manual methods
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Author(s):  
Vikram Raja ◽  
Bindu Bhaskaran ◽  
Koushik Karan Geetha Nagaraj ◽  
Jai Gowtham Sampathkumar ◽  
Shri Ram Senthilkumar

In today's competitive world, robot designs are developed to simplify and improve quality wherever necessary. The rise in technology and modernization has led people from the unskilled sector to shift to the skilled sector. The agricultural sector's solution for harvesting fruits and vegetables is manual labor and a few other agro bots that are expensive and have various limitations when it comes to harvesting. Although robots present may achieve harvesting, the affordability of such designs may not be possible by small and medium-scale producers. The integrated robot system is designed to solve this problem, and when compared with the existing manual methods, this seems to be the most cost-effective, efficient, and viable solution. The robot uses deep learning for image detection, and the object is acquired using robotic manipulators. The robot uses a Cartesian and articulated configuration to perform the picking action. In the end, the robot is operated where carrots and cantaloupes were harvested. The data of the harvested crops are used to arrive at the conclusion of the robot's accuracy.


2022 ◽  
Vol 2160 (1) ◽  
pp. 012078
Author(s):  
Xinhai Li ◽  
Haixin Luo ◽  
Lingcheng Zeng ◽  
Chenxu Meng ◽  
Yanhe Yin

Abstract Currently, the check of the relay protection pressure plate’s throw-out status is mainly carried out manually, due to the extremely large number of decompression plates, manual methods can cause detection errors due to fatigue. This paper proposes the processing of relay protection pressure plate photographs by using image processing techniques, the Faster R-CNN image recognition algorithm uses the feature of generating detection frames directly using RPN to identify the platen throwback status of the processed platen images, greatly improving the speed and accuracy of the detection frame generation. The experimental results show that, the method proposed in this paper effectively solves the problem of errors arising from manual verification checks of platen throwbacks, reduced workload for substation staff, the platen recognition rate can be over 98% correct.


2021 ◽  
Author(s):  
Babar Mohamed Saleem ◽  
Janardhanan Kunissery Puliyakotte ◽  
Abullais Ullalil Mundeth ◽  
Diaa Mohamed Yasein ◽  
Mohammed Ali Al-Muri ◽  
...  

Abstract ADNOC BAB Field has 11 water disposal wells, which are currently being monitored manually. The paper is about the implementation of remote annulus pressure monitoring for water disposal wells. The manual methods of monitoring remote annulis pressure comes in with inherent disadvantages like no continuous monitoring and deployment of our skilled resources for the same. The paper throws light on the present issues faced while using the manual monitoring and how it has been covered when the proposed wireless technology is implemented. Also the paper illustrates, the savings in terms of man power and resources and relevance of the technology to the modern age oil and gas upstream industry considering the scalablity to more number of wells in vast oil fields.


2021 ◽  
Author(s):  
Victoria Berezowski ◽  
Xanthé Mallett ◽  
Ian Moffat

The purpose of this review paper is to highlight various geomatic techniques that crime scene reconstructionists or forensic practitioners can use to document different kinds of scenes, highlighting the advantages, disadvantages, and when best to use each technology. This paper explores geomatic techniques such as a total station, photogrammetry, laser scanners and structured light scanners and how they can be used to reconstruct crime scenes. The goal of this paper is not to discredit manual methods, as they are long standing and reliable, but instead to shed light on alternative methods that may produce equally or more accurate results with a more visually appealing final product. It is important for law enforcement and forensic professionals to understand the advantages and disadvantages of each technique, knowing when certain techniques should be used (and when they should not), and being able to revert to traditional methods if required.


2021 ◽  
Vol 5 (1) ◽  
pp. 55
Author(s):  
Dwi Santoso ◽  
Galih Yogi Rahajeng ◽  
Saat Egra

ABSTRAKPermasalahan yang dihadapi oleh Kelompok tani Suka Maju hingga saat ini yaitu masih menggunakan metode manual dalam proses penanaman benih jagung, hal ini membuat waktu pengerjaan lebih lama dan posisi lubang tidak sejajar dan presisi. Dampak dari dua hal tersebut yaitu akan menambah biaya tenaga kerja dan posisi jagung yang tidak sejajar ataupun berhimpitan akan membuat petumbuhan tanaman jagung tidak optimal. Pengabdian ini bertujuan untuk menerapkan teknologi alat penanam benih tipe row seeder untuk mengurangi jerih kerja petani pada saat proses penanaman benih khususnya tanaman jagung. Kegiatan PKM ini dilakukan di lahan Kelompok tani Suka Maju  Kelurahan Juata Laut Kecamatan Tarakan Utara, Kota Tarakan. Kegiatan ini dibagi dalam beberapa tahapan yaitu survey, sosialisasi, pembuatan alat, bimbingan teknis serta evaluasi pelaksanaan dan keberlanjutan program oleh Kelompok Tani. Kegiatan PKM penerapan teknologi alat penanam tipe row seeder di kelompok tani Suka Maju berjalan dengan baik serta para petani bersemangat untuk mengaplikasikan alat penanam di setiap lahan mereka. Selain itu terjadi peningkatan efisiensi dalam proses budidaya tanaman jagung dikelompok tani suka maju yaitu proses penananam jagung bisa lebih cepat 45% dibandingkan pada saat penanaman benih jagung secara manual Kata kunci: penerapan; alat penanam benih jagung; tipe row seeder. ABSTRACTThe problem faced by the Suka Maju farmer group until now is that they still use manual methods in the process of planting corn seeds, this makes the processing time longer and the position of the planting holes is not parallel and precise. The impact of these two things is that it will increase labor costs and the position of corn that is not parallel or coincides will make corn plant growth not optimal. This service aims to apply row seeder type seed planter technology to reduce the labor of farmers during the seed planting process, especially for corn plants. This PKM activity was carried out on agricultural land belonging to the Suka Maju farmer group, Juata Laut Village, North Tarakan District, Tarakan City. This activity is divided into several stages, namely survey, socialization, tool making, technical guidance and evaluation of the implementation and sustainability of the program by the Farmer Group. The PKM activity for the application of row seeder type planter technology in the Suka Maju farmer group is going well and the farmers are excited to apply the planter in each of their lands. In addition, there is an increase in efficiency in the corn cultivation process in the advanced farmer group, namely the corn planting process can be 45% faster than when planting corn seeds manually. Keywords: application; corn seed planter; row seeder type.


2021 ◽  
Author(s):  
R. Heema ◽  
K.S. Gnanalakshmi

The dairy and food industries aims to achieve targeted productivity and very keen on product quality and consumer demand. Due to increasing technological advances, these food and dairy industries gained numerous technological support. Among the diverse development, the usages of e-nose and e-tongue paved the way to handle the production without any kind of deviation. In the food industries product perfection, uniform taste and aroma plays a supreme role because these parameters determine the marketing strategy. The electronic nose (e-nose) is a non-destructive intelligent electronic sensing instrument, which mimics the human olfactory system to detect, discriminate and classify odour samples. e-nose and e-tongue is an electronic tool used as a fast screening method to provide information about the product quality which is not easily done by manual methods as it is a time-consuming process. In this paper, the principle of e-nose and e-tongue and their applications in the dairy and food industries are explained.


Author(s):  
Peechana Aiadsakun ◽  
Wilaiwan Sriwimol ◽  
Nannapas Thongbun ◽  
Bancha Rui-on ◽  
Kulathida Thiparaksaphan ◽  
...  

2021 ◽  
Vol 6 (2) ◽  
pp. 259
Author(s):  
Budi Yanto ◽  
Luth Fimawahib ◽  
Asep Supriyanto ◽  
B.Herawan Hayadi ◽  
Rinanda Rizki Pratama

Sweet orange is very much consumed by humans because oranges are rich in vitamin C, sweet oranges can be consumed directly to drink. The classification carried out to determine proper (good) and unfit (rotten) oranges still uses manual methods, This classification has several weaknesses, namely the existence of human visual limitations, is influenced by the psychological condition of the observations and takes a long time. One of the classification methods for sweet orange fruit with a computerized system the Convolutional Neural Network (CNN) is algorithm deep learning to the development of the Multilayer Perceptron (MLP) with 100 datasets of sweet orange images, the classification accuracy rate was 97.5184%. the classification was carried out, the result was 67.8221%. Testing of 10 citrus fruit images divided into 5 good citrus images and 5 rotten citrus images at 96% for training 92% for testing which were considered to have been able to classify the appropriateness of sweet orange fruit very well. The graph of the results of the accuracy testing is 0.92 or 92%. This result is quite good, for the RGB histogram display the orange image is good


2021 ◽  
Vol 11 (23) ◽  
pp. 11084
Author(s):  
José Hurtado-Avilés ◽  
Vicente J. León-Muñoz ◽  
Pilar Andújar-Ortuño ◽  
Fernando Santonja-Renedo ◽  
Mónica Collazo-Diéguez ◽  
...  

Axial vertebral rotation (AVR) and Cobb angles are the essential parameters to analyse different types of scoliosis, including adolescent idiopathic scoliosis. The literature shows significant discrepancies in the validity and reliability of AVR measurements taken in radiographic examinations, according to the type of vertebra. This study’s scope evaluated the validity and absolute reliability of thoracic and lumbar vertebrae AVR measurements, using a validated software based on Raimondi’s method in digital X-rays that allowed measurement with minor error when compared with other traditional, manual methods. Twelve independent evaluators measured AVR on the 74 most rotated vertebrae in 42 X-rays with the software on three separate occasions, with one-month intervals. We have obtained a gold standard for the AVR of vertebrae. The validity and reliability of the measurements of the thoracic and lumbar vertebrae were studied separately. Measurements that were performed on lumbar vertebrae were shown to be 3.6 times more valid than those performed on thoracic, and with almost an equal reliability (1.38° ± 1.88° compared to −0.38° ± 1.83°). We can conclude that AVR measurements of the thoracic vertebrae show a more significant Mean Bias Error and a very similar reliability than those of the lumbar vertebrae.


Agronomy ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 2328
Author(s):  
Lifa Fang ◽  
Yanqiang Wu ◽  
Yuhua Li ◽  
Hongen Guo ◽  
Hua Zhang ◽  
...  

A consistent orientation of ginger shoots when sowing ginger is more conducive to high yields and later harvesting. However, current ginger sowing mainly relies on manual methods, seriously hindering the ginger industry’s development. Existing ginger seeders still require manual assistance in placing ginger seeds to achieve consistent ginger shoot orientation. To address the problem that existing ginger seeders have difficulty in automating seeding and ensuring consistent ginger shoot orientation, this study applies object detection techniques in deep learning to the detection of ginger and proposes a ginger recognition network based on YOLOv4-LITE, which, first, uses MobileNetv2 as the backbone network of the model and, second, adds coordinate attention to MobileNetv2 and uses Do-Conv convolution to replace part of the traditional convolution. After completing the prediction of ginger and ginger shoots, this paper determines ginger shoot orientation by calculating the relative positions of the largest ginger shoot and the ginger. The mean average precision, Params, and giga Flops of the proposed YOLOv4-LITE in the test set reached 98.73%, 47.99 M, and 8.74, respectively. The experimental results show that YOLOv4-LITE achieved ginger seed detection and ginger shoot orientation calculation, and that it provides a technical guarantee for automated ginger seeding.


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