Research of Real-Time Data Presentation of Cloud Monitoring Based on Highcharts

2014 ◽  
Vol 1079-1080 ◽  
pp. 847-850
Author(s):  
De Zhi Bian ◽  
Jing Tao Li
Keyword(s):  
Real Time ◽  
Rail Transit ◽  
Real Time Monitoring ◽  
Time Data ◽  
Data Presentation ◽  
The Real ◽  
Adverse Conditions ◽  
Cloud Monitoring ◽  
Real Time Data

Based on industry, agriculture and rail transit to the data in real-time monitoring tasks, this paper proposes a new cloudmonitoring method, it mainly studies the real-time data presentation.This article uses the graphical component of Highcharts and the dataextraction technology of JQuery, it can present efficient real-time data to managers, it can also make managers learn quickly the shape of the data and the possibility of adverse conditions.

scholarly journals The Key Technology Design of the Real-Time Monitoring System Based on FPGA

2019 ◽  
Vol 15 (05) ◽  
pp. 38
Author(s):  
Bengang Bao ◽  
Xiangping Zhu ◽  
Yonghong Tan
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Monitoring System ◽  
Data Acquisition System ◽  
Lighting System ◽  
Real Time Monitoring ◽  
Time Data ◽  
Key Technology ◽  
The Real ◽  
Real Time Data

<p class="keywords"><span lang="EN-US">Due to having a direct affect for the growth of crops, the monitor and modification for the indicators of Greenhouse environment play significant roles in improving the yield of crops. The system, which adopts FPGA technology to control and modify the air condition and lighting system by collecting and analyzing the data of the temperature and humidity, has achieved good effects in practice. In our study, the key technology of real-time data acquisition system based on FPGA is proposed. In particular, based on FPGA, the designed ADC0809 and asynchronous FIFO can save the data in real time, which can be analyzed and disposed timely, so that the environment can be corrected in time.</span></p>

scholarly journals Industrial Parameters Monitoring System based on Embedded Web Server

2019 ◽  
Vol 8 (9) ◽  
pp. 2450-2453
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Electronic Device ◽  
Physical Parameters ◽  
Real Time Monitoring ◽  
Time Data ◽  
The Real ◽  
Industrial Sectors ◽  
Free Data ◽  
Real Time Data

The main aim of this paper is to deal with remote monitoring of various physical parameters of an electrical device via web-based application. This system facilitate user to monitor the real-time data from across the globe as the whole data is made available through pre-designed website. Real-time monitoring of electrical parameters is needed beside the high performance and precision of measurements with the development of modern industry towards networking. The main objectives of paper are to access the real-time data on global scale, to reduce the cost of visit & maintenance and finally to improve quality as well as throughput of production. All the physical parameters of an electronic device such as temperature, current, gas flow, viscosity etc. will be monitor independently. Microcontroller is used for the interconnection of all sensors and all collected information will be send to the web page using GSM facility. This real-time monitoring system definitely offers user for hassle free data accession. For high precision, repeatability of real-time data monitoring system has been done. This concept is helpful in industrial sectors for real time monitoring.

Emergent Advancements in M.tb Detection: An Artificial Intelligence Approach (Preprint)

2021 ◽  
Author(s):  
Jasleen Kaur ◽  
Shruti Kapoor ◽  
Maninder Singh ◽  
Parvinderjit Singh Kohli ◽  
Urvinder Singh ◽  
...  
Keyword(s):  
Machine Learning ◽  
Early Detection ◽  
Real Time ◽  
Automatic Detection ◽  
Machine Learning Algorithms ◽  
Real Time Monitoring ◽  
Time Data ◽  
The Real ◽  
Handheld Device ◽  
Real Time Data

BACKGROUND Infectious diseases are the major cause of mortality across the globe. Tuberculosis is one such infectious disease which is in the top 10 deaths causing diseases in developing as well as developed countries. The biosensors have emerged as a promising approach to attain the early detection of the pathogenic infection with accuracy and precision. However, the main challenge with biosensors is real time data monitoring preferentially reversible and label free measurements of certain analytes. Integration of biosensor and Artificial Intelligence (AI) approach would enable better acquisition of patient’s data in real time manner enabling automatic detection and monitoring of Mycobacterium tuberculosis (M.tb.) at an early stage. Here we propose a biosensor based smart handheld device that can be designed for automatic detection and real time monitoring of M.tb from varied analytic sources including DNA, proteins and biochemical metabolites. The collected data would be continuously transferred to the connected cloud integrated with AI based clinical decision support systems (CDSS) which may consist of the machine learning based analysis model useful in studying the patterns of disease infestation, progression, early detection and treatment. The proposed system may get deployed in different collaborating centres for validation and collecting the real time data. OBJECTIVE To propose a biosensor based smart handheld device that can be designed for automatic detection and real time monitoring of M.tb from varied analytic sources including DNA, proteins and biochemical metabolites. METHODS The Major challenges for control and early detection of the Mycobacterium tuberculosis were studied based upon the literature survey. Based upon the observed challenges, the biosensor based smart handheld device has been proposed for automatic detection and real time monitoring of M.tb from varied analytic sources including DNA, proteins and biochemical metabolites. RESULTS In this viewpoint, we propose an application based novel approach of combining AI based machine learning algorithms on the real time data collected with the use of biosensor technology which can serve as a point of care system for early diagnosis of the disease which would be low cost, simple, responsive, measurable, can diagnose and distinguish between active and passive cases, include single patient visits, cause considerable inconvenience, can evaluate the cough sample, require minimum material aid and experienced staff, and is user-friendly. CONCLUSIONS In this viewpoint, we propose an application based novel approach of combining AI based machine learning algorithms on the real time data collected with the use of biosensor technology which can serve as a point of care system for early diagnosis of the disease which would be low cost, simple, responsive, measurable, can diagnose and distinguish between active and passive cases, include single patient visits, cause considerable inconvenience, can evaluate the cough sample, require minimum material aid and experienced staff, and is user-friendly.

scholarly journals The Importance of Implementing Cyber Physical Systems to Acquire Real-Time Data and Indicators

J ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 147-153
Author(s):  
Paula Morella ◽  
María Pilar Lambán ◽  
Jesús Antonio Royo ◽  
Juan Carlos Sánchez
Keyword(s):  
Decision Making ◽  
Data Acquisition ◽  
Real Time ◽  
Failure Detection ◽  
Cyber Physical Systems ◽  
Future Research ◽  
Time Data ◽  
Physical Systems ◽  
The Real ◽  
Real Time Data

Among the new trends in technology that have emerged through the Industry 4.0, Cyber Physical Systems (CPS) and Internet of Things (IoT) are crucial for the real-time data acquisition. This data acquisition, together with its transformation in valuable information, are indispensable for the development of real-time indicators. Moreover, real-time indicators provide companies with a competitive advantage over the competition since they enhance the calculus and speed up the decision-making and failure detection. Our research highlights the advantages of real-time data acquisition for supply chains, developing indicators that would be impossible to achieve with traditional systems, improving the accuracy of the existing ones and enhancing the real-time decision-making. Moreover, it brings out the importance of integrating technologies 4.0 in industry, in this case, CPS and IoT, and establishes the main points for a future research agenda of this topic.

Customer behavior analysis using real-time data processing

2019 ◽  
Vol 31 (1) ◽  
pp. 265-290 ◽  
Author(s):  
Ganjar Alfian ◽  
Muhammad Fazal Ijaz ◽  
Muhammad Syafrudin ◽  
M. Alex Syaekhoni ◽  
Norma Latif Fitriyani ◽  
...  
Keyword(s):  
Data Processing ◽  
Real Time ◽  
Association Rule ◽  
Customer Behavior ◽  
Time Data ◽  
Content Type ◽  
The Real ◽  
Real Time Data ◽  
Real Time Data Processing ◽  
Big Data Technology

PurposeThe purpose of this paper is to propose customer behavior analysis based on real-time data processing and association rule for digital signage-based online store (DSOS). The real-time data processing based on big data technology (such as NoSQL MongoDB and Apache Kafka) is utilized to handle the vast amount of customer behavior data.Design/methodology/approachIn order to extract customer behavior patterns, customers’ browsing history and transactional data from digital signage (DS) could be used as the input for decision making. First, the authors developed a DSOS and installed it in different locations, so that customers could have the experience of browsing and buying a product. Second, the real-time data processing system gathered customers’ browsing history and transaction data as it occurred. In addition, the authors utilized the association rule to extract useful information from customer behavior, so it may be used by the managers to efficiently enhance the service quality.FindingsFirst, as the number of customers and DS increases, the proposed system was capable of processing a gigantic amount of input data conveniently. Second, the data set showed that as the number of visit and shopping duration increases, the chance of products being purchased also increased. Third, by combining purchasing and browsing data from customers, the association rules from the frequent transaction pattern were achieved. Thus, the products will have a high possibility to be purchased if they are used as recommendations.Research limitations/implicationsThis research empirically supports the theory of association rule that frequent patterns, correlations or causal relationship found in various kinds of databases. The scope of the present study is limited to DSOS, although the findings can be interpreted and generalized in a global business scenario.Practical implicationsThe proposed system is expected to help management in taking decisions such as improving the layout of the DS and providing better product suggestions to the customer.Social implicationsThe proposed system may be utilized to promote green products to the customer, having a positive impact on sustainability.Originality/valueThe key novelty of the present study lies in system development based on big data technology to handle the enormous amounts of data as well as analyzing the customer behavior in real time in the DSOS. The real-time data processing based on big data technology (such as NoSQL MongoDB and Apache Kafka) is used to handle the vast amount of customer behavior data. In addition, the present study proposed association rule to extract useful information from customer behavior. These results can be used for promotion as well as relevant product recommendations to DSOS customers. Besides in today’s changing retail environment, analyzing the customer behavior in real time in DSOS helps to attract and retain customers more efficiently and effectively, and retailers can get a competitive advantage over their competitors.

Cassandra-based data repository design for food supply chain traceability

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sandeep Kumar Singh ◽  
Mamata Jenamani
Keyword(s):  
Supply Chain ◽  
Real Time ◽  
Radio Frequency Identification ◽  
Query Language ◽  
Data Repository ◽  
Time Data ◽  
Content Type ◽  
The Real ◽  
Traceability System ◽  
Real Time Data

Purpose The purpose of this paper is to design a supply chain database schema for Cassandra to store real-time data generated by Radio Frequency IDentification technology in a traceability system. Design/methodology/approach The real-time data generated in such traceability systems are of high frequency and volume, making it difficult to handle by traditional relational database technologies. To overcome this difficulty, a NoSQL database repository based on Casandra is proposed. The efficacy of the proposed schema is compared with two such databases, document-based MongoDB and column family-based Cassandra, which are suitable for storing traceability data. Findings The proposed Cassandra-based data repository outperforms the traditional Structured Query Language-based and MongoDB system from the literature in terms of concurrent reading, and works at par with respect to writing and updating of tracing queries. Originality/value The proposed schema is able to store the real-time data generated in a supply chain with low latency. To test the performance of the Cassandra-based data repository, a test-bed is designed in the lab and supply chain operations of Indian Public Distribution System are simulated to generate data.

scholarly journals Aesthetic Archives

2016 ◽  
Vol 41 (1) ◽  
pp. 11-23
Author(s):  
Michael Takeo Magruder ◽  
Jeremy Pilcher
Keyword(s):  
New Media ◽  
Real Time ◽  
Emerging Technologies ◽  
Distributed Data ◽  
Time Data ◽  
The Real ◽  
New Media Art ◽  
Data Flows ◽  
Real Time Data ◽  
Visual Artist

Michael Takeo Magruder, visual artist and researcher, discusses his digital and new media art and practice with Jeremy Pilcher, lawyer and academic, whose research engages with the intersection of art and law. Takeo's work asks viewers to question their relationship both to and within the real-time data flows generated by emerging technologies and the implications these have for archives. His art concerns the way institutions use such systems to create narratives that structure societies. This conversation discusses how Takeo's practice invites us, as individuals, to critically reflect on the implications of the stories that are both told to and about us by using gathered and distributed data.

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