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RISS 인기검색어
- 검색키워드
- 저자 : Md Asrakul Haque (검색결과 3 건)
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Evaluating the Accuracy of FOV Alignment for Micasense Multispectral Imagery in VI Calculation
( Md Asrakul Haque ),( Md Rejaul Karim ),( Md Razob Ali ),( Shaha Nur Kabir ),( Keong Do Lee ),( Yeong Ho Kang ),( Sun-ok Chung ) 한국농업기계학회 2023 한국농업기계학회 학술발표논문집 Vol.28 No.2
Multispectral imagery is pivotal for vegetation index (VI) analysis, shaping crop nutritional management strategies and advancing precision agriculture. Yet, the efficacy of image enhancement techniques in VI calculation remains a critical inquiry. This study addresses this gap by evaluating various image enhancement methods for multispectral imagery, focusing on the widely accepted Normalized Differential Vegetation Index (NDVI). We employed a multispectral sensor, the MicaSense RedEdge MX, alongside an active sensor, the Crop-circle ACS-435, to assess NDVI calculation performance. Our objective was to assess the accuracy of the Field of View (FOV) alignment of MicaSense with the active sensor. Data collection occurred across four distinct wheat growth stages (GS1, GS2, GS3, and GS4) utilizing a handheld structure equipped with Crop Circle ACS 435, MicaSense RedEdge MX, and a Topcon Hiper VR GNSS rover. This setup maintained a consistent 90cm canopy height based on the plot width. Python programming facilitated GPS location processing and image segmentation based on pixel coordinates, mirroring the Crop-circle FOV. We extracted reflectance data from the segmented portion of each band and calculated NDVI using Red and NIR reflectance data. Data enhancement techniques were assessed by comparing enhanced and raw image data against standardized data from the Crop-circle sensor. Regression analysis, including the coefficient of determination (R2) and root mean square error (RMSE), was utilized for evaluation. The application of the FOV enhancement technique to MicaSense images yielded significant improvements in regression metrics (R2 and RMSE) across GS1, GS2, GS3, and GS4. Notably, FOV enhancement resulted in R2 increases of 50%, 18%, 16%, and 4% and RMSE values of0.06, 0.05, 0.06, and 0.03, respectively. The most substantial accuracy enhancements were observed in GS1 (50%), indicating varying effectiveness based on vegetation growth stage and density. This study underscores the critical role of multispectral imagery and the efficacy of FOV alignment in improving NDVI calculation accuracy. These findings hold valuable implications for future research and precision agriculture practices.
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Development of a sandy soil water content monitoring system for greenhouses using Internet of Things
Mohammod Ali,Md Razob Ali,Md Ashrafuzzaman Gulandaz,Md Asrakul Haque,Md Sazzadul Kabir,Sun-Ok Chung 사단법인 한국정밀농업학회 2023 정밀농업과학기술지 Vol.5 No.3
Precision water management is crucial for greenhouse agriculture to maximize crop yields in sandy soil. Due to the low water holding capacity, it is necessary to monitor the water movement in different depths of sandy soil to ensure effective irrigation. Therefore, this study aimed to develop a data acquisition (DAQ) system for sandy soil water content monitoring in an experimental soil bin inside a greenhouse, utilizing the capabilities of the Internet of Things (IoT). A drip irrigation system was implemented, arranged in four pipelines, spaced 60 cm apart, with drippers placed at 30 cm intervals along the pipeline. The overall system was installed in a sandy soil testing bin. A DAQ system was comprised of three basic units: sensor interfacing and circuit board, programming and sensor data acquisition, and data storage and monitoring. A microprocessor was used by interfacing a set of soil water content sensors, ambient temperature, and humidity sensors. The water content sensors were placed in the soil at different depths of 10, 20, 30, 40, and 50 cm, respectively. A microcontroller was used to collect and send the sensor data to monitor and store in memory. During the test, the maximum and minimum average of soil water content, ambient temperature, and humidity values were observed at 33.91±2.5 to 26.95±1.3%, 21.39±2.1 to 42.84±1.7°C, and 48.73±2.3 to 99.90±0.3%, respectively. The water content percentages were varied at different depths of sandy soil due to low water holding capacity. The developed automatic DAQ system would help with remote monitoring and control of greenhouse irrigation, considering the different crop characteristics and environmental conditions.
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Pepper transplanting mechanisms and kinematic simulation analysis: A review
HABINEZA ELIEZEL,Md Nasim Reza,Emmanuel Bicamumakuba,Md Asrakul Haque,박석호,이대현,Sun-Ok Chung,이예슬 사단법인 한국정밀농업학회 2024 정밀농업과학기술지 Vol.6 No.1
Pepper production plays a significant role in the global agricultural economy, yet traditional manual transplanting methods lead to labor intensity challenges, inconsistency, and time constraints. Transplanting mechanisms of pepper transplanters significantly affect the efficiency of the entire transplanting process. This study reviewed the available transplanters used in pepper seedling transplantation, transplanting mechanisms, and the kinematic simulation analysis. Pepper transplanters are categorized into manual, semi-automatic, and fully automatic types. Manual types include handheld and pulling types, while semi-automatic types involve manually seedling feeding with automatic planting such walking-behind, riding, and tractor-drawn models. Fully automatic transplanters synchronize seedling extracting, transfer to the conveyor, and continuous planting into the soil. Picking mechanism utilize pick-up pins, pushing action, and grippers, while planting mechanism is achieved through link-driven, wheel-driven, and rotary gear-driven hoppers. Recent advancements have emphasized 4- and 5-bar pick-up pin-type link-driven hoppers with 1 or 2 degrees of freedom for efficient seedling handling and planting. Kinematic simulation analysis emerges as a crucial tool used by engineers to better understand complex interactions, identify strengths and weaknesses in designs for the evaluation and optimization of mechanisms by modelling forces, motion, and system behavior. The transplanting mechanisms survey, the role of kinematic simulation, and key trends involved, such as increased automation, precision planting, and the integration of sensor technologies, could provide valuable information to farmers and manufacturers for identifying current gaps and improvement areas for enhancing innovation in pepper production.
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