Application of Remote Sensing and AI in Precision Agriculture: Monitoring Plant Health and Growth

The main food production and human sustenance activity is agriculture, which has greatly been improved through use of new methods. Among them, remote sensing (RS) and artificial intelligence (AI), are essential techniques in precision agriculture since they allow identifying the health of plants at an early stage, without errors, and in detail. In this study, the researcher is interested in the application of these technologies as a utilization tool to achieve precision and efficiency in agricultural activities, especially crop health, stress control, and the use of resources. The idea of remote sensing involves the use of satellites, drones, or ground sensors to take images on a large scale and in real-time to monitor the status of crops in large pieces of agricultural farming land. When used in conjunction with remote sensing, AI not only hastens the speed of monitoring plant health, but also enhances the chances of making accurate future decisions that, in case of remedial action, will help avoid crop losses and yield better outputs. The problems that come with these technologies are also discussed in this study, with the primary focus on high quality annotated datasets availability, environmental variability, model interpretation and explanations concerns. The aspect of ethicality, data privacy, and constant surveillance of agricultural activities, and their possibly adverse consequences of these practices are also addressed.

• Publication year

  2025

• Venue

  2025 International Conference on Intelligent Computing, Information and Control Systems (ICOIICS)

• Publication date

  2025-11-19

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1109/ICOIICS67115.2025.11390521
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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