Suggestions on Conducting Ecological Emergency Monitoring

The importance of ecological environment monitoring was discussed,and the problems in ecological emergency environment monitoring were analyzed.Based on this,some suggestions were put forward for ecological environment emergency monitoring,in order to provide effective reference for relevant staff.

Study on the Automatic Generation of Emergency Monitoring Scheme of Atmospheric Pollution Based on GIS

Based on emergency monitoring work flow analysis of atmospheric pollution incidents, key technical problems involved in the atmospheric pollution monitoring scheme based on GIS was studied, including the orientation of the accident site, the inquiry of the distribution of the emergency monitoring units and the groups of experts and the determination of the shortest path of emergency monitoring researchers and equipments arriving to the accident site as well as the integrated technology of Gaussian model with GIS which was mainly researched. The automatic prototype system of the emergency monitoring optimized scheme of the atmospheric pollution based on GIS was analyzed with the case of atmospheric pollution accident in Kunshan.

Panzhihua Airport Landslide (Oct. 3rd 2009) and an Emergency Monitoring and Warning System Based on the Internet of Things

Panzhihua city （26°O5＇-27°21＇N, 101°OS＇- 102°15＇E）, located in a mountainous area, is one of the large cities in Sichuan province, China. A landslide occurred in the filling body of the eastern part of the Panzhihua airport on October 3, 2009 （hereafter called the lo.3 landslide）. We conducted field survey on the landslide and adopted emergency monitoring and warning models based on the Internet of Things （loT） to estimate the losses from the disaster and to prevent a secondary disaster from occurring. The results showed that four major features of the airport site had contributed to the landslide, i.e, high altitude, huge amount of filling rocks, deep backfilling and great difficulty of backfilling. The deformation process of the landslide had six stages and the unstable geological structure of high fillings and an earthquake were the main causes of the landslide. We adopted relative displacement sensing technology and Global System for Mobile Communications （GSM） technology to achieve remote, real-time and unattended monitoring of ground cracks in the landslide. The monitoring system, including five extensometers with measuring ranges of 200, 450 and 7oo mm, was continuously working for 17 months and released 7 warning signals with an average warning time of about 26 hours. At 10 am on 6 December 2009, the system issued a warning and on-site workers were evacuated and equipment protected immediately. At 2：20 medium-scale collapse monitoring site, which proved the reliability pm on 7 December, a occurred at the No. 5 justified the alarm and and efficiency of the monitoring system.

Evolutionary PSO-based emergency monitoring geospatial edge service chain in the emergency communication network

Emergency communication networks play a vital role in disaster monitoring,transmission,and application during disaster emergency response(DER),however,the performance and stability of edge nodes in the emergency communication networks are often weak due to limited communication and computation resources.This weakness directly affects the quality,of service(Qos)of the geospatial edge service(GES)chains involved in emergency monitoring.Existing research predominantly addresses service compositions in stable environments,neglecting the aggregation of efficient and robust GES chains in emergency communication networks.This study proposes an evolutionary_particie swarm optimization(EPSO)-based emergency monitoring GES chain in an_emergency communication network.it includes a GES chain model of emergency environment monitoring for tailing areas,as well as the designs of the particle chromosome encoding method,fitness evaluation model,and particle chromosome swarm update operators of the EPSO-based GES chain.Finally,the study conducts emergency environment monitoring experiments for tailing areas using the proposed method.Experiments results demonstrate that the proposed method significantly enhances the efficiency,stability,and reliability of emergency monitoring GEs chains in the emergency communication network.This is crucial to providing fast and reliable services for DER during natural disasters.

Efficient Deep Learning Framework for Fire Detection in Complex Surveillance Environment

To prevent economic,social,and ecological damage,fire detection and management at an early stage are significant yet challenging.Although computationally complex networks have been developed,attention has been largely focused on improving accuracy,rather than focusing on real-time fire detection.Hence,in this study,the authors present an efficient fire detection framework termed E-FireNet for real-time detection in a complex surveillance environment.The proposed model architecture is inspired by the VGG16 network,with significant modifications including the entire removal of Block-5 and tweaking of the convolutional layers of Block-4.This results in higher performance with a reduced number of parameters and inference time.Moreover,smaller convolutional kernels are utilized,which are particularly designed to obtain the optimal details from input images,with numerous channels to assist in feature discrimination.In E-FireNet,three steps are involved:preprocessing of collected data,detection of fires using the proposed technique,and,if there is a fire,alarms are generated and transmitted to law enforcement,healthcare,and management departments.Moreover,E-FireNet achieves 0.98 accuracy,1 precision,0.99 recall,and 0.99 F1-score.A comprehensive investigation of various Convolutional Neural Network(CNN)models is conducted using the newly created Fire Surveillance SV-Fire dataset.The empirical results and comparison of numerous parameters establish that the proposed model shows convincing performance in terms of accuracy,model size,and execution time.

便携式GC-MS在应急监测工作中的应用

It′s very useful tools for an instant analysis of organic pollutants monitoring using the HAPSITE portable GC-MS.It discusses how to use HAPSITE portable GC-MS in emergency monitoring and treatment.

Key emergency response technologies for abrupt air pollution accidents in China

Abrupt air pollution accidents can endanger people’s health and destroy the local ecological environment.The appropriate emergency response can minimize the harmful effects of accidents and protect people’s lives and property.This paper provides an overview of the key emergency response technologies for abrupt air pollution accidents around the globe with emphasis on the major achievements that China has obtained in recent years.With decades of effort,China has made significant progress in emergency monitoring technologies and equipment,source estimation technologies,pollutant dispersion simulation technologies and others.Many effective domestic emergency monitoring instruments(e.g.,portable DOAS/FT-IR systems,portable FID/PID systems,portable GC-MS systems,scanning imaging remote sensing systems,and emergency monitoring vehicles)had been developed which can meet the demands for routine emergency response activities.A monitoring layout technique combining air dispersion simulation,fuzzy comprehensive evaluation,and a post-optimality analysis was proposed to identify the optimal monitoring layout scheme under the constraints of limited monitoring resources.Multiple source estimation technologies,including the forward method and the inversion method,have been established and evaluated under various scenarios.Multi-scale dynamic pollution dispersion simulation systems with high temporal and spatial resolution were further developed.A comprehensive emergency response platform integrating database support,source estimation,monitoring schemes,fast monitoring of pollutants,pollution predictions and risk assessment was developed based on the technical idea of"source identification-model simulation-environmental monitoring"dynamic interactive feedback.It is expected that the emergency response capability for abrupt air pollution accidents will gradually improve in China.

Sci-Tech

China Launches Space Junk Monitoring Center China,on June 8,launched a space junk monitoring center to protect its spacecraft in orbit.The center,which is managed by the State Administration of Science,Technology and Industry for National Defense（SASTIND）and the Chinese Academy of Sciences（CAS）,will track and monitor nearearth objects and space debris.