Affiliations 

  • 1 Department of Electronics and Electrical Engineering, Universiti Kuala Lumpur British Malaysian Institute (UniKL BMI), Batu 8, Jalan Sungai Pusu, Gombak 53100, Malaysia
  • 2 Faculty of Computing, Riphah International University, Islamabad 46000, Pakistan
  • 3 Department of Electrical Engineering, Ziauddin University, Karachi 74600, Pakistan
  • 4 Department of Computer Engineering, Umm Al Qura University, Makkah 21955, Saudi Arabia
  • 5 Department of Electrical Engineering, FET, Gomal University, Dera Ismail Khan 29050, Pakistan
  • 6 Faculty of Computing and Informatics, Multimedia University, Cyberjaya 63100, Malaysia
Sensors (Basel), 2022 Nov 07;22(21).
PMID: 36366269 DOI: 10.3390/s22218567

Abstract

Rice is one of the vital foods consumed in most countries throughout the world. To estimate the yield, crop counting is used to indicate improper growth, identification of loam land, and control of weeds. It is becoming necessary to grow crops healthy, precisely, and proficiently as the demand increases for food supplies. Traditional counting methods have numerous disadvantages, such as long delay times and high sensitivity, and they are easily disturbed by noise. In this research, the detection and counting of rice plants using an unmanned aerial vehicle (UAV) and aerial images with a geographic information system (GIS) are used. The technique is implemented in the area of forty acres of rice crop in Tando Adam, Sindh, Pakistan. To validate the performance of the proposed system, the obtained results are compared with the standard plant count techniques as well as approved by the agronomist after testing soil and monitoring the rice crop count in each acre of land of rice crops. From the results, it is found that the proposed system is precise and detects rice crops accurately, differentiates from other objects, and estimates the soil health based on plant counting data; however, in the case of clusters, the counting is performed in semi-automated mode.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.