones a.k.a. unmanned aerial vehicles (UAVs) are widely used agile platforms for inspection purposes (Nooralishahi et al 2022;Maboudi et al 2021;Moreno-Jacobo et al 2021;Savino and Tondolo 2023). Their integration with various systems enhances sustainability and practical applications, especially in construction and infrastructure.…”

Section: Introductionmentioning

confidence: 99%

Automatic non-destructive UAV-based structural health monitoring of steel container cranes

De Arriba López,

Maboudi,

Achanccaray

et al. 2023

Appl Geomat

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Container cranes are of key importance for maritime cargo transportation. The uninterrupted and all-day operation of these container cranes, which directly affects the efficiency of the port, necessitates the continuous inspection of these massive hoisting steel structures. Due to the large size of cranes, the current manual inspections performed by expert climbers are costly, risky, and time-consuming. This motivates further investigations on automated non-destructive approaches for the remote inspection of fatigue-prone parts of cranes. In this paper, we investigate the effectiveness of color space-based and deep learning-based approaches for separating the foreground crane parts from the whole image. Subsequently, three different ML-based algorithms (k-Nearest Neighbors, Random Forest, and Naive Bayes) are employed to detect the rust and repainting areas from detected foreground parts of the crane body. Qualitative and quantitative comparisons of the results of these approaches were conducted. While quantitative evaluation of pixel-based analysis reveals the superiority of the k-Nearest Neighbors algorithm in our experiments, the potential of Random Forest and Naive Bayes for region-based analysis of the defect is highlighted.

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Evaluation of Drones for Inspection and Control in Industry 4.0

Cited by 10 publications

References 3 publications

Exploring enablers and inhibitors of AI‐enabled drones for manufacturing process audits: A mixed‐method approach

Exploring enablers and inhibitors of AI‐enabled drones for manufacturing process audits: A mixed‐method approach

Unmanned Aerial Vehicle Communications for Civil Applications: A Review

Automatic non-destructive UAV-based structural health monitoring of steel container cranes

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