scholarly journals Real-Time Warning Model of Highway Engineering Construction Safety Based on Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Haoran Song ◽  
Hao Yu ◽  
Dianliang Xiao ◽  
Yuexiang Li

Real-time and effective early warning of highway engineering construction sites is the key to ensuring the safety of highway engineering construction. At present, highway engineering construction safety early warning is limited by the experience of relevant personnel at the site and the dynamic changes of the project site environment. Therefore, the creation of a more active, smarter, and more effective real-time early warning model for construction safety is a strong complement to current research and has important theoretical and practical implications. The Internet of Things is the third wave of the information industry after computers, the Internet, and mobile communication networks. It is of great significance to promote the development of science and technology, economic growth, and social progress. Aiming at the shortcomings of the inadequate safety management methods for highway engineering construction in China, the inefficient efficiency of safety production supervision and management, and the emphasis on single and sporty supervision methods, a real-time early warning model for highway engineering construction safety based on the Internet of Things technology was constructed. By quantifying, scoring, and statistics of the safety situation during the construction process, the model achieves the goals of real-time monitoring, early warning, and handling hidden safety hazards. It overcomes problems such as untimely and unscientific safety issues in the past and effectively improves China’s highway engineering construction. The experimental comparison between the real-time early warning model and the traditional early warning model in this paper shows that the accuracy of the early warning model proposed in this paper is improved by nearly 5%, and the false alarm rate is reduced by nearly 4%.

2018 ◽  
Vol 13 (3) ◽  
pp. 448-454
Author(s):  
Junhua Wang ◽  
Yake Tang ◽  
Jianwei Shao ◽  
Mengjiao Long

2020 ◽  
pp. 1260-1284
Author(s):  
Laura Belli ◽  
Simone Cirani ◽  
Luca Davoli ◽  
Gianluigi Ferrari ◽  
Lorenzo Melegari ◽  
...  

The Internet of Things (IoT) is expected to interconnect billions (around 50 by 2020) of heterogeneous sensor/actuator-equipped devices denoted as “Smart Objects” (SOs), characterized by constrained resources in terms of memory, processing, and communication reliability. Several IoT applications have real-time and low-latency requirements and must rely on architectures specifically designed to manage gigantic streams of information (in terms of number of data sources and transmission data rate). We refer to “Big Stream” as the paradigm which best fits the selected IoT scenario, in contrast to the traditional “Big Data” concept, which does not consider real-time constraints. Moreover, there are many security concerns related to IoT devices and to the Cloud. In this paper, we analyze security aspects in a novel Cloud architecture for Big Stream applications, which efficiently handles Big Stream data through a Graph-based platform and delivers processed data to consumers, with low latency. The authors detail each module defined in the system architecture, describing all refinements required to make the platform able to secure large data streams. An experimentation is also conducted in order to evaluate the performance of the proposed architecture when integrating security mechanisms.


Author(s):  
S. Sundar ◽  
Piyush Arora ◽  
Sarthak Agrawal ◽  
R. Kumar ◽  
Harish M. Kittur

<p>In the last few years,there has been big interest in adhoc wireless network as they have tremendous military and commercial potential[1].Traditionally to test various parameters in the MANET , the most popular approach is to use mobile phone and Laptops and use the popular WIFI based protocol . But in the recent years there is a huge attraction towards the Internet Of things and specifically wireless sensor network. In this paper we are going to test the MANET protocol using zigbee based XBee modules specifally to determine the Range and Throughput of the Xbee netowork using XCTU Software . The sensor network will be deployed in the car parking application to see the parameters in the real time and dynamically see the sustainability of the network .The network is being designed keeping in mind that the nodes are mobile and at the same time the network does not require a standard infrastructure.</p>


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