Korea deploys AI drones to stop wild boar incursions into residential areas

Korea has deployed AI-powered drones and thermal imaging to stop wild boars from entering residential areas around northern Seoul. The National Institute of Biological Resources said Thursday that the system tracks boars in real time and alerts authorities when they enter high-risk zones. The ministry plans to roll out the software and guidelines nationwide starting in November.

Seoul’s fire headquarters logged nearly 500 wild boar dispatches in 2025, with hundreds more in previous years.

Researchers trained the system with more than 12,000 wild boar images for the deep-learning model.

The surveillance network uses autonomous drones, closed-circuit cameras, thermal surveillance cameras, and traps to detect boar movements.

During pilot testing around Mount Bukhan, the system tracked boar activity in real time and transmitted warning feeds to central monitors without delay.

The system also builds predictive habitat maps from movement logs to help municipal workers understand seasonal migration routes.

Published Oct 1, 2026 3:55 pm KST

Real-time thermal tracking detects animals near capital's borders

A wild boar foraging near Seoul is automatically detected and monitored by an artificial intelligence-enabled surveillance camera, Sept. 5. Courtesy of Ministry of Climate, Energy and Environment

High above the forested slopes encircling northern Seoul, autonomous drones are scanning the brush for an unexpected urban threat: wild boars.

Equipped with artificial intelligence (AI) and real-time thermal imaging, the unmanned aircraft are part of a new high-tech surveillance system launched by Korea to intercept roaming wildlife before they stray into crowded city areas.

Korea’s National Institute of Biological Resources said Thursday that it developed the AI-driven monitoring system to track wild boars in real time. By integrating autonomous drones and closed-circuit cameras with deep-learning algorithms, the platform detects animal movements, predicts potential travel corridors and alerts local authorities the instant a boar crosses into high-risk zones.

The initiative represents a fundamental shift in urban wildlife management.

Historically, local officials have relied on emergency reporting after boars are spotted near homes, parks or roads — a reactive approach that leaves little time for prevention. Seoul’s fire headquarters logged nearly 500 wild boar dispatches in 2025 alone, alongside hundreds more in previous years.

"The significance of this technology lies in shifting our response from reactive measures to proactive monitoring," said Yoo Ho, president of the National Institute of Biological Resources. "We are establishing a system that looks ahead at high-risk areas to enable swift field intervention."

To train the system, researchers fed more than 12,000 images of wild boars into a deep-learning model. Connected to autonomous drones sweeping a 3-kilometer radius as well as thermal surveillance cameras and traps, the system scans video feeds for boar profiles. When a match is flagged, an automated alert sends exact coordinates and match probability rates directly to emergency responders.

During pilot testing around Mount Bukhan, a popular national park bordering dense residential districts in northern Seoul, the system successfully tracked boar activity in real time. Drones cruising above rugged terrain captured nighttime infrared imagery, pinpointing animals foraging in the brush and transmitting warning feeds to central monitors without delay.

Beyond immediate dispatching, the system aggregates movement logs to build predictive habitat maps, giving municipal caseworkers a clearer view of seasonal migration routes.

Starting in November, the ministry said it will roll out the surveillance software and operational guidelines to local governments nationwide, offering a high-tech blueprint for cities struggling with human-wildlife conflicts.

As urban expansion continues to encroach on natural habitats across Korea, officials hope the AI surveillance network will establish a safer, more sustainable balance between city residents and local wildlife.

This article was published with the assistance of generative AI and edited by The Korea Times.

韩国已部署人工智能无人机和热成像技术，以阻止野猪进入首尔北部居民区。韩国国立生物资源研究所周四表示，该系统可实时追踪野猪，并在野猪进入高风险区域时向有关部门发出警报。该部计划从11月起在全国范围内推广该软件和相关指南。

首尔消防总部记录显示，2025 年共处理了近 500 起野猪扑杀事件，而前几年也有数百起。

研究人员使用超过 12,000 张野猪图像对深度学习模型进行训练。

该监控网络利用自主无人机、闭路电视摄像机、热成像监控摄像机和陷阱来探测野猪的活动。

在布罕山附近的试点测试中，该系统实时跟踪野猪活动，并立即向中央监控器发送预警信息。

该系统还能根据迁徙日志构建预测性栖息地地图，帮助市政工作人员了解季节性迁徙路线。

发布于2026年10月1日下午3:55（韩国标准时间）

实时热成像追踪技术探测到首都边界附近的动物

9月5日，一头在首尔附近觅食的野猪被人工智能监控摄像头自动探测并监控。图片由韩国气候、能源和环境部提供。

在环绕首尔北部森林覆盖的山坡上空，自主无人机正在扫描灌木丛，寻找意想不到的城市威胁：野猪。

这些无人机配备了人工智能（AI）和实时热成像技术，是韩国推出的一项新型高科技监视系统的一部分，旨在拦截游荡的野生动物，防止它们误入拥挤的城市地区。

韩国国立生物资源研究所周四表示，他们开发了一套人工智能驱动的野猪实时监测系统。该平台将自主无人机、闭路电视摄像头与深度学习算法相结合，能够检测动物的活动轨迹，预测潜在的迁徙路线，并在野猪进入高风险区域的第一时间向地方当局发出警报。

该举措标志着城市野生动物管理方式的根本性转变。

历史上，地方官员通常依赖于在居民区、公园或道路附近发现野猪后的紧急报告——这种被动应对的方式几乎没有留下任何预防措施。仅2025年一年，首尔消防总部就记录了近500起野猪出警事件，而此前几年也发生过数百起。

“这项技术的意义在于将我们的应对措施从被动反应转变为主动监测，”国立生物资源研究所所长柳浩表示，“我们正在建立一个能够提前识别高风险区域的系统，以便迅速采取现场干预措施。”

为了训练这套系统，研究人员将超过12000张野猪图像输入到深度学习模型中。该系统与在3公里半径范围内进行扫描的自主无人机、热成像监控摄像头和陷阱相连，扫描视频流以寻找野猪的特征。一旦发现匹配目标，系统会自动发出警报，将精确坐标和匹配概率直接发送给应急人员。

在首尔北部毗邻人口密集住宅区的热门国家公园北汉山附近进行的试点测试中，该系统成功实现了对野猪活动的实时追踪。无人机在崎岖地形上空盘旋，拍摄夜间红外图像，精确定位在灌木丛中觅食的动物，并将预警信息实时传输至中央监控系统。

除了立即调度外，该系统还会汇总移动日志以构建预测栖息地地图，使市政工作人员能够更清楚地了解季节性迁徙路线。

该部表示，从 11 月开始，将向全国地方政府推广监控软件和操作指南，为受人兽冲突困扰的城市提供高科技蓝图。

随着城市扩张不断侵占韩国各地的自然栖息地，官员们希望人工智能监控网络能够在城市居民和当地野生动物之间建立更安全、更可持续的平衡。

本文由生成式人工智能协助发布，并由《韩国时报》编辑。