Crop protection and disease detection using artificial intelligence and computer vision: a comprehensive review

被引:0
|
作者
Shah K. [1 ]
Sushra R. [2 ]
Shah M. [3 ]
Shah D. [4 ,8 ]
Shah H. [4 ]
Raval M. [5 ]
Prajapati M. [6 ]
机构
[1] Software Engineer, Walmart, Sunnyvale, CA
[2] Atmiya Vidya Mandir, Gujarat, Surat
[3] Department of Chemical Engineering, School of Energy Technology, Pandit Deendayal Energy University, Gujarat, Gandhinagar
[4] Robotics, ECE Concentration, Northeastern University, Boston, MA
[5] Department of Computer Science, Concentration in AI, Hofstra University, Hempstead, NY
[6] Technology, Gujarat, Navsari
[7] D Engineer, Span Inspection Systems Pvt. Ltd, Gujarat, Gandhinagar
关键词
Agriculture; Computer vision; Crop; Disease; Machine learning; Protection;
D O I
10.1007/s11042-024-19205-9
中图分类号
学科分类号
摘要
The technological advancements in the field of agriculture have increased to a great extent in recent years, and many techniques have evolved from other techniques. Some methods are improved or upgraded from the previous versions by implementing a new model or using better hardware devices. This has been helpful for the farmers in increasing crop productivity, and the life expectancy of crops has also increased as the diseases inside or outside the crops can be detected much earlier, and learning at an early stage helps prevent other crops. In this paper, we have presented a study where many varieties of fruits and vegetables have been taken to determine which method was used for a particular crop. By analyzing the various works carried out by the authors, it was inferred that most of the works revolved around image processing and hyperspectral imaging. Due to this, we had also included most of the papers, particularly as the models and hardware components used were much better than other works. Then, a comparative study was done where different fruits and vegetables highlighted the two main areas: the method used and the accuracy obtained. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
引用
收藏
页码:3723 / 3743
页数:20
相关论文
共 50 条
  • [21] Time Headway Using Computer Vision Integrated with Artificial Intelligence
    Obaidat, Mohammed Taleb
    AlOmari, Laith D.
    JORDAN JOURNAL OF CIVIL ENGINEERING, 2024, 18 (03) : 481 - 491
  • [22] Feasibility of Using Computer Vision and Artificial Intelligence Techniques in Detection of Some Apple Pests and Diseases
    Abbaspour-Gilandeh, Yousef
    Aghabara, Abdollah
    Davari, Mahdi
    Maja, Joe Mari
    APPLIED SCIENCES-BASEL, 2022, 12 (02):
  • [23] Fishing event detection and species classification using computer vision and artificial intelligence for electronic monitoring
    Saqib, Muhammad
    Khokher, Muhammad Rizwan
    Yuan, Xin
    Yan, Bo
    Bearham, Douglas
    Devine, Carlie
    Untiedt, Candice
    Cannard, Toni
    Maguire, Kylie
    Tuck, Geoffrey N.
    Little, L. Rich
    Wang, Dadong
    FISHERIES RESEARCH, 2024, 280
  • [24] A comprehensive review on heart disease prognostication using different artificial intelligence algorithms
    Fathima, A. Jainul
    Fasla, M. M. Noor
    COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING, 2024, 27 (11) : 1357 - 1374
  • [25] Artificial Intelligence Integrated Rice Crop Disease Detection Using Drones for Smart Farming
    Verma, Ayush Kumar
    Diksha
    Sharma, Sachin
    Proceedings of International Conference on Circuit Power and Computing Technologies, ICCPCT 2024, 2024, : 709 - 713
  • [26] Artificial Intelligence and Computer Vision in Low Back Pain: A Systematic Review
    D'Antoni, Federico
    Russo, Fabrizio
    Ambrosio, Luca
    Vollero, Luca
    Vadala, Gianluca
    Merone, Mario
    Papalia, Rocco
    Denaro, Vincenzo
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2021, 18 (20)
  • [27] Breast Cancer Detection and Classification using Traditional Computer Vision Techniques: A Comprehensive Review
    Zahoor, Saliha
    Lali, Ikram Ullah
    Khan, Muhammad Attique
    Javed, Kashif
    Mehmood, Waqar
    CURRENT MEDICAL IMAGING, 2020, 16 (10) : 1187 - 1200
  • [28] A comprehensive review on automation in agriculture using artificial intelligence
    Jha, Kirtan
    Doshi, Aalap
    Patel, Poojan
    Shah, Manan
    ARTIFICIAL INTELLIGENCE IN AGRICULTURE, 2019, 2 : 1 - 12
  • [29] A comprehensive review of using optical fibre interferometry for intrusion detection with artificial intelligence techniques
    Mehta, Hitesh
    Ramrao, Nagaraj
    Sharan, Preeta
    JOURNAL OF OPTICS-INDIA, 2024,
  • [30] A comprehensive review of elderly fall detection using wireless communication and artificial intelligence techniques
    Gharghan, Sadik Kamel
    Hashim, Huda Ali
    MEASUREMENT, 2024, 226