9月22日，管理中心工作人员通过悬崖上的水渠前往银杉群落监测样地。 9月23日，在金佛山黑叶猴远程视频监控点，工作人员李新在检查观测设备。 9月23日，工作人员李新（左）、王泳鳗在安装红外相机。 9月23日，在重庆金佛山国家级自然保护区管理事务中心，工作人员李新通过视频分析黑叶猴生活习性。 这是9月22日拍摄的人工繁育的银杉幼苗。 9月22日，在金佛山珍稀植物园，工作人员王泳鳗在为人工繁育的银杉幼苗浇水。 9月22日，在银杉群落监测样地，工作人员李新在检查调试监测系统。 9月23日拍摄的位于金佛山深处的银杉群落监测样地（无人机照片）。 9月23日，在重庆金佛山国家级自然保护区管理事务中心，工作人员韦冠吾在实验室进行植物繁育实验。 9月23日，在重庆金佛山国家级自然保护区管理事务中心，工作人员李新在通过远程视频监控观测黑叶猴的重点活动区域。 ...

Group 1: Ecological and Tourism Development - Qingxi Village in Fujian has transformed from an area with poor ecological conditions to a thriving tourist destination through the integration of agriculture, culture, and tourism projects [1][3] - The village has developed various tourism activities, including a rafting project, attracting a peak of over 500,000 visitors this year and generating tourism revenue exceeding 1.5 million yuan [5] Group 2: Environmental Monitoring and Protection - In Yunnan, the population of Asian elephants has stabilized at over 300 due to conservation efforts, with advanced technology being utilized for real-time monitoring of their activities and habitats [10][18] - A comprehensive monitoring and early warning system has been established, which has issued over 13,000 alerts since its trial run in 2020, effectively reducing human-elephant conflict incidents [18]

Core Viewpoint - The article highlights the significant contributions of Guo Rui and his team in the conservation and research of biodiversity in the Qingtian Peak National Nature Reserve, particularly focusing on the South China sika deer and the Anji salamander, showcasing successful habitat restoration and species reintroduction efforts [3][4][5]. Group 1: Conservation Efforts - Guo Rui has led innovative habitat restoration projects for the South China sika deer, resulting in a population increase to over 300 individuals [3][4]. - The reserve has successfully reintroduced over 80 sika deer into the wild, with 22 wearing unique tracking collars that provide real-time location data [4][5]. - The team has developed a method to artificially intervene in the breeding of the critically endangered Anji salamander, increasing the number of egg capsules by 35% [6][7]. Group 2: Research and Monitoring - The Qingtian Peak Nature Reserve employs a comprehensive wildlife monitoring system, including infrared cameras and sound monitoring devices, to track various species and their behaviors [8]. - The team has discovered and published over 20 new insect species, demonstrating the extensive biodiversity present in the region [9]. - Guo Rui's research has led to significant findings regarding the genetic diversity and breeding patterns of the sika deer through fecal sample analysis [4][5]. Group 3: Community Engagement and Future Goals - There has been a notable increase in public awareness and engagement in wildlife protection, with numerous reports of injured animals being rescued [10]. - Guo Rui aims to promote biodiversity conservation stories from Hangzhou on a global stage, particularly during the upcoming World Biosphere Reserve Conference in 2025 [10].

Core Insights - The article highlights the successful implementation of biodiversity observation in Jiangsu Baohua Mountain National Forest Park, utilizing 24 infrared cameras to monitor wildlife and document ecological health [1][2][3] Group 1: Biodiversity Observation - The biodiversity observation project began in 2024, with infrared cameras deployed across various habitats, including forests and valleys, to capture wildlife activity [2][3] - Notable sightings include the national second-class protected animal, the muntjac, and the rare weasel, indicating a thriving ecosystem [2][3] - The presence of common species like wild boars and South China rabbits suggests a stable forest ecosystem with ample food resources [3] Group 2: Technological Integration - The project represents a shift from traditional wildlife tracking methods to a technology-driven approach, enhancing observation efficiency and reducing human interference [3][4] - The integration of infrared cameras and traditional survey methods has created a comprehensive observation network, improving data collection on biodiversity [3][4] Group 3: Future Plans - The Jiangsu Environmental Science Institute plans to expand the biodiversity observation network across the province, optimizing the layout of observation points and incorporating advanced monitoring technologies [5] - The initiative aims to protect and preserve biodiversity, emphasizing the importance of safeguarding natural habitats for the sustainability of wildlife [5]

Group 1: Importance of Embodied AI and Multi-Sensor Fusion Perception - Embodied AI is a crucial direction in AI development, enabling autonomous decision-making and action through real-time perception in dynamic environments, with applications in autonomous driving and robotics [2][3] - Multi-sensor fusion perception (MSFP) is essential for robust perception and accurate decision-making in embodied AI, integrating data from various sensors like cameras, LiDAR, and radar to achieve comprehensive environmental awareness [2][3] Group 2: Limitations of Current Research - Existing AI-based MSFP methods have shown success in fields like autonomous driving but face inherent challenges in embodied AI, such as the heterogeneity of cross-modal data and temporal asynchrony between different sensors [3][4] - Current reviews on MSFP often focus on single tasks or research areas, limiting their applicability to researchers in related fields [4] Group 3: Overview of MSFP Research - The paper discusses the background of MSFP, including various perception tasks, sensor data types, popular datasets, and evaluation standards [5] - It reviews multi-modal fusion methods at different levels, including point-level, voxel-level, region-level, and multi-level fusion [5] Group 4: Sensor Data and Datasets - Various sensor data types are critical for perception tasks, including camera data, LiDAR data, and radar data, each with unique advantages and limitations [7][10] - The paper presents several datasets used in MSFP research, such as KITTI, nuScenes, and Waymo Open, detailing their characteristics and the types of data they provide [12][13][14] Group 5: Perception Tasks - Key perception tasks include object detection, semantic segmentation, depth estimation, and occupancy prediction, each contributing to the overall understanding of the environment [16][17] Group 6: Multi-Modal Fusion Methods - Multi-modal fusion methods are categorized into point-level, voxel-level, region-level, and multi-level fusion, each with specific techniques to enhance perception robustness [20][21][22][27] Group 7: Multi-Agent Fusion Methods - Collaborative perception techniques integrate data from multiple agents and infrastructure, addressing challenges like occlusion and sensor failures in complex environments [32][34] Group 8: Time Series Fusion - Time series fusion is a key component of MSFP systems, enhancing perception continuity across time and space, with methods categorized into dense, sparse, and hybrid queries [40][41] Group 9: Multi-Modal Large Language Model (MM-LLM) Fusion - MM-LLM fusion combines visual and textual data for complex tasks, with various methods designed to enhance the integration of perception, reasoning, and planning capabilities [53][54][57][59]

Core Insights - The article discusses the ongoing wildlife investigation in the Giant Panda National Park, focusing on the use of advanced technology to study the population and distribution of wild giant pandas and other species in the region [1][3]. Group 1: Research Methods - The investigation employs air and water environmental DNA sampling techniques to collect genetic information from the environment, providing a more accurate analysis of species and population distribution [3]. - The study combines traditional methods, such as the bite mark method, with modern techniques like fecal DNA targeting to enhance the accuracy of estimating wild panda populations and their distribution [5]. - A comprehensive monitoring system has been established, integrating aerial, terrestrial, and satellite technologies to improve the effectiveness and timeliness of wildlife monitoring [6]. Group 2: Geographic and Ecological Context - The Bai Shui Jiang area of the Giant Panda National Park spans 180,000 hectares and serves as a crucial ecological corridor connecting the provinces of Shaanxi and Sichuan [8]. - The park is actively engaged in joint patrols among the three provinces to protect the ecological environment of wild giant pandas and other rare animals [8].

Core Insights - The Gahai Wetland, located in Gansu Province, is part of the Gahai Zhecha National Nature Reserve, which plays a crucial role in wildlife monitoring and conservation efforts [1] - The protection station has deployed nearly 80 infrared cameras to monitor the activities of wildlife such as snow leopards and blue sheep [1][20] - The monitoring process involves retrieving and analyzing video footage from these cameras biannually, providing accurate data for wildlife conservation [1][6] Group 1 - The elevation of the protection station is 3,300 meters, with monitoring points set between 3,700 and 4,200 meters, where rare animals are often found [2][4] - The team successfully retrieved memory cards from 17 infrared cameras in one day, which will be processed and sent to the management center [6] - Staff members have dedicated nearly 10 years to their roles at the Gahai protection station, often facing challenging conditions [7] Group 2 - The infrared camera footage has captured various wildlife species, including the snow leopard, which is a first-class protected animal, and the blue sheep, which is a second-class protected animal [10][13][20] - The Gahai Zhecha National Nature Reserve has seen a gradual increase in biodiversity, with 354 species of wildlife recorded, including 19 first-class and 66 second-class protected species [20] - The area is becoming a harmonious habitat for wildlife due to enhanced conservation efforts [20]

Core Viewpoint - The article highlights the stable population of the critically endangered Chinese pangolin in the Dinghu Mountain National Nature Reserve, managed by the South China Botanical Garden, showcasing the reserve's unique biodiversity and conservation efforts [1][5]. Group 1: Conservation Efforts - The Dinghu Mountain National Nature Reserve, covering an area of 11.33 square kilometers, preserves nearly 400-year-old South Asian tropical monsoon evergreen broadleaf forests and seven other forest vegetation types [3]. - The reserve has been actively involved in biodiversity monitoring since 2016, with evidence of the Chinese pangolin's presence captured through infrared cameras since 2018 [5]. - Advanced technologies such as drones for forest patrols and artificial intelligence for fire detection are utilized for monitoring and research purposes [5]. Group 2: Global Contributions - The South China Botanical Garden is engaged in global biodiversity mapping and has contributed to the Global Plant Protection Strategy (2023-2030), sharing China's experience in plant conservation at international forums [6]. - Dinghu Mountain has established itself as a "laboratory for observation" for global ecologists, collaborating with over 20 countries on long-term research projects since 1988 [6]. - The reserve's "forest ecosystem carbon sink model" has been included in the United Nations climate change assessment reports, providing reference for developing countries in addressing climate crises [7]. Group 3: Biodiversity Significance - The Dinghu Mountain serves as a "gene pool" with 202 species named after it, and 44 species directly named "Dinghu," emphasizing its ecological importance [3]. - The presence of the Chinese pangolin, known as a "forest guardian," plays a crucial role in controlling ant populations, highlighting its ecological significance [5].