qCrop: An IoT Based Framework to Enhance Crop Productivity in Smart Agriculture

Food is crucial in our life. Despite food manufacturers' efforts to meet consumers' needs with manufactured food, it cannot attain the identical level of quality and flavor as natural food. Some fruits and vegetables are classified as food that cannot be manufactured. Also, they play an essential role worldwide. This paper focuses on how farmers can protect their farms from an object that might threaten the crops and cause damage to them. It proposes a framework that farmers may utilize to safeguard the crops against any species of birds. Considering the adverse impact of bird attacks on crop production, this system effectively addresses this problem and consistently enhances the quality and quantity of them. It utilizes computer vision technology to establish a secure environment for the crop. This system is called Quality of Crop Device (qCrop), and it works with a You Only Look Once (Yolov8m) model to detect birds with high accuracy to protect farms.

Authors

Institutions

Publication Details

Published
2024-10-06
DOI
https://doi.org/10.1109/vlsi-soc62099.2024.10767795
Citations
3
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
1.80
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

qCrop: An IoT Based Framework to Enhance Crop Productivity in Smart Agriculture

Elias Kougianos, Saraju P. Mohanty, Laavanya Rachakonda, Mahdi Shamsa
3 citations
Smart Agriculture and AI
1.80
article

qCrop: An IoT Based Framework to Enhance Crop Productivity in Smart Agriculture

Elias Kougianos, Saraju P. Mohanty, Laavanya Rachakonda, Mahdi Shamsa
article en
3 citations

Abstract

Food is crucial in our life. Despite food manufacturers' efforts to meet consumers' needs with manufactured food, it cannot attain the identical level of quality and flavor as natural food. Some fruits and vegetables are classified as food that cannot be manufactured. Also, they play an essential role worldwide. This paper focuses on how farmers can protect their farms from an object that might threaten the crops and cause damage to them. It proposes a framework that farmers may utilize to safeguard the crops against any species of birds. Considering the adverse impact of bird attacks on crop production, this system effectively addresses this problem and consistently enhances the quality and quantity of them. It utilizes computer vision technology to establish a secure environment for the crop. This system is called Quality of Crop Device (qCrop), and it works with a You Only Look Once (Yolov8m) model to detect birds with high accuracy to protect farms.

University of North Texas (US), University of North Carolina Wilmington (US)
Zero hunger
Openalex Percentile: Top 12%
Smart Agriculture and AI
1.80
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

qCrop: An IoT Based Framework to Enhance Crop Productivity in Smart Agriculture — Elias Kougianos, Saraju P. Mohanty, et al. · (2024) | TGRS Research Map | TGRS