New monitoring interface for the AMS experiment Hashmani, Raheem Karim; Konyushikhin, Maxim; Shan, Baosong ...
Nuclear instruments & methods in physics research. Section A, Accelerators, spectrometers, detectors and associated equipment,
01/2023, Letnik:
1046
Journal Article
Recenzirano
Odprti dostop
The Alpha Magnetic Spectrometer (AMS) is constantly exposed to harsh condition on the ISS. As such, there is a need to constantly monitor and perform adjustments to ensure the AMS operates safely and ...efficiently. With the addition of the Upgraded Tracker Thermal Pump System, the legacy monitoring interface was no longer suitable for use. This paper describes the new AMS Monitoring Interface (AMI). The AMI is built with state-of-the-art time series database and analytics software. It uses a custom feeder program to process AMS Raw Data as time series data points, feeds them into InfluxDB databases, and uses Grafana as a visualization tool. It follows modern design principles, allowing client CPUs to handle the processing work, distributed creation of AMI dashboards, and up-to-date security protocols. In addition, it offers a more simple way of modifying the AMI and allows the use of APIs to automate backup and synchronization. The new AMI has been in use since January 2020 and was a crucial component in remote shift taking during the COVID-19 pandemic.
•Alpha Magnetic Spectrometer monitoring data.•Time series database.•Time series data analytics.•New Monitoring Interface.•Grafana.
The foundry industry with its casting processes and conditions create the basis for the quality of the final metallic components. The control of the process parameters is therefore of primary ...importance. Topics such as Industry 4.0, digitalisation, Internet of Things or Big Data allowing for a new grade of process monitoring but so far are mainly practiced by a few large foundries, which have started early with the digitalisation of their processes due to the high degree of automation already in place. Small and medium-sized foundries on the other hand often struggle with these issues. Concrete, comprehensible solutions are missing from the point of view of many medium-sized foundries without competences in the new IT-related topics. As the innovative backbone of industry, however, SMEs must also find and enter into this new world of manufacturing. Taking the example of, but not limited to, SME aluminium foundries, the topic presented here therefore aims at a basic and practicable approach for the digital monitoring of the most important process parameters during the production of aluminium castings. The Message Queuing Telemetry Transport (MQTT) communication protocol in combination with suitable microcontrollers, sensor technology as well as corresponding professional open-source software could provide a comprehensive, cost-effective infrastructure for real-time monitoring and visualisation of all relevant process data. In the sense of horizontal integration, the work demonstrates an implementable concept for the appropriate integration of the necessary components and their software-technical linking as well as the associated potential for process transparency, reproducibility and sustainability.
A new material testing reactor Jules Horowitz Reactor is under construction at CEA Cadarache. The materials to be irradiated will be placed into experimental devices around the reactor. Process and ...measurements of experimental devices will be carried out by command control. A data acquisition system having processing performances will be associated to the programmable logic controller. The challenge is to design and realize for twenty experiment devices a high availability data acquisition system architecture for 50 years of sustainability. The real time target will achieve 24/7 data acquisition and real time processing. This scalable architecture could be use as well for JHR experimental devices with high availability as for testbed. This architecture could be run on a standalone station for a measuring bench or deployed on cluster for high availability. CAREDAS’s design is modular and use proven widely used open source solutions. All parts are independent from each other and can be replaced with another technology with the same functionalities. This ensures sustainability and control of software sources.
In order to better meet the needs of bridge monitoring systems, this paper constructs the Prophet-Transformer time-series prediction model method based on the combination of Transformer and Prophet ...algorithms, for the reconstruction study of missing data, and explores the application characteristics and detailed modeling process of the model in depth. In this paper, the missing deflection data of the bridge is predicted in the context of Meixi River Bridge of Zhengwan Line. Compared with the single Transformer model, the Prophet-Transformer model has higher prediction accuracy, as well as lower MAE and RMSE of 0.0825 and 0.1104, respectively. Experimental results show that the time series obtained by InfluxDB data can effectively recover the missing data of bridges after processing by Prophet-Transformer model, which makes the bridge monitoring data have better analyzability and higher utilization.
Suitability Of Influxdb Database For Iot Applications Nasar, Mohammad; Kausar, Mohammad Abu
International journal of innovative technology and exploring engineering,
08/2019, Letnik:
8, Številka:
10
Journal Article
Odprti dostop
Large amounts of data are generated every moment by connected objects creating Internet of Things (IoT). IoT isn’t about things; it’s about the data those things create and collect. Organizations ...rely on this data to provide better user experiences, to make smarter business decisions, and ultimately fuel their growth. However, none of this is possible without a reliable database that is able to handle the massive amounts of data generated by IoT devices. Relational databases are known for being flexible, easy to work with, and mature but they aren’t particularly known for is scale, which prompted the creation of NoSQL databases. Another thing to note is that IoT data is time-series in nature. In this paper we are discussed and compare about top five time-series database like InfluxDB, Kdb+, Graphite, Prometheus and RRDtool.
With the rise of the Industrial Internet of Things (IIoT), there is an intense pressure on resource and performance optimization leveraging on existing technologies, such as Software Defined ...Networking (SDN), edge computing, and container orchestration. Industry 4.0 emphasizes the importance of lean and efficient operations for sustainable manufacturing. Achieving this goal would require engineers to consider all layers of the system, from hardware to software, and optimizing for resource efficiency at all levels. This emphasizes the need for container-based virtualization tools such as Docker and Kubernetes, offering Platform as a Service (PaaS), while simultaneously leveraging on edge technologies to reduce related latencies. For network management, SDN is poised to offer a cost-effective and dynamic scalability solution by customizing packet handling for various edge applications and services. In this paper, we investigate the energy and latency trade-offs involved in combining these technologies for industrial applications. As a use case, we emulate a 3D-drone-based monitoring system aimed at providing real-time visual monitoring of industrial automation. We compare a native implementation to a containerized implementation where video processing is orchestrated while streaming is handled by an external UE representing the IIoT device. We compare these two scenarios for energy utilization, latency, and responsiveness. Our test results show that only roughly 16 percent of the total power consumption happens on the mobile node when orchestrated. Virtualization adds up about 4.5 percent of the total power consumption while the latency difference between the two approaches becomes negligible after the streaming session is initialized.
Currently, big sensor data arise in a wide spectrum of Industry 4.0, Internet of Things, and Smart City applications. In such subject domains, sensors tend to have a high frequency and produce ...massive time series in a relatively short time interval. The data collected from the sensors are subject to mining in order to make strategic decisions. In the article, we consider the problem of choosing a Time Series Database Management System (TSDBMS) to provide efficient storing and mining of big sensor data. We overview InfluxDB, OpenTSDB, and TimescaleDB, which are among the most popular state-of-the-art TSDBMSs, and represent different categories of such systems, namely native, add-ons over NoSQL systems, and add-ons over relational DBMSs (RDBMSs), respectively. Our overview shows that, at present, TSDBMSs offer a modest built-in toolset to mine big sensor data. This leads to the use of third-party mining systems and unwanted overhead costs due to exporting data outside a TSDBMS, data conversion, and so on. We propose an approach to managing and mining sensor data inside RDBMSs that exploits the Matrix Profile concept. A Matrix Profile is a data structure that annotates a time series through the index of and the distance to the nearest neighbor of each subsequence of the time series and serves as a basis to discover motifs, anomalies, and other time-series data mining primitives. This approach is implemented as a PostgreSQL extension that allows an application programmer both to compute matrix profiles and mining primitives and to represent them as relational tables. Experimental case studies show that our approach surpasses the above-mentioned out-of-TSDBMS competitors in terms of performance since it assumes that sensor data are mined inside a TSDBMS at no significant overhead costs.
A smart energy platform for the large-space stadium based on Internet of Things (IoT) is proposed. The platform could realize the safe and stable operation of the energy system in various scenarios ...and promote low-carbon, efficient and sustainable development. In this paper, the smart energy platform is constructed based on IoT device data collection, time series data storage, front-end smart energy platform, and back-end optimization modules. The architecture and framework of the platform are explained in details. This study takes a large-space building in Hangzhou as an example to explain how the smart energy platform works in the real site. The real-time monitoring map of carbon emissions module and load prediction module of air-conditioning system are presented. The developed smart energy platform based on IoT could support the digital twin-based operation management of various types of low-carbon buildings in the future.
The proposed paper presents a concept and the deployment of an intelligent street lighting system using various open-source software and hardware components. This allows for smart control of the ...lighting fixture intensity based on traffic measurement data. The main idea is to monitor and control each light fixture from a central location and to implement different algorithms for energy efficiency improvement. The system has proven its stability over a one-month period and has achieved energy savings of 31.6%. It must be noted that this percentage is influenced by traffic patterns, so some fluctuation in energy savings is expected according to the varying load on the streets.
PDF
