Geometric Feature Characterization of Apple Trees from 3D LiDAR Point Cloud Data DOI Creative Commons
Md Rejaul Karim, Shahriar Ahmed, Md Nasim Reza

et al.

Journal of Imaging, Journal Year: 2024, Volume and Issue: 11(1), P. 5 - 5

Published: Dec. 31, 2024

The geometric feature characterization of fruit trees plays a role in effective management orchards. LiDAR (light detection and ranging) technology for object enables the rapid precise evaluation features. This study aimed to quantify height, canopy volume, tree spacing, row spacing an apple orchard using three-dimensional (3D) sensor. A sensor was used collect 3D point cloud data from orchard. Six samples trees, representing variety shapes sizes, were selected collection validation. Commercial software python programming language utilized process collected data. processing steps involved conversion, radius outlier removal, voxel grid downsampling, denoising through filtering erroneous points, segmentation region interest (ROI), clustering density-based spatial (DBSCAN) algorithm, transformation, removal ground points. Accuracy assessed by comparing estimated outputs with corresponding measured values. sensor-estimated heights 3.05 ± 0.34 m 3.13 0.33 m, respectively, mean absolute error (MAE) 0.08 root squared (RMSE) 0.09 linear coefficient determination (r2) 0.98, confidence interval (CI) −0.14 −0.02 high concordance correlation (CCC) 0.96, indicating strong agreement accuracy. volumes 13.76 2.46 m3 14.09 2.10 m3, MAE 0.57 RMSE 0.61 r2 value 0.97, CI −0.92 0.26, demonstrating precision. For distances 3.04 0.17 3.18 0.24 3.35 3.40 0.05 values 0.12 0.92 0.07 0.94 respectively. −0.18 0.01, −0.1, 0.002 Although minor differences observed, estimates efficient, though specific measurements require further refinement. results are based on limited dataset six values, providing initial insights into performance. However, larger would offer more reliable accuracy assessment. small sample size (six trees) limits generalizability findings necessitates caution interpreting results. Future studies should incorporate broader diverse validate refine characterization, enhancing practices

Language: Английский

Drones in Precision Agriculture: A Comprehensive Review of Applications, Technologies, and Challenges DOI Creative Commons

Ridha Guebsi,

Sonia Mami,

Karem Chokmani

et al.

Drones, Journal Year: 2024, Volume and Issue: 8(11), P. 686 - 686

Published: Nov. 19, 2024

In the face of growing challenges in modern agriculture, such as climate change, sustainable resource management, and food security, drones are emerging essential tools for transforming precision agriculture. This systematic review, based on an in-depth analysis recent scientific literature (2020–2024), provides a comprehensive synthesis current drone applications agricultural sector, primarily focusing studies from this period while including few notable exceptions particular interest. Our study examines detail technological advancements systems, innovative aerial platforms, cutting-edge multispectral hyperspectral sensors, advanced navigation communication systems. We analyze diagnostic applications, crop monitoring mapping, well interventional like spraying drone-assisted seeding. The integration artificial intelligence IoTs analyzing drone-collected data is highlighted, demonstrating significant improvements early disease detection, yield estimation, irrigation management. Specific case illustrate effectiveness various crops, viticulture to cereal cultivation. Despite these advancements, we identify several obstacles widespread adoption, regulatory, technological, socio-economic challenges. particularly emphasizes need harmonize regulations beyond visual line sight (BVLOS) flights improve economic accessibility small-scale farmers. review also identifies key opportunities future research, use swarms, improved energy autonomy, development more sophisticated decision-support systems integrating data. conclusion, underscore transformative potential technology sustainable, productive, resilient agriculture global 21st century, highlighting integrated approach combining innovation, adapted policies, farmer training.

Language: Английский

Citations

15
Estimating Subcanopy Solar Radiation Using Point Clouds and GIS-Based Solar Radiation Models DOI Creative Commons

Daniela Buchalová,

Jaroslav Hofierka, Jozef Šupinský

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(2), P. 328 - 328

Published: Jan. 18, 2025

This study explores advanced methodologies for estimating subcanopy solar radiation using LiDAR (Light Detection and Ranging)-derived point clouds GIS (Geographic Information System)-based models, with a focus on evaluating the impact of different data types model performance. The research compares performance two modeling approaches—r.sun Point Cloud Solar Radiation Tool (PCSRT)—in capturing dynamics beneath tree canopies. models were applied to contrasting environments: forested area built-up area. r.sun model, based raster data, PCSRT which uses voxelized clouds, evaluated their accuracy efficiency in simulating radiation. Data collected terrestrial laser scanning (TLS), unmanned (ULS), aerial (ALS) capture structural complexity Results indicate that choice significantly affects outputs. PCSRT, its voxel-based approach, provides higher precision heterogeneous forest environments. Among types, ULS provided most accurate estimates, closely matching situ pyranometer measurements, due high-resolution coverage canopy structures. TLS offered detailed local but was limited spatial extent, while ALS, despite broader coverage, showed lower insufficient density under dense These findings underscore importance selecting appropriate radiation, particularly complex

Language: Английский

Citations

0
Smart Glove: A Cost-Effective and Intuitive Interface for Advanced Drone Control DOI Creative Commons
C. Randieri,

Andrea Pollina,

Adriano Puglisi

et al.

Drones, Journal Year: 2025, Volume and Issue: 9(2), P. 109 - 109

Published: Feb. 1, 2025

Recent years have witnessed the development of human-unmanned aerial vehicle (UAV) interfaces to meet growing demand for intuitive and efficient solutions in UAV piloting. In this paper, we propose a novel Smart Glove v 1.0 prototype advanced drone gesture control, leveraging key low-cost components such as Arduino Nano process data, MPU6050 detect hand movements, flexible sensors easy throttle nRF24L01 module wireless communication. The proposed research highlights design methodology reporting flight tests associated with simulation findings demonstrate characteristics v1.0 terms intuitive, responsive, hands-free piloting interface. We aim make experience more enjoyable leverage ergonomics by adapting pilot’s preferred position. overall project points seedbed future solutions, eventually extending its applications medicine, space, metaverse.

Language: Английский

Citations

0
TIA Design for FMCW LiDAR Systems DOI Creative Commons
Amin Chegeni, Johannes Sturm

International Journal of Circuit Theory and Applications, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 6, 2025

ABSTRACT This paper presents a design methodology for transimpedance amplifier (TIA) that emphasizes enhanced power supply rejection ratio (PSRR), specifically tailored long‐distance frequency‐modulated continuous‐wave (FMCW) LiDAR systems. In these advanced systems, when critical components such as the transmitter, receiver, and optical phase shifters are integrated into system‐on‐chip (SoC), is subject to significant fluctuations. These fluctuations primarily result from high current switching activities inherent in components. Given extremely weak amplitude of received signals, it imperative TIA, serving initial stage signal amplification, possesses robust ability reject variations maintain integrity. Another challenge TIA input DC current. Typically, AC signal, which carries desired distance information, accompanied by substantial If left unaddressed, this component can saturate thereby preventing accurate amplification signal. To overcome this, proposed incorporates mechanism designed current, ensuring operates within its optimal range effectively processes The architecture not only addresses but also significantly improves PSRR, making highly suitable stringent demands Furthermore, versatility allows be applied other systems encounter similar challenges with interference. Detailed post layout simulations conducted using 0.25‐μm IHP standard CMOS process demonstrate achieves improvement 30‐dB enhancement compared conventional designs. performance maintained even presence underscoring efficacy real‐world applications. results indicate efficient solution SoC‐based FMCW applications requiring sensitivity resilience disturbances.

Language: Английский

Citations

0
Visual Navigation and Crop Mapping of a Phenotyping Robot MARS-PhenoBot in Simulation DOI Creative Commons
Zhengkun Li, Rui Xu, Changying Li

et al.

Smart Agricultural Technology, Journal Year: 2025, Volume and Issue: unknown, P. 100910 - 100910

Published: March 1, 2025

Language: Английский

Citations

0
Soybean–Corn Seedling Crop Row Detection for Agricultural Autonomous Navigation Based on GD-YOLOv10n-Seg DOI Creative Commons

Tao Sun,

Feixiang Le, Chen Cai

et al.

Agriculture, Journal Year: 2025, Volume and Issue: 15(7), P. 796 - 796

Published: April 7, 2025

Accurate crop row detection is an important foundation for agricultural machinery to realize autonomous operation. Existing methods often compromise between real-time performance and accuracy, limiting their practical field applicability. This study develops a high-precision, efficient algorithm specifically optimized soybean–corn compound planting conditions, addressing both computational efficiency recognition accuracy. In this paper, method based on GD-YOLOv10n-seg with principal component analysis (PCA) fitting was proposed. Firstly, the dataset of seedling rows established, images were labeled line labels. Then, improved model constructed by integrating GhostModule DynamicConv into YOLOv10n-segmentation model. The experimental results showed that performed better in MPA MIoU, size reduced 18.3%. center lines segmentation fitted PCA, where accuracy reached 95.08%, angle deviation 1.75°, overall processing speed 61.47 FPS. can provide reliable solution navigation operations such as weeding pesticide application under mode.

Language: Английский

Citations

0
Early prediction of disease in soybeans by state-of-the-art machine vision technology DOI
Amit Ghimire, Yoon-Ha Kim

Journal of Crop Science and Biotechnology, Journal Year: 2025, Volume and Issue: unknown

Published: April 28, 2025

Language: Английский

Citations

0
A Review on the Evolution of Air-Assisted Spraying in Orchards and the Associated Leaf Motion During Spraying DOI Creative Commons
Guanqun Wang, Ziyu Li,

Weidong Jia

et al.

Agriculture, Journal Year: 2025, Volume and Issue: 15(9), P. 964 - 964

Published: April 29, 2025

Air-assisted spraying is vital in modern orchard pest management by enhancing droplet penetration and coverage on complex canopies. However, the interaction between airflow, droplets, flexible foliage remains unclear, limiting spray efficiency environmental sustainability. This review summarizes recent advances understanding leaf motion dynamics wind fields their impact pesticide deposition. First, we technologies, focusing air-assisted systems contribution to more uniform coverage. Next, analyze mechanisms of deposition within canopies, highlighting how characteristics, size, canopy structure influence distribution. Special attention given aerodynamic responses, including bending, vibration, transient deformation induced impacts. Experimental simulation studies reveal affects retention, spreading, secondary splashing. The limitations static boundary models simulations are discussed, along with potential fluid-structure (FSI) models. Future directions include integrated leaf-droplet experiments, intelligent airflow control, incorporating plant biomechanics into precision spraying. Understanding environments key efficiency, precision,

Language: Английский

Citations

0
Application of LiDAR Sensors for Crop and Working Environment Recognition in Agriculture: A Review DOI Creative Commons
Md Rejaul Karim, Md Nasim Reza, Hongbin Jin

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(24), P. 4623 - 4623

Published: Dec. 10, 2024

LiDAR sensors have great potential for enabling crop recognition (e.g., plant height, canopy area, spacing, and intra-row spacing measurements) the of agricultural working environments field boundaries, ridges, obstacles) using machinery. The objective this study was to review use in crops environments. This also highlights sensor testing procedures, focusing on critical parameters, industry standards, accuracy benchmarks; it evaluates specifications various commercially available with applications feature characterization importance mounting technology machinery effective Different studies shown promising results an airborne LiDAR, such as coefficient determination (R2) root-mean-square error (RMSE) values 0.97 0.05 m wheat, 0.88 5.2 cm sugar beet, 0.50 12 potato height estimation, respectively. A relative 11.83% observed between manual measurements, highest distribution correlation at 0.675 average 5.14% during soybean estimation LiDAR. An object detection 100% found identification three scanning methods: center cluster, lowest point, stem–ground intersection. effectively detect obstacles, which is necessary precision agriculture autonomous navigation. Future directions emphasize need continuous advancements technology, along integration complementary systems algorithms, machine learning, improve performance applications. strategic framework implementing includes recommendations precise testing, solutions current limitations, guidance integrating other technologies enhance digital agriculture.

Language: Английский

Citations

3
Advances in LiDAR Hardware Technology: Focus on Elastic LiDAR for Solid Target Scanning DOI Creative Commons
Wentao Li,

Tianyun Shi,

Rui Wang

et al.

Sensors, Journal Year: 2024, Volume and Issue: 24(22), P. 7268 - 7268

Published: Nov. 14, 2024

This paper explores the development of elastic LiDAR technology, focusing specifically on key components relevant to solid target scanning applications. By analyzing its fundamentals and working mechanisms, advantages for precise measurement environmental sensing are demonstrated. emphasizes innovative advances in emitters systems, examines impact optical design performance cost. Various ranging methods discussed. Practical application cases presented, future trends challenges explored. The purpose this is provide a comprehensive perspective technical details LiDAR, current state application, directions. All instances “LiDAR” refer LiDAR.

Language: Английский

Citations

2