山地生态养殖场管理山羊闯入分析数据

随着人们生活质量的极大改善，山地生态养殖的家畜家禽已经成为市场上备受欢迎的品种,同时也备受人们的喜爱。物联网技术的发展也为养殖场所提供了更完善的安防监管效果，养殖场管理山羊闯入分析数据，是基于传感器和高清摄像头的养殖安防管理系统采集日常监测数据，包括识别时间、区域位置、养殖场、猪舍编号、猪数量（头）、鸡数量（羽）、设备编号、告警类型等数据，实时监测日常养殖场内异常闯入情况，在发生突发状况时，快速了解现场状况，定位闯入所在位置，及时处理，保障养殖场的动物日常生存。吕梁地区黄土高原农村地区，很多家庭会散养山羊补贴家用，时长会放养再 山里，闯入养殖场会对养殖食物等构成威胁。定期对告警数据设备抓图所反映的现场情况进行分析，方便管理人员对山羊闯入行为进行日常监管，预防发生重大的养殖安全事件，为养殖设备维护和管理提供支持；根据一段时间内告警的数据规模、现场图片、时间等，帮助区域内的动物养殖企业了解该地的具体情况，研判市场营销和生产投入计划；公开报道一段时间内告警数据，可以掌握区域内的野生动物生态，为合地区管理和治理野生动物危险发生做参考预计。1、从基于传感器和高清摄像头的养殖安防管理系统采集日常监测数据，包括识别时间、区域位置、养殖场、猪舍编号、存栏（头）、设备编号、告警类型、抓取图片等数据。2、首先对敏感信息进行加密处理，对数据进行加工。基于传感器和高清摄像头识别，在识别到有异常闯入时，开启摄像头拍摄，并将图片和视频段上传到云服务器。通过基于深度学习神经网络训练的目标检测算法进行图片检测，输出图片相关属性，图片属性包含type、score，对输出的type进行识别，若目标类型type=16，表示有山羊闯入，系统会向平台发送闯入告警，需要进行人工干预。管理人员就能快速了解现场状况，定位闯入所在位置，及时处理，保障养殖场的动物日常生存。

With the significant improvement of people's quality of life, livestock and poultry from mountainous ecological breeding have become highly sought-after varieties in the market and widely favored by consumers. The development of the Internet of Things (IoT) has also provided more comprehensive security supervision capabilities for breeding farms. The data for farm goat intrusion analysis is collected daily by the aquaculture security management system based on sensors and high-definition (HD) cameras, including recognition time, regional location, farm information, pigsty number, pig count (head), chicken count (feather), equipment number, alarm type, captured images, and other related data. This system enables real-time monitoring of abnormal intrusions in daily farm operations, allowing rapid access to on-site conditions, localization of intrusion locations, and timely response to ensure the daily survival of livestock and poultry in the farms.

In rural areas of the Loess Plateau in Lüliang Prefecture, many households raise free-range goats to supplement their household income, as these goats are often grazed in mountainous areas and may intrude into breeding farms, threatening the feed and other resources for the farmed livestock. Regular analysis of the on-site conditions reflected in the images captured by alarm data equipment helps managers conduct daily supervision of goat intrusions, prevent major aquaculture safety incidents, and provide support for aquaculture equipment maintenance and management. By analyzing the scale of alarm data, on-site images, and time stamps over a certain period, this dataset can help local livestock and poultry breeding enterprises understand the local specific conditions and formulate marketing and production investment plans. Publicly releasing the alarm data over a certain period can help grasp the regional wildlife ecology, providing a reference for regional wildlife hazard management and governance.

1. Daily monitoring data is collected from the aquaculture security management system based on sensors and high-definition cameras, including recognition time, regional location, farm information, pigsty number, inventory count (head), equipment number, alarm type, and captured images.

2. First, sensitive information is encrypted and the data is preprocessed. When an abnormal intrusion is detected via the sensors and HD cameras, the camera is activated to capture footage, and the images and video clips are uploaded to the cloud server. Target detection algorithms trained via deep learning neural networks are used to detect the captured images, outputting relevant image attributes including type and score. If the target type is 16, it indicates a goat intrusion, and the system sends an intrusion alarm to the platform, requiring manual intervention. Managers can then quickly understand the on-site situation, locate the intrusion location, and handle it promptly to ensure the daily survival of livestock and poultry in the breeding farms.

搜集汇总

数据集介绍

特点

该数据集为山地生态养殖场管理山羊闯入分析数据，包含9955条记录，每日更新，用于实时监测养殖场山羊闯入情况，保障养殖场安全。数据通过深度学习算法检测山羊闯入并发送告警，支持养殖场安防管理。