scholarly journals Design and Implementation of Autonomous Flower Harvester using Image Processing

2019 ◽  
Vol 8 (2) ◽  
pp. 2638-2642
Keyword(s):  
Image Processing ◽  
Autonomous System ◽  
Cost Effective ◽  
Robotic Arm ◽  
Watershed Algorithm ◽  
Design And Implementation ◽  
Distance Calculation ◽  
Harvesting Systems ◽  
Cost Efficient

In this paper to design and implementation of fully autonomous system which can harvest flowers. The flowers will be able to cut from the plant by using the device proposed in this paper in a perfect condition which will take lesser time for harvesting as compared to the manual harvesting by humans. In recent days, automated flower harvesting is available only for large flowers like tulip. Thus there will be a requirement for harvesting smaller flowers like rose. This procedure will solve this problem and also it is cost efficient then manual harvesting. In this procedure the watershed algorithm is used to detect the flowers. By the histogram distance calculation, the detected flower is compared to the flowers which are already present in the database. If the detected flower matches 70-80%, then there will be the calculation of centroid of the flower and the distance from the centroid at which the stem is to be cut. The robotic arm is provided that will cut the matched flower when the signal has received to it via microcontroller. The project has to establish a cost effective harvesting systems for agricultural purpose.

scholarly journals A Novel Adaptive Pixels Segmentation Algorithm for Pavement Crack Detection

2021 ◽  
Author(s):  
Nima Safaei ◽  
Omar Smadi ◽  
Babak Safaei ◽  
Arezoo Masoud
Keyword(s):  
Crack Detection ◽  
Low Cost ◽  
Local Level ◽  
Cost Effective ◽  
Segmentation Algorithm ◽  
Pavement Maintenance ◽  
Detection Systems ◽  
Wide Range ◽  
Cost Efficient ◽  
Pavement Crack Detection

<p>Cracks considerably reduce the life span of pavement surfaces. Currently, there is a need for the development of robust automated distress evaluation systems that comprise a low-cost crack detection method for performing fast and cost-effective roadway health monitoring practices. Most of the current methods are costly and have labor-intensive learning processes, so they are not suitable for small local-level projects with limited resources or are only usable for specific pavement types.</p> <p>This paper proposes a new method that uses an improved version of the weighted neighborhood pixels segmentation algorithm to detect cracks in 2-D pavement images. This method uses the Gaussian cumulative density function as the adaptive threshold to overcome the drawback of fixed thresholds in noisy environments. The proposed algorithm was tested on 300 images containing a wide range of noise representative of different noise conditions. This method proved to be time and cost-efficient as it took less than 3.15 seconds per 320 × 480 pixels image for a Xeon (R) 3.70 GHz CPU processor to determine the detection results. This makes the model a perfect choice for county-level pavement maintenance projects requiring cost-effective pavement crack detection systems. The validation results were promising for the detection of low to severe-level cracks (Accuracy = 97.3%, Precision = 79.21%, Recall= 89.18% and F<sub>1</sub> score = 83.9%).</p>

scholarly journals Implementation of Gesture Control Robotic Arm for Automation of Industrial Application

2020 ◽  
pp. 147-156
Author(s):  
Shriya A. Hande ◽  
Nitin R. Chopde
Keyword(s):  
System Design ◽  
The Other ◽  
Robotic Arm ◽  
Human Hand ◽  
Design And Implementation ◽  
Gesture Control ◽  
Rf Signals ◽  
Pick And Place ◽  
Almost All ◽  
Minimal Effort

<p>In today’s world, in almost all sectors, most of the work is done by robots or robotic arm having different number of degree of freedoms (DOF’s) as per the requirement. This project deals with the Design and Implementation of a “Wireless Gesture Controlled Robotic Arm with Vision”. The system design is divided into 3 parts namely: Accelerometer Part, Robotic Arm and Platform. It is fundamentally an Accelerometer based framework which controls a Robotic Arm remotely utilizing a, little and minimal effort, 3-pivot (DOF's) accelerometer by means of RF signals. The Robotic Arm is mounted over a versatile stage which is likewise controlled remotely by another accelerometer. One accelerometer is mounted/joined on the human hand, catching its conduct (motions and stances) and hence the mechanical arm moves in like manner and the other accelerometer is mounted on any of the leg of the client/administrator, catching its motions and stances and in this way the stage moves as needs be. In a nutshell, the robotic arm and platform is synchronised with the gestures and postures of the hand and leg of the user / operator, respectively. The different motions performed by robotic arm are: PICK and PLACE / DROP, RAISING and LOWERING the objects. Also, the motions performed by the platform are: FORWARD, BACKWARD, RIGHT and LEFT.</p>

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