Date of Publication

9-2020

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Electronics and Communications Engineering

Subject Categories

Electrical and Computer Engineering

College

Gokongwei College of Engineering

Department/Unit

Electronics and Communications Engineering

Thesis Adviser

Elmer P. Dadios

Defense Panel Chair

Argel A. Bandala

Defense Panel Member

Raouf Naguib
Ryan Rhay P. Vicerra
Laurence A. Gan Lim
Edwin J. Calilung

Abstract/Summary

In the country, it was only last March 2, 2019, that the ‘First Smart Farm in the Philippines’ has been inaugurated. The farm is owned by the government and not by any local farmer or farm owners. To hasten up the involvement of local farmers to the idea of smart farming, technologies that are easily deployable and less expensive can be introduced to them. One of the crux aspects in the implementation of smart farming is the monitoring system which observes the significant indicators that help farmers to identify what is needed, and where and when it should be applied.

The machine vision monitoring and detection system developed in this research work consist primarily of three modules. First, the path planning module is designed to generate the mission-specific waypoints based on the user-defined area-of-interest (AOI) for the unmanned aerial vehicle intended for data acquisition. The second module is the farm activity monitor (FAM) which detects and counts farmers in the field and recognizes their activities. The final module is the crop health monitoring (CHM) which collects the field data related to vegetation fraction, weed estimate, nitrogen and chlorophyll contents of crops, and pest damage detection. Also, the crop schedule and the planned farm activities can be accessed.

Abstract Format

html

Language

English

Format

Electronic

Keywords

Agricultural innovations; Computer vision

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Embargo Period

8-26-2022

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