Design of College English Process Evaluation System Based on Data Mining Technology and Internet of Things

2020 ◽  
Vol 16 (2) ◽  
pp. 18-33 ◽  
Author(s):  
Hongli Lou
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Process Evaluation ◽  
Evaluation System ◽  
Current Situation ◽  
The Internet ◽  
Mining Technology ◽  
College English ◽  
Procedural Evaluation ◽  
The Internet Of Things

This article proposes a new idea for the current situation of procedural evaluation of college English based on Internet of Things. The Internet of Things is used to obtain the intelligent data to enhance the teaching flexibility. The data generated during the process of procedural evaluation is carefully analyzed through data mining to infer whether the teacher's procedural evaluation in English teaching can be satisfied.

Distributed Learning on Mobile Devices: a New Approach to Data Mining in the Internet of Things

2020 ◽  
pp. 1-1
Author(s):  
Xiongtao Zhang ◽  
Xiaomin Zhu ◽  
Weidong Bao ◽  
Laurence T. Yang ◽  
Ji Wang ◽  
...  
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Mobile Devices ◽  
Distributed Learning ◽  
The Internet ◽  
New Approach ◽  
The Internet Of Things

scholarly journals A Novel Sensor Data Pre-Processing Methodology for the Internet of Things Using Anomaly Detection and Transfer-By-Subspace-Similarity Transformation

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4536 ◽  
Author(s):  
Yan Zhong ◽  
Simon Fong ◽  
Shimin Hu ◽  
Raymond Wong ◽  
Weiwei Lin
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Anomaly Detection ◽  
Sensor Data ◽  
Detection Methods ◽  
The Internet ◽  
Quality Of Data ◽  
Data Mining Algorithms ◽  
Sensing Applications ◽  
The Internet Of Things

The Internet of Things (IoT) and sensors are becoming increasingly popular, especially in monitoring large and ambient environments. Applications that embrace IoT and sensors often require mining the data feeds that are collected at frequent intervals for intelligence. Despite the fact that such sensor data are massive, most of the data contents are identical and repetitive; for example, human traffic in a park at night. Most of the traditional classification algorithms were originally formulated decades ago, and they were not designed to handle such sensor data effectively. Hence, the performance of the learned model is often poor because of the small granularity in classification and the sporadic patterns in the data. To improve the quality of data mining from the IoT data, a new pre-processing methodology based on subspace similarity detection is proposed. Our method can be well integrated with traditional data mining algorithms and anomaly detection methods. The pre-processing method is flexible for handling similar kinds of sensor data that are sporadic in nature that exist in many ambient sensing applications. The proposed methodology is evaluated by extensive experiment with a collection of classical data mining models. An improvement over the precision rate is shown by using the proposed method.

Big Data in manufacturing systems engineering – close up on a machine tool

2016 ◽  
Vol 64 (7) ◽  
Author(s):  
Christian Bauer ◽  
Zaigham-Faraz Siddiqui ◽  
Manuel Beuttler ◽  
Klaus Bauer
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Internet Of Things ◽  
Systems Engineering ◽  
Machine Tools ◽  
Manufacturing Systems ◽  
The Internet ◽  
New Approach ◽  
New Challenges ◽  
The Internet Of Things

AbstractWith the increasing connectivity of devices, the amount of data that is recorded and ready for analysis is growing correspondingly. This is also the case for shop floors in flexible sheet metal handling and production. With the growing need for flexibility in production, the availability of machine tools is imminent. This paper shows different approaches that a classical manufacturing systems company such as TRUMPF takes in applying data mining techniques to address the new challenges which come with the Internet of things. In addition to classical methods, a new approach is introduced that does not need any alteration of the machine or its interfaces.

scholarly journals Parallel Approaches for Data Mining in the Internet of Things Realm

2018 ◽  
Vol 46 (5) ◽  
pp. 807-811 ◽  
Author(s):  
Francesco Piccialli ◽  
Salvatore Cuomo ◽  
Gwanggil Jeon
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
The Internet ◽  
The Internet Of Things

A Semantic Sensor Web Architecture in the Internet of Things

2019 ◽  
pp. 75-97
Author(s):  
Eliot Bytyçi ◽  
Besmir Sejdiu ◽  
Arten Avdiu ◽  
Lule Ahmedi
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Sensor Data ◽  
Wireless Sensor ◽  
The Internet ◽  
Web Architecture ◽  
Hidden Knowledge ◽  
Semantic Sensor Web ◽  
The Internet Of Things ◽  
The Web

The Internet of Things (IoT) vision is connecting uniquely identifiable devices to the internet, best described through ontologies. Furthermore, new emerging technologies such as wireless sensor networks (WSN) are recognized as essential enabling component of the IoT today. Hence, the interest is to provide linked sensor data through the web either following the semantic web enablement (SWE) standard or the linked data approach. Likewise, a need exists to explore those data for potential hidden knowledge through data mining techniques utilized by a domain ontology. Following that rationale, a new lightweight IoT architecture has been developed. It supports linking sensors, other devices and people via a single web by mean of a device-person-activity (DPA) ontology. The architecture is validated by mean of three rich-in-semantic services: contextual data mining over WSN, semantic WSN web enablement, and linked WSN data. The architecture could be easily extensible to capture semantics of input sensor data from other domains as well.

Data Mining Techniques for Distributed Denial of Service Attacks Detection in the Internet of Things

2016 ◽  
pp. 275-334 ◽  
Author(s):  
Pheeha Machaka ◽  
Fulufhelo Nelwamondo
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Denial Of Service ◽  
Current Data ◽  
The Internet ◽  
Denial Of Service Attacks ◽  
Distributed Denial Of Service ◽  
Ddos Attacks ◽  
Data Mining Techniques ◽  
The Internet Of Things

This chapter reviews the evolution of the traditional internet into the Internet of Things (IoT). The characteristics and application of the IoT are also reviewed, together with its security concerns in terms of distributed denial of service attacks. The chapter further investigates the state-of-the-art in data mining techniques for Distributed Denial of Service (DDoS) attacks targeting the various infrastructures. The chapter explores the characteristics and pervasiveness of DDoS attacks. It also explores the motives, mechanisms and techniques used to execute a DDoS attack. The chapter further investigates the current data mining techniques that are used to combat and detect these attacks, their advantages and disadvantages are explored. Future direction of the research is also provided.

Data Mining for the Internet of Things: Literature Review and Challenges

2021 ◽  
Vol 9 (VII) ◽  
pp. 3351-3362
Author(s):  
Dr. Mohd Zuber
Keyword(s):  
Data Mining ◽  
Big Data ◽  
Internet Of Things ◽  
The Internet ◽  
Mining System ◽  
Research Issues ◽  
Data Mining Algorithms ◽  
Huge Data ◽  
Mining Algorithms ◽  
The Internet Of Things

The huge data generate by the Internet of Things (IOT) are measured of high business worth, and data mining algorithms can be applied to IOT to take out hidden information from data. In this paper, we give a methodical way to review data mining in knowledge, technique and application view, together with classification, clustering, association analysis and time series analysis, outlier analysis. And the latest application luggage is also surveyed. As more and more devices connected to IOT, huge volume of data should be analyzed, the latest algorithms should be customized to apply to big data. We reviewed these algorithms and discussed challenges and open research issues. At last a suggested big data mining system is proposed.

Smart Environmental Protection: The New Pathway for the Application of the Internet of Things in Environmental Management

2013 ◽  
Vol 411-414 ◽  
pp. 2245-2250 ◽  
Author(s):  
Ying Jiong Zhao ◽  
Bin Du ◽  
Bo Kai Liu
Keyword(s):  
Data Mining ◽  
Environmental Management ◽  
Internet Of Things ◽  
Environmental Protection ◽  
Emission Reduction ◽  
Pollutant Emission ◽  
The Internet ◽  
The Internet Of Things ◽  
Data Mining Application ◽  
Emission Dynamic

The intellectual environmental management can be realized accurately by applying the technology of the Internet of Things (IOT) to sense the environmental monitoring object and to precede the data mining application based on the monitoring. Taking Shanxi Province’s environmental IOT system as an example, this system had been achieved real time monitoring .The monitoring data has been applied to the total pollutant emission reduction verification, pollutant emission charge, administrative penalties, total pollutant emission dynamic management, pollutant emission allowance trade, and environmental mobile law-enforcing system, which provides a solid platform for the environmental management .Applying the technology of the IOT, using the “Whole Circle”environmental management, combining the environmental economic means, the innovation in methods, mechanism and supervision of environmental protection system can be realized.

scholarly journals Internet of Things Online Monitoring System Based on Cloud Computing

2017 ◽  
Vol 13 (09) ◽  
pp. 123 ◽  
Author(s):  
Kehua Xian
Keyword(s):  
Data Mining ◽  
Cloud Computing ◽  
Internet Of Things ◽  
Monitoring System ◽  
Online Monitoring ◽  
The Internet ◽  
Online Monitoring System ◽  
Database Service ◽  
Internet Of Things Technology ◽  
The Internet Of Things

<p><span style="font-family: 宋体; font-size: medium;">In order to develop a new convenient online monitoring system for Internet of things, an online monitoring system based on cloud computing is designed. The performance of this new Internet of things technology used in modern agricultural is test by Amazon relational database service (RDS) and ZigBee perception network. By analyzing the Internet of things related technologies and agricultural modernization, the integration framework of the Internet of things, cloud computing and data mining technology in the field of modern agriculture are proposed. Through the modern agricultural Internet of things monitoring system, the Internet of things intelligent gateway, cloud based research and construction of large data analysis and data mining projects are verified. The experimental results show that the relevant parameters of the model are obtained by training about 70% of the original data after adopting the cloud computing. Based on the above finding, it is concluded that the open Internet of things platform needs to be supported by the powerful computing resources. In addition, the cloud computing technology is suitable for the development of the Internet of things service platform.</span></p>

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