Augmented Reality Combined with Machine Learning to Increase Productivity in Fruit Packing

被引:0
|
作者
van der Westhuizen, M. [1 ]
von Leipzig, K. H. [1 ]
Hummel, V. [2 ]
机构
[1] Univ Stellenbosch, Dept Ind Engn, Stellenbosch, South Africa
[2] Reutlingen Univ, ESB Business Sch, Logist Management, Reutlingen, Germany
关键词
Augmented reality; Machine learning; Avocado fruit; Productivity; Hololens; Microsoft azure;
D O I
10.1007/978-3-031-15602-1_31
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
This paper studies the benefits of using Augmented Reality and Machine Learning in the agricultural industry for the purpose of fruit classification. During fruit classification colour plays a vital role in determining fruit quality and attractiveness. It is for this reason that technology in agriculture is being adopted that can visually grade produce. Currently, the study of Augmented Reality and Machine learning technologies in the Agricultural sector is limited, specifically cornering productivity improvement resulting from the implementation of these technologies. Therefore, technology which offers collaboration between employees and visual technology, in the form of Augmented Reality using the HoloLens 1, was studied. Augmented Reality requires strong data analytical support because the effectiveness of Augmented Reality is directly proportional to the quality of the information utilised. To ensure accurate data analytics Machine Learning was used. To analyse the use of Augmented Reality and Machine Learning in agriculture these two technologies were used to classify avocados in terms of both fruit grade and size. Machine Learning was implemented using Microsoft Azure which was used to grade the fruit. This was done by providing 1053 photos of avocados to Microsoft Azure from which the Machine Learning algorithm could learn how the fruit was to be graded. To determine the size of the avocado the number of pixels and the distance of the avocado from the HoloLens was used. An Augmented Reality and Machine Learning prototype was implemented, and the time taken to pack an avocado box was taken. It was found that there was a packing speed increase of 29.87% and a decrease in the variation of this speed by 96.2% when the prototype was implemented. Doing a t-test it was quantified that the increase in packing speed was statistically significant. Therefore, it can be concluded that the use of Augmented Reality and Machine Learning can be used to aid employees to improve tasks in the agricultural industry.
引用
收藏
页码:415 / 431
页数:17
相关论文
共 50 条
  • [31] Virtual Reality and Tracking the Mating Behavior of Fruit Flies: a Machine Learning Approach
    Mozaffari, M. Hamed
    Wen, Shuangyue
    Lee, Won-Sook
    [J]. 2018 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND VIRTUAL ENVIRONMENTS FOR MEASUREMENT SYSTEMS AND APPLICATIONS (CIVEMSA), 2018,
  • [32] Designing Augmented Reality Virtual Displays for Productivity Work
    Pavanatto, Leonardo
    [J]. 2021 IEEE INTERNATIONAL SYMPOSIUM ON MIXED AND AUGMENTED REALITY ADJUNCT PROCEEDINGS (ISMAR-ADJUNCT 2021), 2021, : 459 - 460
  • [33] Data-Driven Digital Twins in Surgery utilizing Augmented Reality and Machine Learning
    Riedel, Paul
    Riesner, Michael
    Wendt, Karsten
    Assmann, Uwe
    [J]. 2022 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS WORKSHOPS (ICC WORKSHOPS), 2022, : 580 - 585
  • [34] A Comprehensive Survey on the Investigation of Machine-Learning-Powered Augmented Reality Applications in Education
    Khan, Haseeb Ali
    Jamil, Sonain
    Piran, Md. Jalil
    Kwon, Oh-Jin
    Lee, Jong-Weon
    [J]. TECHNOLOGIES, 2024, 12 (05)
  • [35] Augmented Reality-Centered Position Navigation for Wearable Devices with Machine Learning Techniques
    Kamalam, G. K.
    Joshi, Shubham
    Maheshwari, Manish
    Selvan, K. Senthamil
    Jamal, Sajjad Shaukat
    Vairaprakash, S.
    Alhassan, Musah
    [J]. JOURNAL OF HEALTHCARE ENGINEERING, 2022, 2022
  • [36] Augmented Reality and Machine Learning based Product Identification in Retail using Vuforia and MobileNets
    Upadhyay, Gagan Kishor
    Aggarwal, Divij
    Bonsai, Amogh
    Bhola, Geetanjali
    [J]. PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON INVENTIVE COMPUTATION TECHNOLOGIES (ICICT-2020), 2020, : 479 - 485
  • [37] An integrated framework of sensing, machine learning, and augmented reality for aquaculture prawn farm management
    Rahman, Ashfaqur
    Xi, Mingze
    Dabrowski, Joel Janek
    McCulloch, John
    Arnold, Stuart
    Rana, Mashud
    George, Andrew
    Adcock, Matt
    [J]. AQUACULTURAL ENGINEERING, 2021, 95
  • [38] Conceptual model of learning based on the combined capabilities of augmented and virtual reality technologies with adaptive learning systems
    Osadchyi, Viacheslav V.
    Chemerys, Hanna Y.
    Osadcha, Kateryna P.
    Kruhlyk, Vladyslav S.
    Koniukhov, Serhii L.
    Kiv, Arnold E.
    [J]. PROCEEDINGS OF THE 3RD INTERNATIONAL WORKSHOP ON AUGMENTED REALITY IN EDUCATION (AREDU 2020), 2020, 2731 : 328 - 340
  • [39] Increase grit and learning satisfaction in physical education among student-athletes: augmented reality Learning is the Solution?
    Paramitha, Sandey Tantra
    Setiawan, Edi
    Lesmana, Irfan Benizar
    Tannoubi, Amayra
    Raman, Arumugam
    Kurtoglu, Ahmet
    Gazali, Novri
    Rochman, Taupik
    Getu, Samson
    Lobo, Joseph
    [J]. RETOS-NUEVAS TENDENCIAS EN EDUCACION FISICA DEPORTE Y RECREACION, 2024, (61): : 589 - 597
  • [40] MACHINE TO INCREASE PRODUCTIVITY OF A TILLAGE OPERATION
    YOUNG, PE
    [J]. TRANSACTIONS OF THE ASAE, 1976, 19 (06): : 1055 - 1061