scholarly journals Object Recognition of Environmental Information in the Internet of Things Based on Augmented Reality

2018 ◽  
Vol 173 ◽  
pp. 02023
Author(s):  
Chen Shasha ◽  
Wang Mei ◽  
Qin Xuebin
Keyword(s):  
Augmented Reality ◽  
Internet Of Things ◽  
Coal Mine ◽  
Detection System ◽  
Rapid Development ◽  
Environmental Information ◽  
The Internet ◽  
The Real ◽  
Augmented Reality System ◽  
The Internet Of Things

With the rapid development of Internet of things, on the basis of existing mine technology, As the basic digital mine, the detection system will become more and more mature with the construction of digital mines.This article takes China‘s coal production as the main basis, developed a matching coal mine augmented reality system, This article uses augmented reality technology to provide information through computer systems, increase the perception of coal mine workers on the real environment, and superimpose computer-generated prompt information into the real scene of the coal mine, realize "enhancement" of real coal mine environment.The experimental results show that this system is workable.Object recognition of environmental information in the Internet of things based on augmented reality system designed and implemented in this paper, in providing a new direction for Research on IoT Smart Mines and Application of Mobile Devices.

Sustainable Security for the Internet of Things Using Artificial Intelligence Architectures

2021 ◽  
Vol 21 (3) ◽  
pp. 1-22
Author(s):  
Celestine Iwendi ◽  
Saif Ur Rehman ◽  
Abdul Rehman Javed ◽  
Suleman Khan ◽  
Gautam Srivastava
Keyword(s):  
Internet Of Things ◽  
Detection System ◽  
Experimental Testing ◽  
Cyber Attacks ◽  
Internet Technology ◽  
The Internet ◽  
Business Operations ◽  
Private Data ◽  
The Internet Of Things ◽  
Better Than

In this digital age, human dependency on technology in various fields has been increasing tremendously. Torrential amounts of different electronic products are being manufactured daily for everyday use. With this advancement in the world of Internet technology, cybersecurity of software and hardware systems are now prerequisites for major business’ operations. Every technology on the market has multiple vulnerabilities that are exploited by hackers and cyber-criminals daily to manipulate data sometimes for malicious purposes. In any system, the Intrusion Detection System (IDS) is a fundamental component for ensuring the security of devices from digital attacks. Recognition of new developing digital threats is getting harder for existing IDS. Furthermore, advanced frameworks are required for IDS to function both efficiently and effectively. The commonly observed cyber-attacks in the business domain include minor attacks used for stealing private data. This article presents a deep learning methodology for detecting cyber-attacks on the Internet of Things using a Long Short Term Networks classifier. Our extensive experimental testing show an Accuracy of 99.09%, F1-score of 99.46%, and Recall of 99.51%, respectively. A detailed metric representing our results in tabular form was used to compare how our model was better than other state-of-the-art models in detecting cyber-attacks with proficiency.

scholarly journals Building Topic-Driven Virtual IoTs in a Multiple IoTs Scenario

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2956 ◽  
Author(s):  
Paolo Lo Giudice ◽  
Antonino Nocera ◽  
Domenico Ursino ◽  
Luca Virgili
Keyword(s):  
Social Networks ◽  
Internet Of Things ◽  
Social Networking ◽  
Virtual Communities ◽  
The Internet ◽  
The Real ◽  
Challenging Issue ◽  
The One ◽  
The Internet Of Things ◽  
Made In

In the last years, several attempts to combine the Internet of Things (IoT) and social networking have been made. In the meantime, things involved in IoT are becoming increasingly sophisticated and intelligent, showing a behavior that tends to look like the one of users in social networks. Therefore, it is not out of place to talk about profiles of things and about information and topics exchanged among them. In such a context, constructing topic-driven virtual communities starting from the real ones operating in a Multi-IoT scenario is an extremely challenging issue. This paper aims at providing some contributions in this setting. First of all, it presents the concept of profile of a thing. Then, it introduces the concept of topic-guided virtual IoT. Finally, it illustrates two approaches (one supervised and one unsupervised) to constructing topic-guided virtual IoTs in a Multi-IoT scenario.

scholarly journals Towards Deep-Learning-Driven Intrusion Detection for the Internet of Things

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 1977 ◽  
Author(s):  
Geethapriya Thamilarasu ◽  
Shiven Chawla
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Intrusion Detection ◽  
Intrusion Detection System ◽  
Learning Algorithm ◽  
Detection System ◽  
Cyber Attacks ◽  
The Internet ◽  
Critical Systems ◽  
The Internet Of Things

Cyber-attacks on the Internet of Things (IoT) are growing at an alarming rate as devices, applications, and communication networks are becoming increasingly connected and integrated. When attacks on IoT networks go undetected for longer periods, it affects availability of critical systems for end users, increases the number of data breaches and identity theft, drives up the costs and impacts the revenue. It is imperative to detect attacks on IoT systems in near real time to provide effective security and defense. In this paper, we develop an intelligent intrusion-detection system tailored to the IoT environment. Specifically, we use a deep-learning algorithm to detect malicious traffic in IoT networks. The detection solution provides security as a service and facilitates interoperability between various network communication protocols used in IoT. We evaluate our proposed detection framework using both real-network traces for providing a proof of concept, and using simulation for providing evidence of its scalability. Our experimental results confirm that the proposed intrusion-detection system can detect real-world intrusions effectively.

scholarly journals Development of Metal Polishing Dust Monitoring System using the Internet of Things and Cloud Server

2019 ◽  
Vol 15 (04) ◽  
pp. 53
Author(s):  
Zhiyao Fan ◽  
Tianhong Pan ◽  
Li Ma
Keyword(s):  
Internet Of Things ◽  
Monitoring System ◽  
Remote Monitoring ◽  
Environmental Information ◽  
Sensor Nodes ◽  
The Internet ◽  
Sink Node ◽  
Remote Monitoring System ◽  
Cloud Server ◽  
The Internet Of Things

In order to increase the management efficiency and decrease the maintenance costs in the traditional dust monitoring system, a novel real-time remote monitoring system using the Internet of Things and cloud server is proposed in this paper. The system includes several sensor nodes, a sink node and Cloud Server. The high-precision dust probe, temperature and humidity sensors, water flow sensors and hydrogen transmitters are integrated together into a sensor node to access the metal polished environmental information. Then, the collected information is transmitted to sink-node using the 2.4G wireless network. The sink-node uploads data to the Cloud Server through the 4G network and TCP Socket. Based on the Browser/Server (B/S) model, a remote monitoring system is developed by using Tencent Cloud Server, C# language, and SQL database. As a result, the on-site metal polishing environmental information is obtained via the App and Web page.

scholarly journals IoTbased smart and flexible lightning in streets

2018 ◽  
Vol 7 (2.8) ◽  
pp. 291 ◽  
Author(s):  
Raju Anitha ◽  
M Nishitha ◽  
K Akhila ◽  
K Sai Anusha ◽  
G Srilekha
Keyword(s):  
Internet Of Things ◽  
Embedded System ◽  
Voice Recognition ◽  
The Internet ◽  
The Real ◽  
Emergency Situations ◽  
Turn On ◽  
Energy Consumptions ◽  
The Internet Of Things

The internet of Things (IOT) is always giving unprecedented answers for the customary issues looked by man.One of the real obstacles in city is we are spending huge expenses on street light.  To control the street lights based on detection of sunlight by implemented with smart embedded system. The paper is mainly utilized for smart and climate adaptive lighting in street lights. The street lights are automatically ON during the evening time and automatically OFF during day time.The street light can be accessed to turn ON or OFF at anyplace and anytime through web.In addition to that On top of the street light we are placing camera to track the activities performed on the street and where the recordings are stored in a server. Furthermore a panic button is placed on the pole, If there is any emergency situations like harassment, robbery there is a panic button is available at the reachable height any person can press it if he is in danger. If people are unable to press the panic button, they should use voice recognition which is connected to panic button, when it recognises some commands like help, it automatically press the panic button. Whenever the panic button is pressed, the footages at that time recorded by the camera is sent straightforwardly to the cloud account. The near specific police headquarters can have access of the account by which they can see the incident’s spot. Every region's street lights are associated with the specific area's police headquarters and cloud account can be accessible by each of them. Here GSMTechnology is eliminated completely.Safety and energy consumptions can be ensured by this idea.

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