Eyes in the Sky: Drones Applications in the Built Environment under Climate Change Challenges

Drones, Journal Year: 2023, Volume and Issue: 7(10), P. 637 - 637

Published: Oct. 16, 2023

This paper reviews the diverse applications of drone technologies in built environment and their role climate change research. Drones, or unmanned aerial vehicles (UAVs), have emerged as valuable tools for environmental scientists, offering new possibilities data collection, monitoring, analysis urban environment. The begins by providing an overview different types drones used environment, including quadcopters, fixed-wing drones, hybrid models. It explores capabilities features, such high-resolution cameras, LiDAR sensors, thermal imaging, which enable detailed acquisition studying impacts areas. then examines specific contribution to These include mapping heat islands, assessing energy efficiency buildings, monitoring air quality, identifying sources greenhouse gas emissions. UAVs researchers collect spatially temporally rich data, allowing a trends patterns. Furthermore, discusses integrating with artificial intelligence (AI) derive insights develop predictive models mitigation adaptation environments. Finally, addresses technologies’ challenges future directions encompass regulatory frameworks, privacy concerns, management, need interdisciplinary collaboration. By harnessing potential scientists can enhance understanding areas contribute developing sustainable strategies resilient cities.

Language: Английский

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Object detection and tracking in Precision Farming: a systematic review

Computers and Electronics in Agriculture, Journal Year: 2024, Volume and Issue: 219, P. 108757 - 108757

Published: Feb. 23, 2024

Object Detection and Tracking have gained importance in recent years because of the great advances image video analysis techniques accurate results these technologies are producing. Moreover, they successfully been applied to multiple fields, including agricultural domain since offer real-time monitoring status crops animals while counting how many present within a field/barn. This review aims current literature on field Precision Farming. For that, over 300 research articles were explored, from which 150 last five systematically reviewed analysed regarding algorithms implemented, belong to, difficulties faced, limitations should be tackled future. Lastly, it examines potential issues that this approach might have, for instance, lack open-source datasets with labelled data. The findings study indicate critical enhance Farming pave way robotization sector provide insights crop animal management, optimize resource allocation. Future work focus optimal acquisition prior Tracking, along consideration biophysical environment farming scenarios.

Language: Английский

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Mask YOLOv7-Based Drone Vision System for Automated Cattle Detection and Counting

Artificial Intelligence and Applications, Journal Year: 2024, Volume and Issue: unknown

Published: Jan. 17, 2024

Conventional method of counting animals is one the most challenging tasks in livestock management; moreover, drone-acquired imagery, though promising, more intelligent management. In this paper, we apply state-of-the-art object detection model, Mask YOLOv7, for and cattle different scenarios such as controlled (feedlot) environment uncontrolled (open-range) environment. mechanism was embedded into backbone YOLOv7 algorithm (Mask YOLOv7) instance segmentation individual object. We evaluate performance model proposed study using Intersection over Union threshold 0.5, average precision (AP), mean precision. The results experiment conducted show that achieves an accuracy 93% 95% These affirm potential to perform competitively with any other existing models terms AP especially when speed matters. Moreover, research has applications inventory, which helps tracking, monitoring, reporting vital information about cattle.

Language: Английский

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AI and Related Technologies in the Fields of Smart Agriculture: A Review

Information, Journal Year: 2025, Volume and Issue: 16(2), P. 100 - 100

Published: Feb. 2, 2025

The integration of cutting-edge technologies—such as the Internet Things (IoT), artificial intelligence (AI), machine learning (ML), and various emerging technologies—is revolutionizing agricultural practices, enhancing productivity, sustainability, efficiency. objective this study is to review literature regarding development evolution AI well other technologies in fields Agriculture they are developed transformed by integrating above technologies. areas examined open field smart farming, vertical indoor zero waste agriculture, precision livestock greenhouses, regenerative agriculture. This paper links current research, technological innovations, case studies present a comprehensive these being context for benefit farmers consumers general. By exploring practical applications future perspectives, work aims provide valuable insights address global food security challenges, minimize environmental impacts, support sustainable goals through application new

Language: Английский

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Towards evaluation of the PID criteria based UAVs observation and tracking head within resizable selection by COA algorithm

Results in Control and Optimization, Journal Year: 2023, Volume and Issue: 12, P. 100279 - 100279

Published: Aug. 23, 2023

The study of unmanned systems has garnered significant academic attention worldwide. advancements in tracking technologies, particularly the aerial vehicle (UAV) developed by US Air Force, have motivated scientists to extensively explore this field due abundance available resources. However, UAV's effectiveness motion is influenced its three fundamental motions: pitch, roll, and yaw. To address this, been developing optimization algorithms models enhance performance. Nonetheless, practical scenarios, each requires specific measurements, their relative importance varies. This presents several challenges, including existence multiple criteria for selecting values, determining criteria's significance, evaluating trade-offs between performance across different cases. Consequently, selection evaluation UAV control becomes complex. proposes a novel process that employs cuckoo algorithm (COA) real measured resizable margins goal detection instead traditional fixed-size criteria. framework consists enhancing PID gains using COA algorithm, focusing on altitude attitude functional controllers. results demonstrate significance various motions. Rigorous analysis were conducted validate proposed research framework.

Language: Английский

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Harm to Nonhuman Animals from AI: a Systematic Account and Framework

Philosophy & Technology, Journal Year: 2023, Volume and Issue: 36(2)

Published: April 6, 2023

Abstract This paper provides a systematic account of how artificial intelligence (AI) technologies could harm nonhuman animals and explains why animal harms, often neglected in AI ethics, should be better recognised. After giving reasons for caring about outlining the nature harm, interests, wellbeing, develops comprehensive ‘harms framework’ which draws on scientist David Fraser’s influential mapping human activities that impact sentient animals. The harms framework is fleshed out with examples inspired by both scholarly literature media reports. help inform ethical analyses AI’s serve as clear basis development regulation to prevent mitigate nonhumans.

Language: Английский

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Detection and monitoring wheat diseases using unmanned aerial vehicles (UAVs)

Computers and Electronics in Agriculture, Journal Year: 2024, Volume and Issue: 224, P. 109158 - 109158

Published: June 16, 2024

Language: Английский

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A Survey on Applications of Unmanned Aerial Vehicles Using Machine Learning

IEEE Access, Journal Year: 2023, Volume and Issue: 11, P. 117582 - 117621

Published: Jan. 1, 2023

Unmanned Aerial Vehicles (UAVs) play an important role in many applications, including health, transport, telecommunications and safe rescue operations. Their adoption can improve the speed precision of applications when compared to traditional solutions based on handwork. The use UAVs brings scientific technological challenges. In this context, Machine Learning (ML) techniques provide several problems concerning civil military applications. An increasing number papers ML context have been published academic journals. work, we present a literature review UAVs, outlining most recurrent areas commonly used UAV results reveal that environment, communication security are among main research topics.

Language: Английский

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Blockchain and NFT-based traceability and certification for UAV parts in manufacturing

Journal of Industrial Information Integration, Journal Year: 2024, Volume and Issue: 39, P. 100597 - 100597

Published: March 11, 2024

Language: Английский

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Livestock detection in African rangelands: Potential of high-resolution remote sensing data

Remote Sensing Applications Society and Environment, Journal Year: 2024, Volume and Issue: 33, P. 101139 - 101139

Published: Jan. 1, 2024

Livestock production is vital in eradicating poverty, malnutrition, and attainment of the Sustainable Development Goals (SDG) developing regions such as Africa. The livestock sector Africa contributes 10%–44% gross domestic product more than 70% greenhouse gas emissions continent. With anticipated increase demand for products, need to mitigate climate change, lack accurate census data, innovative remote sensing technologies methods become crucial sector. In this paper, we present a review current technological advancements detection algorithms censuses, identifying weaknesses sensors methods, highlighting issues that currently limit adoption these African countries. We observed last four years (2019–2022) accounted 69% all studies. This surge was driven by development Unmanned Aerial Vehicles, which offer high resolution images flexibility detection. addition, use automated are fast, efficient accurate. However, surrounding background different species, herd size spatial datasets affects accuracy. suggest publicly accessible aerial labelled databases covering various breeds develop customized models heterogeneous landscapes rangelands. Efficient monitoring population trends environmental impacts grazing practises.

Language: Английский

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