Spatial and temporal processes visualization for marine environmental data using particle system

Regarding the data collection process for a comprehensive automated environmental monitoring and precaution platform, this paper first analyses the key issues and challenges, including setting of monitoring targets, heterogeneity of monitoring equipments, diversity of communication methods, and online monitoring. Based on this, an embedded real-time environmental data collecting system is proposed. The contributions of the paper are as follows: we have designed an embedded environmental data collector which supports three collecting modes; we have proposed a novel integration technique for heterogeneous monitoring devices and an adaptive internetworking approach. The proposed system is a component of a distributed environmental monitoring platform which will be deployed in Guangzhou city.

Aiming at enhancing the rendering performance of complex natural phenomena such as smoke diffusion, a rendering approach based on Compute Unified Device Architecture (CUDA) and particle system is designed and implemented in this paper. The strategy that host memory resource is mapped to the CUDA memory address, and the technique which uses two-dimensional textured planar graph to simulate the three-dimensional effect combined with CUDA parallel computing (the parallel billboard technique) are integrated applied. The simulation results demonstrate that this proposed approach can effectively accelerate the rendering process, save memory usage, and achieve impressive visual effects.

At present, the environmental monitoring of the substation suffers from complex wiring, low intelligence, high staff work intensity, and a lack of information-based overall management. Moreover, the distribution of substations is relatively scattered, making it complex and costly to set up a dedicated communication network. In response to these problems, this paper combines modern communication technology, sensor technology, and mobile intelligent terminal development technology to study an overall information-based substation environmental monitoring system. The monitoring system proposed in this paper includes a main controller, a data collection terminal, and a mobile communication terminal. The environmental data collected by the main controller is sent to the server through the communication method of subscription and substation using wireless communication technology, and the interface of the mobile communication terminal can display indoor environmental monitoring data. When the environmental data of the Substation exceeds the set threshold value to issue an early warning alert, the user can control it remotely through the mobile communication terminal to improve the indoor environment of the Substation. The system has a simple operation interface, low power consumption, and strong expansion compatibility, which effectively realizes remote monitoring and control of the substation environment and has good engineering application value.

Big Data analytics's integration with Internet of Things (IoT) and Cloud Computing (CC) technologies is explored in the present investigation to provide a robust framework for evolving environmental data management. The use of IoT sensors and devices allows for the continuous collection, transmission, and processing of real-time environmental data, and, with the aid of big data analytics, this massive volume of data can be handled, stored, and analyzed effectively, producing insights that were previously impossible. The rapid expansion of data produced by many sources in today's connected world presents both advantages and challenges for environmental data management. For large-scale applications, the usage of cloud computing guarantees data accessibility, scalability, and flexibility. The combined approach facilitates environmentally sound management by enabling predictive modeling, real-time monitoring, and intelligent decision-making. Better fine-grained structure, increased flexibility, and accuracy are all demonstrated by the notable advancement in IoT-CC technology. By tackling issues like pollution, resource management, and climate change, this integration seeks to improve the precision, promptness, and efficacy of environmental monitoring systems. The suggested methodology demonstrates the approach's potential influence on upcoming environmental data management procedures as well as its contribution to intelligent, sustainable ecosystems.

Considerable attention has been directed towards techniques and procedures which facilitate the high quality of field-collected ambient environmental data. This study addresses the quality control methods used to assure data quality after the data have been recorded. The two major elements associated with the validation of much of Tennessee Valley Authority's (TVA's) environmental data are: (1) initial computer flagging of physically/chemically questionable and outlying data and (2) analyst review and feedback to field technicians to implement corrective actions. Examples of these procedures as applied to aerometric data will be discussed. The benefits of this approach include timely feedback to the field technicians to resolve potential problems with a monitoring system and assignment of quality code ratings and precision and accuracy to all archived and reported data.

The 2015 New York City Legionnaires' Disease Outbreak: A Case Study on a History-Making Outbreak.

Environmental monitoring refers to the tools and techniques designed to observe an environment, characterize its quality, and establish environmental parameters, to accurately quantify the impact an activity has on an environment. A warmer climate may result in lower thermal efficiency and reduced load-including shutdowns in thermal power plants. It is found in research that a rise in temperature of 1°C reduces the supply of nuclear power by about 0.5% through its effect on thermal efficiency. A drastic change in air pressure also indicates there could be a significant climate change. In the event of a radiological release accident, environmental data is required to reduce radiation exposure to humans. That’s why environmental monitoring is very important for a nuclear power plant. It can be a crucial matter for the industries also because environmental monitoring helps industries operate responsibly, minimize negative impacts on the planet, and contribute to a more sustainable future. An IoT-based system can do environmental monitoring. Anyone using an IoT-based system can get environmental data like temperature, pressure, humidity, etc. Here the projected system delivers sensor data which are got from the environment to an API called ThingSpeak over an HTTP protocol and allows storing of data. The proposed system works well and it shows reliability. The prototype has been used to monitor and analyse real-time data using graphical information of the environment.

Australia invests significant resources in environmental data acquisition, management and publication. Although data are abundant, users are typically hampered by an inability to discover, access and re-use the data. The National Environmental Information Infrastructure (NEII) activity will improve the effectiveness and efficiency of discovering, accessing and re-using environmental data beyond its primary purpose. The NEII is envisioned as a federation of environmental data nodes adopting common standards to create a data infrastructure with an initial focus on nationally significant environmental data. Its primary focus is on the discovery and re-use of national environmental data that is already well-managed, but that currently has limited application beyond its original business purpose. In common with spatial data infrastructures, the NEII encompasses common data models, exchange formats and standard network protocols along with centralised catalogues of uniform metadata descriptions. It also includes standardised models for describing environmental measurements, monitoring sites and methods used to observe the environment to address the unique requirements of environmental information. These architectural elements are more fully described in the NEII Reference Architecture (Bureau of Meteorology, 2014b, www.neii.gov.au). The Bureau of Meteorology is leading the development of the NEII including provision of core coordination and integration infrastructure, as well as the governance and collaboration framework for its development and operation. However its ongoing success is dependent on establishing enduring partnerships with major national environmental information organisations. The NEII Programme is framed around five focus areas including (a) Communication, (b) Engagement, (c) Policies and frameworks, (d) Data management, and (e) ICT build. This paper provides a more detailed overview of one component of the Data Management area regarding the development of the NEII Conformance Framework. Conformance means following established guidelines, specifications and standards or working towards them. A conformance framework is a structured set of guidelines that detail the levels at which a participant provides services that comply with the NEII architecture. The NEII Conformance Framework has been developed to (a) enable partners to set priorities against specific expectations that will jointly lead to developing a sustainable federated environmental information system; (b) enable users of the NEII to rapidly assess the suitability of data for their business needs; and (c) provide a common measurement system to monitor progress in the development of the NEII. The framework adopts a capability maturity model approach to describe the steady improvement required for NEII nodes to progress from a basic data release (experimental data service with limited operational support) to an enduring federated system providing environmental information. The design of the model is informed by other maturity-based approaches for open data such as the Open Data Institute's certification approach (Open Data Institute 2015). The paper also presents a worked example of the conformance framework against the Bureau of Meteorology's Australian Hydrologic Geospatial Fabric NEII data services. The paper concludes with an overview of major learnings from the programme to-date. These relate primarily to reducing the cost of participation in NEII by data custodians given the challenge of delivering data using NEII standards; and developing approaches to better support users to use the portfolio of NEII data given some of the methods of data delivery may be new to non-technical users. The NEII programme has prioritised both these and developed work packages to achieve improvements.

With the increasing ecological environment problems such as soil erosion and wind and sandification in recent years, mankind has realized the necessity and the importance of protecting the environment, and has begun to study this problem continuously, hoping to find an effective solution to the ecological environment management, so that human development can maintain a balance with nature. In this environment, many disciplines have come into being, and soil and water protection is one of them. Soil erosion (also known as soil erosion) is a global environmental problem, and it is of great significance to control soil erosion as one of the measures to improve the overall ecological environment. “Digital soil and water culture” has become the inevitable trend of the modernization and information development of soil and water, and “computer-aided design technology” as its component is being widely used in soil and water science research, planning, design, construction and management. Therefore, through the analysis of the examples of computer-aided design applied accurately in soil and water protection drawing, this paper aims to further improve and pay attention to the research of the basic technology of “digital soil and water protection”, so as to lay the foundation for the comprehensive meeting of the “digital information” society. The computer-aided design has great advantages in the monitoring of large-scale ecological resources and environment, and has the advantages of fast, intuitive and wide monitoring area, so this paper explores the application of computer-aided design in soil and water conservation assessment.

The article discusses the possibility of using digital platforms for environmental management. The aim of the research is to determine the directions of using digital platforms for environmental management. To preserve the environment, increase energy conservation and sustainable development of territories, effective management is always important. Digital innovation allows citizens to engage, develop environmental volunteering, improve environmental literacy, collect more environmental data, and improve governance. The work identified the types of digital platforms depending on the subject of management, the main types of digital platforms and the main type of activity based on the chosen platform. The article considered the main digital platforms for environmental management in the field of ecology and the environment of the Russian Federation, highlighted the main functions of the platforms, problems and development directions. It is necessary to create such hybrid systems of environmental supervision in the field of water resources protection, to detect the facts of illegal construction and violation of construction parameters, remote control over the intended use of land, deforestation, and the environmental situation in water and air.

科学合理的海域空间评价单元划分是各类海洋空间监测、评价、规划和管理的基础工作，对于保护海洋生态环境，实现海洋资源的可持续开发利用具有重大现实意义。然而，海洋的流动性、开放性、边界模糊性等特征，导致海洋空间评价单元划分较陆地而言更为复杂、困难。以福建省东山湾为例，提出一种适用于小尺度海域的空间评价单元划分技术方案，通过从化学属性、物理属性、生物学属性三个方面构建海域空间生态属性划分指标体系，进行空间分类评价，运用插值、叠加分析等GIS技术将东山湾划分为67个基本空间评价单元。研究结果不仅能为进一步划定东山湾海洋空间规划提供技术支持，同时为其他小尺度海域生态监测、评价、规划和管理提供科学参考。;For the sustainable development and utilization of marine resources, and protection of marine ecological environment, coastal countries have successively implemented marine spatial planning (MSP). MSP is considered as an important marine management tool, which is an indispensable part of marine ecological civilization construction in China. Scientific and reasonable division of marine spatial units is the basic work of marine spatial monitoring, evaluation, planning and management, which is of great practical significance for the protection of marine ecological environment and the sustainable development of marine resources. However, the characteristics of the ocean, such as mobility, openness and boundary ambiguity, make the division of marine spatial units more complex and difficult than that of land. In this study, we collect a large number of data from environmental monitoring sites in Dongshan Bay. Based on the comprehensive and detailed data which can capture ecological environment status, we propose a technical scheme of spatial evaluation units division which is suitable for fine-scale sea areas. The scheme constructs the index system for the division of marine spatial evaluation units based on the physical, biological and chemical elements. Combined with GIS technology such as interpolation and spatial overlay analysis, Dongshan Bay is divided into 67 basic spatial evaluation units, which is a more accurate and scientific division of marine spatial units. On the basis of marine spatial units, local government can carry out the marine spatial monitoring, evaluation, planning and management. The marine environmental protection strategies and marine exploitation activities can be formulated for the sea areas with different environmental endowments by considering the local conditions. This division approach can not only provide technical support for the MSP of Dongshan Bay, but also can be a supplement of spatial units division approach for marine spatial monitoring, evaluation, planning and management. This division approach is suitable for fine-scale sea areas, but it is also applicable to large and medium-scale sea areas where complete and detailed environmental monitoring data can be obtained. The technical scheme of marine spatial units division proposed in this study has a wide application prospect.

Environmental information and data underpin achievement of the U.S. Department of Energy (DOE) Office of Environmental Management (EM) mission at the Hanford Site. The Hanford Environmental Data Management (HEDM) Program is the DOE Richland Operations Office (RL) approach to develop and implement a formal program for managing environmental data and the associated records, materials, and systems at the Hanford Site. The current project, contract, organization, and contractor-specific efforts at managing environmental data sets are insufficient to provide orderly, long-term, site-wide access. A vital element to be created within the HEDM program plan is a catalog of data sources, called the Hanford Environmental Information and Data Index (HEIDI), that will enable long-term access and retrievability for the multiple independent sources of data that might otherwise be difficult to discover. This report compares leading open source and commercial data catalog platforms using criteria to assess the functionality needed to develop the HEIDI catalog of Hanford data sources that connects and exchanges data with established Hanford Local Area Network (HLAN) enterprise information technology systems. Proprietary platforms evaluated included ArcGIS Enterprise Sites, Junar, OpenDataSoft, and Socrata, and non-proprietary platforms included Energy Data eXchange (EDX), Comprehensive Knowledge Archive Network (CKAN), and DKAN (a Drupal-based open data portal based on CKAN). Capabilities supporting data discoverability, retrieval, and archival, as well as metadata standard requirements and integration into the HLAN were rated as either failing to meet requirements (F), meeting requirements (M), or exceeding requirements by delivering additional desired features (E). The lowest rating for any capability area was assigned as the overall rating for the platform. These findings enable DOE-RL and the contractors implementing the HEDM plan to focus on candidate tools likely to meet the requirements for implementing HEIDI. All of the platforms receiving an overall rating of ‘F’ were unable to be deployed on Hanford infrastructure or within dedicated cloud resources. A propriety software-as-a-service (SaaS) model of delivering a data catalog (e.g., found in software such as Junar and OpenDataSoft) favors consistency across customers at the expense of customization and configurable roles that are needed for Hanford work. Hosting data on a shared commercial platform places limits on dataset size (maximum of 240 Mb for OpenDataSoft), a significant limitation for HEIDI implementation. EDX, a government data catalog based on CKAN, received the ‘F’ rating due to an inability to incorporate authentication from HLAN into the system. Among platforms rated ‘M’ or ‘E’, only the Socrata platform had a SaaS delivery model. In contrast to other SaaS platforms, Socrata provided custom roles and gateways that allow local datasets to be incorporated into an online catalog. Socrata also complies with the Federal Risk and Authorization Management Program, a significant benefit for cloud-based management of Hanford data. The other platforms rated ‘M’ or ‘E’, ArcGIS Enterprise Sites, CKAN, and DKAN, provide fully self-hosted options, allowing for greater control and flexibility with the HEIDI catalog. These widely used tools have supportive communities of practice, extensive customization options, and demonstrated deployments that provide evidence that they can meet requirements, often deliver additional desired features, and work well with federal government systems. Completely customized alternatives built on a collection of applications were not evaluated because achieving similar performance to CKAN or DKAN requires substantial resources, especially in the absence of the active communities that have grown to support these tools. ArcGIS Enterprise Sites, Socrata, CKAN, and DKAN were evaluated as strong candidates for successful implementation with HEIDI.

Microalgae biomass production technology is in continuous progress. One of the challenges deals with scaling up existing medium-scale facilities to industrial-scale production systems. This new expanding infrastructure requires adequate data management and data accessibility tools for all the process variables. In this sense, this work presents a novel solution for microalgae production systems based on Internet of Things (IoT) technology as an important ally in the digitalization of these industrial processes. The paper summarizes the development of an IoT-based platform for data management in a large-scale microalgae cultivation plant with more than 12 industrial photobioreactors. A cloud-based architecture is provided for a solution for data management and a graphical front-end for data access (real-time and historical data). Different profiles can be managed for technicians and researchers depending on their skills and needs.

Effective management and analysis of genotypic, phenotypic, and environmental data generated by plant breeding initiatives are crucial for informed decision-making. However, many existing repository solutions may not meet the specific project requirements, forcing individuals to rely on Excel files for data storage, despite Excel not being an ideal option. Using such data files may lead to errors and complicated processing. To prevent such issues, we have developed an approach that utilizes Excel templates to store project data. These templates adhere to existing standards such as MCPD or MIAPPE but are also flexible enough to incorporate project-specific information. Additionally, we have developed a validation process using the Frictionless library, which was implemented in the EU AGENT project, to help data providers meet all template requirements. Our approach links accessions from a project to a shared database of known accessions with passport data using a unique identifier. This accession database is also stored in a standardized and Frictionless validated Excel file. This process of linking accessions from a project file to this database can often largely be automated. Validated and linked Excel files can be seamlessly imported into an existing repository system such as Germinate , which also offers a BrAPI endpoint for accessing and analysing the data. This enables easy updating of published data whenever new project data becomes available. Overall, our approach provides a straightforward yet effective way of managing data from different plant breeding experiments and projects while adhering to the FAIR principles.

This paper presents an overview of the development of the SEDRIS standards, their contents and applications, and examples of their implementation for the management and exchange of environmental data. This overview includes data applications involving Space Environment Effects; Space Science and Astronomy; Space-based Technologies for Water Resources, Hydrology & Environments; Remote Sensing, Geomatics, Global Positioning System usage and Geographic Information System applications; and Air Traffic and Air Transport.