Versatile Multipurpose Crashproof UAV: Machine Learning and IoT approach

Dave, Meha; Patel, Roshani; Joshi, Ishwariy; Goradiya, Bhargav

doi:10.1109/incet49848.2020.9154141

Cited by 3 publications

(5 citation statements)

References 13 publications

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“…Actual technology completed and qualified through test and demonstration [48], [61] tionally, as mentioned before, the performance comparison of different backhaul connectivity technologies in the LoRa network can be explored by the researchers, as the study regarding this scope has not yet been reported.…”

Section: Discussionmentioning

confidence: 99%

“…The LoRa module was already equipped with a board, so no additional board was required. Other hardware employed by other researchers can be observed in Table6[47],[48],[55]-[61].This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ This article has been accepted for publication in a future issue of this journal, but has not been fully edited.…”

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confidence: 99%

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A Systematic Review of Real-Time Deployments of UAV-Based LoRa Communication Network

2021

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The term Internet of Things (IoT) has emerged in recent decades because this network revolutionizes almost every aspect of our daily life, including products such as smartphones and intelligent vehicles, and crucial tasks such as precision agriculture and environmental monitoring. Myriads of communication technologies have been developed to fulfill the two main features of the IoT: long-range transmissions and low power consumption. Long-range (LoRa) has become one of the vital parts of IoT communication. In this study, the real-time deployments of an unmanned aerial vehicle (UAV)-based LoRa communication network are systematically reviewed, with a focus on the communication setup and its reported performance. Importantly, the UAV-based LoRa communication network has a low bit rate connectivity to ensure the high reliability of connections, especially in applications that require long transmission ranges. This study provides recommendations for researchers on what research perspectives need to be explored when implementing UAVs for IoT-based LoRa communication. This study also describes publication trends related to UAV-based LoRa communication networks. A supplementary Excel file that contains the reported publications on UAV-based LoRa communication networks is included to show this publication trend.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

A Systematic Review of Real-Time Deployments of UAV-Based LoRa Communication Network

2021

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“…3D‐printed cages are usually designed for specific inspection purposes or inprior environments (Shahmoradi et al, 2021; Edgerton et al, 2019). Özaslan et al (2015) and Dave et al (2020) developed drones with LiDAR and customized cages for collision‐tolerate flight. Shahmoradi et al (2020) used an encased drone to inspect in prior mines.…”

Section: Path Planning For Uav Inspectionmentioning

confidence: 99%

Unmanned aerial vehicle navigation in underground structure inspection: A review

Zhang,

Hao,

Zhang

et al. 2023

Geological Journal

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Many years after construction, a number of existing old tunnels and underground structures are deteriorating with time as evidenced by cracks, large deformations, water leakage and so forth, which usually require regular site inspections to record their structural deterioration by taking high‐pixel, high‐overlap images along miles of a tunnel network. For complex underground structures (e.g., long tunnels and large caves), unmanned aerial vehicles (UAVs) may be adaptive in acquiring images at multiple heights and angles with low operational costs. So far, UAV underground structural health monitoring has become mature for open‐air surveying with rapid developments in robotic software and hardware. However, the UAV image acquisition for underground working conditions still faces a number of key challenges. This paper aims to provide an overview of UAV navigation techniques in confined dark spaces for geotechnical engineers, geologists, drone developers and other interdisciplinary researchers & professionals in the structural health monitoring field. It specifies the challenges for UAV application in underground space, mainly including lack of Global Navigation Satellite System (GNSS) signals, poor lighting conditions, weak features and obstacle avoidance and then followed by strategic solutions. For example, in light of poor GNSS signals, the fusion of multi‐sensors (e.g., laser imaging, detection and ranging (LiDAR) and multi‐cameras) can enhance localization accuracy in low‐luminance underground conditions. To address obstacle avoidance, computer vision (CV)‐based navigation algorithms (e.g., deep reinforced learning [DRL]) enable effective navigation in complex 3D spaces, but their adaptability is limited by arithmetic power and pre‐training needs. The review of relevant previous studies concludes that further development for UAVs in underground space inspection may focus on operation in large‐scale geometric inspection environments, obstacle avoidance, features and semantic recognition.

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“…Not only does it contain much of the technical and theoretical information about its bit rate, spreading factor, transmission power, coding rate, bandwidth, and carrier frequencies around the world, but a plethora of papers showing UAV-based modules and UAV-based gateways are also evident within the survey. Some of the most interesting are [5], which focuses on the detection of gas leakages with air and humidity sensors, with a camera feed enhanced via machine learning; [6] in which a wireless sensor network is proposed for marine environmental monitoring, with compelling real-life results; and [7], a study on adaptable usage between LoRa and Wi-Fi for high-data management in agricultural applications.…”

Section: Related Workmentioning

confidence: 99%

“…The model conveys both line-of-sight (LoS) and non-line-of-sight (NLoS) losses and is represented in Equations ( 3) and (4), and the probability of having a LoS connection for an elevation angle of θ is given by (5). Hence, the average path loss between LoS and NLoS situations is described as:…”

Section: Classical Propagation Model For Uav Base Stationsmentioning

confidence: 99%

Intelligent Drone Positioning via BIC Optimization for Maximizing LPWAN Coverage and Capacity in Suburban Amazon Environments

Ferreira

Neto

Barros

et al. 2023

Sensors

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This paper aims to provide a metaheuristic approach to drone array optimization applied to coverage area maximization of wireless communication systems, with unmanned aerial vehicle (UAV) base stations, in the context of suburban, lightly to densely wooded environments present in cities of the Amazon region. For this purpose, a low-power wireless area network (LPWAN) was analyzed and applied. LPWAN are systems designed to work with low data rates but keep, or even enhance, the extensive area coverage provided by high-powered networks. The type of LPWAN chosen is LoRa, which operates at an unlicensed spectrum of 915 MHz and requires users to connect to gateways in order to relay information to a central server; in this case, each drone in the array has a LoRa module installed to serve as a non-fixated gateway. In order to classify and optimize the best positioning for the UAVs in the array, three concomitant bioinspired computing (BIC) methods were chosen: cuckoo search (CS), flower pollination algorithm (FPA), and genetic algorithm (GA). Positioning optimization results are then simulated and presented via MATLAB for a high-range IoT-LoRa network. An empirically adjusted propagation model with measurements carried out on a university campus was developed to obtain a propagation model in forested environments for LoRa spreading factors (SF) of 8, 9, 10, and 11. Finally, a comparison was drawn between drone positioning simulation results for a theoretical propagation model for UAVs and the model found by the measurements.

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Versatile Multipurpose Crashproof UAV: Machine Learning and IoT approach

Cited by 3 publications

References 13 publications

A Systematic Review of Real-Time Deployments of UAV-Based LoRa Communication Network

A Systematic Review of Real-Time Deployments of UAV-Based LoRa Communication Network

Unmanned aerial vehicle navigation in underground structure inspection: A review

Intelligent Drone Positioning via BIC Optimization for Maximizing LPWAN Coverage and Capacity in Suburban Amazon Environments

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