Optimal edge-cloud collaboration based strategies for minimizing valid latency of railway environment monitoring system

Response speed is vital for the railway environment monitoring system,especially for the sudden-onset disasters.The edge-cloud collaboration scheme is proved efficient to reduce the latency.However,the data characteristics and communication demand of the tasks in the railway environment monitoring system are all different and changeable,and the latency contribution of each task to the system is discrepant.Hence,two valid latency minimization strategies based on the edge-cloud collaboration scheme is developed in this paper.First,the processing resources are allocated to the tasks based on the priorities,and the tasks are processed parallly with the allocated resources to minimize the system valid latency.Furthermore,considering the differences in the data volume of the tasks,which will induce the waste of the resources for the tasks finished in advance.Thus,the tasks with similar priorities are graded into the same group,and the serial and parallel processing strategies are performed intra-group and inter-group simultaneously.Compared with the other four strategies in four railway monitoring scenarios,the proposed strategies proved latency efficiency to the high-priority tasks,and the system valid latency is reduced synchronously.The performance of the railway environment monitoring system in security and efficiency will be promoted greatly with the proposed scheme and strategies.

A Cost-Efficient Environment Monitoring Robotic Vehicle for Smart Industries

Environmental monitoring is essential for accessing and avoiding the undesirable situations in industries along with ensuring the safety of workers.Moreover,inspecting and monitoring of environmental parameters by humans lead to various health concerns,which in turn brings to the requirement of monitoring the environment by robotics.In this paper,we have designed and implemented a cost-efficient robotic vehicle for the computation of various environmental parameters such as temperature,radiation,smoke,and pressure with the help of sensors.Furthermore,the robotic vehicle is designed in such a way that it can be dually controlled by using the remote control along with the distant computer.In addition,contrary to the existing researches,the GSM modules are used to achieve the two-way long distance communication between the robotic vehicle and the distant computer.On the distant computer,the above-mentioned environmental parameters can be monitored along with controlling the robotic vehicle with the help of Graphical User Interface(GUI).In order to fulfill the given tasks,we have proposed two algorithms implemented at the robotic vehicle and the distant computer respectively in this paper.The final results validate the proposed algorithms where the above-mentioned environmental parameters can be monitored along with the smooth-running operation of the robotic vehicle.

Design and Implementation of Environment Monitoring and Alarm System for Broiler Breeding Based on Internet of Things

Environment plays a vital role in the breeding process of broilers. In order to effectively monitor and control the breeding environment of broilers, a broiler breeding environment monitoring and alarm system based on internet of things is studied and established. The system adopts the narrow band internet of things communication technology, and can transmit the temperature, humidity, illumination and ammonia and other environ-mental data in the chicken house remotely through terminal collection unified interface device. Meantime, it realizes the control of fans, wet cur-tains, small windows and illumination in the chicken house by threshold method. The system software is designed and implemented by C#, SQL Server, WeX5 and other development tools, including platform terminal and enterprise terminal. Since its operation, the system is featured by stable state, reliable data and timely alarm, which solves the problem of unified control of different sensors and realizes the effective control of house envi-ronment.

Cars as a Diffuse Network of Road-Environment Monitoring Nodes

The present paper aims to describe the conceptual idea to use cars as sensors to measure and acquire data related road environment. The parameters are collected using only standard equipment commonly installed and operative on commercial cars. Real sensors and car sub-systems (e.g. thermometers, accelerometers, ABS, ESP, and GPS) together with other “implicit” sensors (e.g. fog lights, windscreen wipers) acquire and contain information. They are shared inside an in-vehicle communication network using mainly the standard CAN bus and can be collected by a simple central node. This node can also be available on the market without too expensive costs thanks to some companies which business is devoted to car fleet monitoring. All the collected data are then geolocalized using a standard GPS receiver and sent to a remote elaboration unit, exploiting mobile network technologies such as GPRS or UMTS. A large number of cars, connected together in a diffuse Wireless Sensor Network, allow the elaboration unit to realize some info-layers put at the disposal of a car driver. Traffic, state of the road and other information about the weather can be received by car drivers using an ad hoc developed mobile application for smartphone which can give punctual information related to a specific route, previously set on the mobile phone navigator. The description of some experimental activities is presented, some technical points will be addressed and some examples of applications of the network of cars “as sensors” will be given.

A LEACH-Head Expected Frequency Appraisal Algorithm for Water-Environment Monitoring Networks

Water-environment monitoring network (WMN) is a wireless sensor network based real-time system, which collects, transmits, analyzes and processes water-environment parameters in large area. Both cluster selection mechanisms and energy saving strategies play an important role on designing network routing protocols for the WMN. Since those existing routing algorithms can not be used directly in the WMN, we thus propose an improved version of LEACH, a LEACH-Head Expected Frequency Appraisal (LEACH-HEFA) algorithm, for the WMN in this paper. Simulation results show that the LEACH-HEFA can balance the energy consumption of nodes, rationalize the clustering process and prolong the network lifetime significantly in the WMN. It indicates that the LEACH-HEFA is suitable to the WMN.

Sound-Environment Monitoring Method Based on Computational Auditory Scene Analysis

Monitoring techniques are a key technology for examining the conditions in various scenarios, e.g., structural conditions, weather conditions, and disasters. In order to understand such scenarios, the appropriate extraction of their features from observation data is important. This paper proposes a monitoring method that allows sound environments to be expressed as a sound pattern. To this end, the concept of synesthesia is exploited. That is, the keys, tones, and pitches of the monitored sound are expressed using the three elements of color, that is, the hue, saturation, and brightness, respectively. In this paper, it is assumed that the hue, saturation, and brightness can be detected from the chromagram, sonogram, and sound spectrogram, respectively, based on a previous synesthesia experiment. Then, the sound pattern can be drawn using color, yielding a “painted sound map.” The usefulness of the proposed monitoring technique is verified using environmental sound data observed at a galleria.

About Some Aspects of Use of Optical Sensors for Monitoring the Aquatic Environment

Multi-channel polarization optical technology is increasingly used for prompt monitoring of water systems.Optical devices during the assessment of water quality determine the intensity of light through the studied aquatic environment.Spectrophotometric devices measure the spectrum of weakening of light through the aquatic environment.Spectroellipsometric devices receive spectra in vertical and horizontal polarizations.The presented article develops an adaptive optical hardware and image system for monitoring water bodies.The system is combined.It consists of 2 parts:1)automated spectrophotometer-refractometer,and 2)adaptive spectroellipsometer.The system is equipped with a corresponding algorithmic and software,including algorithms for identifying spectral curves,databases and knowledge of spectral curves algorithms for solving reverse problems.The presented system is original since it differs from modern foreign systems by a new method of spectrophotometric and spectroellipsometric measurements,an original elemental base of polarization optics and a comprehensive mathematical approach to assessing the quality of a water body.There are no rotating polarization elements in the system.Therefore,this makes it possible to increase the signal-to-noise ratio and,as a result,improve measurement stability and simplify multichannel spectrophotometers and spectroellipsometers.The proposed system can be used in various water systems where it is necessary to assess water quality or identify the presence of a certain set of chemical elements.

Comprehensive early warning of rock burst utilizing microseismic multi-parameter indices

Rock bursts have become one of the most severe risks in underground coal mining and its early warning is an important component in the safety management. Microseismic(MS) monitoring is considered potentially as a powerful tool for the early warning of rock burst. In this study, an MS multi-parameter index system was established and the critical values of each index were estimated based on the normalized multi-information warning model of coal-rock dynamic failure. This index system includes bursting strain energy(BSE) index, time-space-magnitude independent information(TSMII) indices and timespace-magnitude compound information(TSMCI) indices. On the basis of this multi-parameter index system, a comprehensive analysis was conducted via introducing the R-value scoring method to calculate the weights of each index. To calibrate the multi-parameter index system and the associated comprehensive analysis, the weights of each index were first confirmed using historical MS data occurred in LW402102 of Hujiahe Coal Mine(China) over a period of four months. This calibrated comprehensive analysis of MS multi-parameter index system was then applied to pre-warn the occurrence of a subsequent rock burst incident in LW 402103. The results demonstrate that this multi-parameter index system combined with the comprehensive analysis are capable of quantitatively pre-warning rock burst risk.

Atmospheric environment monitoring technology and equipment in China:A review and outlook

Accurate monitoring of the atmospheric environment and its evolution are important for understanding the sources,chemical mechanisms,and transport processes of air pollution and carbon emissions in China,and for regulatory and control purposes.This study gives an overview of atmospheric environment monitoring technology and equipment in China and summarizes the major achievements obtained in recent years.China has made great progress in the development of atmospheric environment monitoring technology and equipment with decades of effort.The manufacturing level of atmospheric environment monitoring equipment and the quality of products have steadily improved,and a technical&production system that can meet the requirements of routine monitoring activities has been initiated.It is expected that domestic atmospheric environment monitoring technology and equipment will be able to meet future demands for routine monitoring activities in China and provide scientific assistance for addressing air pollution problems.

A Multi-Agent System for Environmental Monitoring Using Boolean Networks and Reinforcement Learning

Distributed wireless sensor networks have been shown to be effective for environmental monitoring tasks,in which multiple sensors are deployed in a wide range of the environments to collect information or monitor a particular event,Wireless sensor networks,consisting of a large number of interacting sensors,have been successful in a variety of applications where they are able to share information using different transmission protocols through the communication network.However,the irregular and dynamic environment requires traditional wireless sensor networks to have frequent communications to exchange the most recent information,which can easily generate high communication cost through the collaborative data collection and data transmission.High frequency communication also has high probability of failure because of long distance data transmission.In this paper,we developed a novel approach to multi-sensor environment monitoring network using the idea of distributed system.Its communication network can overcome the difficulties of high communication cost and Single Point of Failure(SPOF)through the decentralized approach,which performs in-network computation.Our approach makes use of Boolean networks that allows for a non-complex method of corroboration and retains meaningful information regarding the dynamics of the communication network.Our approach also reduces the complexity of data aggregation process and employee a reinforcement learning algorithm to predict future event inside the environment through the pattern recognition.

An SNN Ontology Based Environment Monitoring Method for Intelligent Irrigation System

In order to realize high precision of environment parameters detection in irrigation applications,a sensor and sensor network(SSN) ontology based data fusion method is proposed.An SSN sub-ontology for soilstate monitoring is revised,which includes the sensing devices hierarchies and measurement properties selection according to the detection feature interests.As for sensor data processing,a tuning data method by data pool filtering and clustering is adopted,as well as a useful data fusion method for multi-sensor system.The testing results show that both the accuracy and efficiency of the proposed method are higher after related filtering and clustering process,which enables a thorough monitoring for intelligent irrigation systems and can be extended into environment monitoring and control applications.

Hybrid Deep Learning Enabled Air Pollution Monitoring in ITS Environment

Intelligent Transportation Systems(ITS)have become a vital part in improving human lives and modern economy.It aims at enhancing road safety and environmental quality.There is a tremendous increase observed in the number of vehicles in recent years,owing to increasing population.Each vehicle has its own individual emission rate;however,the issue arises when the emission rate crosses a standard value.Owing to the technological advances made in Artificial Intelligence(AI)techniques,it is easy to leverage it to develop prediction approaches so as to monitor and control air pollution.The current research paper presents Oppositional Shark Shell Optimization with Hybrid Deep Learning Model for Air Pollution Monitoring(OSSOHDLAPM)in ITS environment.The proposed OSSO-HDLAPM technique includes a set of sensors embedded in vehicles to measure the level of pollutants.In addition,hybridized Convolution Neural Network with Long Short-Term Memory(HCNN-LSTM)model is used to predict pollutant level based on the data attained earlier by the sensors.In HCNN-LSTM model,the hyperparameters are selected and optimized using OSSO algorithm.In order to validate the performance of the proposed OSSO-HDLAPM technique,a series of experiments was conducted and the obtained results showcase the superior performance of OSSO-HDLAPM technique under different evaluation parameters.

Strengthened Monitoring of H5 Avian Influenza Viruses in External Environment in Hubei, 2018

The contamination status of H5 avian influenza viruses and distribution of subtypes of H5N1 and H5N6 in poultry-related environment of Hubei areas were investigated.Urban and rural live poultry markets,poultry farms,intensive livestock farms and other monitoring types of 103 counties in 17 cities were selected in Hubei.Wiping samples from cage surface,wiping samples from chopping board,fecal specimens and other environmental samples were collected and tested by real-time RT-PCR using primers and probes of influenza A,avian influenza of H5,N1 and N6 from December 2017 to March 2018.The avian influenza virus positive rate was compared among different monitoring sites,samples,time and regions.Totally,7132 environmental samples were collected in 1634 monitoring points with a positive rate of 2.24%.The positive rate of H5 avian influenza virus was the highest in urban and rural live poultry markets(3.44%,x^2=61.329,P<0.05)in 6 monitoring sites and wiping samples from chopping board(5.46%,x^2=67.072,P<0.05)in 6 sample types.H5N6 avian influenza viruses were detected more in eastern than western Hubei,and H5N6 avian influenza viruses were detected only in Xiangyang city of western Hubei.There were important high-risk places of human infection with H5 avian influenza virus in urban and rural live poultry markets and the poultry slaughtering plants.H5N6 has been the predominant subtype of H5 avian influenza viruses in the eastern and western Hubei and H5N6 avian influenza viruses were still present in a few areas of Hubei.Outbreaks of human H5N1 and H5N6 avian influenza remain at risk in Hubei province.

Research on Distribution of Electromagnetic Environment around Substations and Optimization Layout of On-line Monitoring

The characteristics and distribution law of electromagnetic environment around substations with different levels of voltage were studied,and the main influencing factors were discussed. Meanwhile,a scheme for locating monitoring points suitable for an on-line monitoring system of electromagnetic environment was proposed.

A Design of Modern Greenhouse Environmental Monitoring System

Based on the problems in the current greenhouse environmental monitoring system such as difficult connection layout,low flexibility and high costs,this paper builds the greenhouse environmental monitoring system based on wireless sensor network,and designs the sensor nodes and gateway nodes. The sensor nodes of this system are responsible for collecting environmental parameters and sending the data to gateway nodes via wireless sensor network. And the gateway nodes transmit the data to the remote monitoring platform. The microprocessor module of node hardware uses MSP430F149 microprocessor for data processing and control; wireless communication module consists of nRF905 RF chip and peripheral circuit,responsible for transmitting and receiving data; sensor module uses AM2301 sensor for data measurement; the power supply module uses the circuit consisting of LT1129-3. 3,LT1129-5 and Max660 to provide 3. 3 and ± 5V power. The C language development is employed for wireless routing protocol of node and time synchronization algorithm,to achieve node data acquisition and processing,rule forwarding and remote transmission. Remote monitoring software uses NET. ASP,HTML and C# development to provide visual WEB mode remote data management platform for users. The system goes through networking testing in greenhouse in Xining City,and test results show that the system operation is stable and reliable,and the average network packet loss rate is 2. 4%,effectively solving the problems in greenhouse environmental monitoring system and meeting the application requirements of greenhouse cultivation environmental monitoring.

Radioactivity monitoring in environmental water and air around QNPP

Results of environmental radioactivity monitoring around Qinshan Nuclear Power Plant (QNPP) are reported in this paper. From 1992 to 2005, concentrations of 90Sr, 137Cs and 3H in terrestrial freshwater are (4.4±1.7) mBq·L-1, (0.3±0.1) mBq·L-1 and (1.6±0.5) Bq·L-1, respectively, and (2.8±2.4) Bq·L-1 of 3H in rainwater. Concentrations of 90Sr, 137Cs and 3H in the seawater samples collected from sea area nearby QNPP are (5.4±4.1) mBq·L-1, (0.7±0.2) mBq·L-1 and (1.0±0.5) Bq·L-1, respectively. Concentrations of 90Sr, 137Cs and 3H in the total waste water discharged from NPP-I are (4.0±1.8) m Bq·L-1, (1.0±0.5) mBq·L-1 and (2.8±2.2) Bq·L-1, respectively, and (1.4±0.4) Bq·L-1 of 3H in seawater sampled from No.1 outlet. Atomspheric 3H concentration in 1993～2005 at two monitoring sites is (78.9±96.3) and (64.2±40.2) mBq·m-3, respectively, with an increasing trend after 2003. Atmospheric 14C concentrations at the two sites are in the same levels as the background and data of the reference site.

Thoughts on Integrated Monitoring of Ecological Environment at Provincial Level

The Law of Soil and Water Conservation entitles the administrations of water resources at various level to monitor ecological environment and to proclaim status of soil erosion periodically.Monitoring units of soil and water conservation approved by local governments are obliged to undertake this work.How to develop a monitoring program needs an overall and long-term concept.Particularity and objectives of ecological environment monitoring was discussed. Monitoring at provincial level may be divided into two levels:province-wide and at project level. Those indicators meaningful,sensitive to any disturbances,and simple to measure may be selected to test status of ecosystem stability and health.It makes sense to have an integrated sampling design,to set up permanent observation plots and to collect data, so that to have a relative timely,accurate understanding of ecosystems in the province.A program regarding sampling design,field methods, data analysis,documentation and implementation was detailed.

Research Progress of On-line Monitoring Technology for Electromagnetic Environment of Power Transmission and Transformation Projects

Based on the collection of relevant literature and cases,the research and application status of on-line monitoring technology for electromagnetic environment of power transmission and transformation projects at home and abroad were introduced.Moreover,the problems existing in the on-line monitoring of electromagnetic environment were expounded,and the development prospect was forecasted.

Investigation on environment monitoring system for a combination of hydroponics and aquaculture in greenhouse

This work develops a distributed environmental monitoring system for the combination of hydroponics and aquaculture based on the internet of things technology,which mainly includes the information perception layer,the information transmission layer and the sys-tem architecture.The system has employed multiple sensors terminal to real-time acqui-sition,including air and water temperatures,dissolved oxygen etc.LoRa protocol is suitable for sending small data and the 4G was employed to collect data and send to the cloud plat-form.Java is used to develop background applications,to access cloud platforms and local data processing.Based on the collection and processing of environmental data and cloud service platform,the mobile application program client and remote login desktop have been developed.It has been implemented and tested in Tongzhou,Beijing for 3 months in 2020.The results showed the proposed monitoring system stability for overall operation and accuracy data transmission,which can support the actual hydroponics and aquacul-ture production management.After analysis of monitoring data collected from the devel-oped monitoring system,indoor air and water temperature have the obvious correlation with atmospheric pressure(0.7 and 0.9)and outdoor temperature(1.0 and 0.9),respectively.