Interactive Orchard Intrusion Detection System Using Sensors and Human-in-the-Loop Control

To mitigate agricultural crop losses caused by wildlife and unauthorized intrusions, an interactive orchard intrusion detection system combining edge-level automation and human-inthe-loop control was developed.The system integrates an Arduino Mega 2560 microcontroller, a servo-mounted 180° scanning ultrasonic sensor, multi-modal deterrents, and an Internet Protocol camera for real-time smartphone verification.Experimental results for performance evaluation showed a spatial detection accuracy of 94.0%, an average local response latency of 420 ms, and a false-positive rejection rate of 89.5% against environmental clutter such as wind-driven foliage.Despite these advantages, the system presented limitations: ultrasonic susceptibility to severe weather and dense vegetation, reliance on manual human verification under intermittent rural connectivity, and vulnerability to pest habituation and high power demands.To address these limitations, it is necessary to incorporate edge AI for autonomous threat classification, solarassisted energy harvesting for power-supply autonomy, and long-range-based decentralized communication protocols to ensure long-range operation.The improved system serves as a scalable, low-cost solution for precision agriculture.

Authors

Institutions

Publication Details

Journal
Sensors and Materials
Published
2026-10-29
DOI
https://doi.org/10.18494/sam6269
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Interactive Orchard Intrusion Detection System Using Sensors and Human-in-the-Loop Control

Dyi‐Cheng Chen, Tian-Syung Lan, Shih-Ming Cho, Li-Chan Lu et al.
Sensors and Materials
Smart Agriculture and AI
article

Interactive Orchard Intrusion Detection System Using Sensors and Human-in-the-Loop Control

Dyi‐Cheng Chen, Tian-Syung Lan, Shih-Ming Cho, Li-Chan Lu, Min-Chie Chiu
article en

Abstract

To mitigate agricultural crop losses caused by wildlife and unauthorized intrusions, an interactive orchard intrusion detection system combining edge-level automation and human-inthe-loop control was developed.The system integrates an Arduino Mega 2560 microcontroller, a servo-mounted 180° scanning ultrasonic sensor, multi-modal deterrents, and an Internet Protocol camera for real-time smartphone verification.Experimental results for performance evaluation showed a spatial detection accuracy of 94.0%, an average local response latency of 420 ms, and a false-positive rejection rate of 89.5% against environmental clutter such as wind-driven foliage.Despite these advantages, the system presented limitations: ultrasonic susceptibility to severe weather and dense vegetation, reliance on manual human verification under intermittent rural connectivity, and vulnerability to pest habituation and high power demands.To address these limitations, it is necessary to incorporate edge AI for autonomous threat classification, solarassisted energy harvesting for power-supply autonomy, and long-range-based decentralized communication protocols to ensure long-range operation.The improved system serves as a scalable, low-cost solution for precision agriculture.

Sensors and MaterialsVol. 38(10)
Hsing Wu University (TW), Hsiuping University of Science and Technology (TW), Tatung University (TW), National Changhua University of Education (TW)
Openalex Percentile: Top 15%
Smart Agriculture and AI
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.

Laika access coming soon