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Design of an ICT-based Irrigation Control System for Orchard Soil Water Content Monitoring
아흐메드샤리아르 ( Shahriar Ahmed ),알리모하마드 ( Mohammad Ali ),하비네자엘리에젤 ( Eliezel Habineza ),정선옥 ( Sun-ok Chung ) 한국농업기계학회 2022 한국농업기계학회 학술발표논문집 Vol.27 No.2
Deficient or excessive irrigation inhibits root growth and increases the risk of essential minerals being leached from the root zone, causing a nutritional deficiency. Irrigation scheduling can be managed based on soil water stress. The purpose of this study was to design an automatic control system for irrigation based on real-time soil water content monitoring in orchard soil which was capable of being accessed remotely via the internet. A test bench was fabricated in a soil bin. Soil water content sensors were installed in separate channels across the test bin to maintain the average water content for different circumstances. A python-based program was created to control the irrigation pump and solenoid valves using water content values from sensors via a micro-controller. Additionally, a python program was developed to transfer all the data from water content, water flow and pressure sensors to a database system to monitor the irrigation operation using a WI-FI network. The system was able to sense analog values from water content sensors, water flow and pressure sensors. The water content values after reaching 25% and 30%, the system sent signals to the irrigation pump and solenoid valves and terminated the irrigation process accordingly. Besides the system sent all the sensors values to the database system every 1-minute interval. With the proposed low-cost real-time monitoring system, it could help to increase production efficiency, use less labor, reduce water loss, and optimize water consumption.
Volumetric yield prediction of Chinese cabbage using CCD camera
구란다즈아스라푸자만 ( Ashrafuzzaman Gulandaz ),카비르사자둘 ( Sazzadul Kabir ),래자나심 ( Nasim Reza ),알리모하마드 ( Mohammad Ali ),정선옥 ( Sun-ok Chung ) 한국농업기계학회 2022 한국농업기계학회 학술발표논문집 Vol.27 No.2
Yield monitoring helps farmers make the proper use of their resources and estimate their crop yield precisely. The objective of the study was to measure the volume of Chinese cabbage using CCD (Charged-coupled device) camera. This system captures RGB images of 30 cabbage samples with the help of two 9-W fluorescent LED light sources, a CCD camera, and an HP core i7 laptop. The camera and LED lights were mounted 1.08 m above the harvester conveyor. The speeds of the conveyor were 0.55 m/s, 0.70 m/s, and 0.85 m/s, respectively, for taking RGB images using the CCD camera, which was triggered by two ultrasonic sensors at a frequency of 5 Hz. Archimedes’ law was used to measure the actual volume of the 30 cabbages in a traditional way. A combination of an RGB image processing technique and a point cloud approach was developed. The images were processed by background subtraction and edge detection algorithms using a Python-based programming language. The volume of cabbage with an ellipsoidal shape was estimated using the box method. Height of each cabbage surface point was found by subtracting the value of each cabbage sample point from the value of the background point. These traditional and box estimation methods provided volumes in the range of 0.003m3 to 0.007m3, respectively. The linear regression approach and t-test analyses (equal variances for means α=0.05) were used to compare the estimated and measured volumes of cabbage, and each method was not substantially different. The results showed that the R2 values were 0.82, 0.74, 0.67 and the root mean square error (RMSE) values were 0.00035 m3, 0.00028 m3 and 0.00025 m3, respectively. In real conditions, the estimated volume can be used to calculate the cabbage yield during harvesting.