山地生态养殖场管理獾子闯入分析数据

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，养殖场管理獾子闯入分析数据，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。吕梁地区黄土高原獾子数量较多，且为群体活动，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，方便管理人员对獾子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=7，表示有獾子闯入，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 continuous improvement of people's living standards, livestock and poultry from mountainous ecological farming have become highly popular and well-loved varieties in the market. The development of Internet of Things (IoT) technology has provided more robust security and supervision capabilities for livestock farms. The badger intrusion analysis data for farm management is collected from daily monitoring data via a breeding security management system based on sensors and high-definition (HD) cameras. These daily monitoring data include recognition time, regional location, farm name, pigsty number, number of pigs (unit: head), number of chickens (unit: feather), device ID, alarm type and other related information, enabling real-time monitoring of abnormal intrusions within the farm. When emergencies occur, farm managers can quickly gain situational awareness, pinpoint the exact intrusion location and take timely actions, thereby ensuring the daily survival of livestock and poultry on the farm.

The Lvliang area on the Loess Plateau has a large population of badgers, which move in groups and pose threats to breeding feed and other resources. Regular analysis of on-site situations reflected by alarm data and captured images facilitates daily supervision of badger intrusions by farm managers, preventing major livestock farming safety incidents and providing support for the maintenance and management of breeding equipment. Based on the alarm data scale, on-site images, time stamps and other information over a certain period, local livestock breeding enterprises can gain a clear understanding of the local specific conditions, and make informed decisions on marketing and production investment plans. Public disclosure of alarm data over a period of time helps to grasp the wildlife ecology within the region, providing references for regional management and the prevention and control of wildlife hazard incidents.

1. Daily monitoring data is collected from the breeding security management system based on sensors and high-definition cameras, including recognition time, regional location, farm name, pigsty number, livestock inventory count (unit: head), device ID, alarm type, captured images and other related data.
2. Sensitive information is first encrypted and the collected data is preprocessed. When abnormal intrusions are detected via sensors and high-definition cameras, the cameras are activated for shooting, and the captured images and video clips are uploaded to the cloud server. Image detection is performed using a target detection algorithm trained on deep learning neural networks, which outputs relevant attributes of the images including "type" and "score". By identifying the output "type" value, if the target type "type=7", it indicates a badger intrusion, and the system will send an intrusion alarm to the platform requiring manual intervention. This allows farm managers to quickly gain situational awareness, pinpoint the intrusion location, respond timely and ensure the daily survival of livestock and poultry on the farm.

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獾子闯入分析数据，包含9955条记录，每日更新，用于实时监测养殖场内的异常闯入情况，特别是獾子的闯入，以保障养殖安全。数据通过传感器和高清摄像头采集，并利用深度学习算法进行目标检测和告警。