The Research of Ponded Water Road Traffic Emergency Management Based on Internet of Things

2015 ◽  
Vol 744-746 ◽  
pp. 1848-1851
Author(s):  
Li Xun Wang ◽  
Zhi Hong Chen ◽  
Li Ying Sui ◽  
Wei Li
Keyword(s):  
Internet Of Things ◽  
Emergency Management ◽  
Road Traffic ◽  
Heterogeneous Data ◽  
Road Surface ◽  
Multiple Sources ◽  
Traffic Jam ◽  
Comprehensive Information ◽  
Development Direction ◽  
The Internet Of Things

This paper presents studies on the theories aimed at using the technologies of Internet of Things in the domain of the emergency management of ponded water on road surface. It first introduces an emergency management model based on the Internet of Things to solve the problem of ponded water on road surface. It discusses a few critical technologies related to this model including monitoring the condition of the ponded water on road surface and the condition of the traffic simultaneously, the framework of data interfacing using multiple sources including the heterogeneous data, the analysis of traffic jam spreading pattern at critical locations of ponded water, comprehensive information analysis, and comprehensive demonstrations of monitoring based on GIS. In the end it gives our expectation about the future and development direction of using the technologies of Internet of Things in city traffic emergency management.

scholarly journals Characteristic Analysis of Multisource Heterogeneous Data in Digital City Planning Based on Internet of Things

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Xiao Xiao
Keyword(s):  
Internet Of Things ◽  
City Planning ◽  
Heterogeneous Data ◽  
Feature Analysis ◽  
The Internet ◽  
Digital City ◽  
Characteristic Analysis ◽  
True Value ◽  
The Relationship ◽  
The Internet Of Things

The purpose of this article is to use the Internet of Things related technology to analyze the characteristics of multisource and easy-to-purchase data for the different types of planning data and different levels of cognitive needs of participants in the entire urban planning process. This paper uses the ontology idea to reconstruct the relationship between multisource and heterogeneous planning data including Internet of Things data, planning documents, and planning drawings, to design the data semantic relationship of the ontology model elements, define the relationship between the data types, and implement the ontology-based method. The semantic expression algorithm in the planning field facilitates the exchange of various planning participants’ understanding of the planning scheme, at the same time, according to the classification of multisource heterogeneous data features, logical reasoning of ontology relationships, filtering redundant information, and multisource heterogeneous planning data visualization. Finally, the information of the same nature collected by the sensor nodes of the Internet of Things is batched, and the calculated fusion information is closer to the true value through a series of weighting formulas. Experiments prove that the feature analysis method proposed in this paper can maintain a loss of 0.02% and achieve an accuracy rate of 79.1% when the overall characteristics of digital city planning are reduced by 67%, which effectively proves the multisource heterogeneous data feature analysis for digital city planning importance.

scholarly journals Consensus-Based Data Management within Fog Computing For the Internet of Things

2021 ◽  
Author(s):  
AISDL
Keyword(s):  
Internet Of Things ◽  
Data Management ◽  
Fog Computing ◽  
Heterogeneous Data ◽  
The Internet ◽  
Effective Decision ◽  
Effective Decision Making ◽  
New Generation ◽  
Delivery Models ◽  
The Internet Of Things

The Internet of Things (IoT) infrastructure forms a gigantic network of interconnected and interacting devices. This infrastructure involves a new generation of service delivery models, more advanced data management and policy schemes, sophisticated data analytics tools, and effective decision making applications. IoT technology brings automation to a new level wherein nodes can communicate and make autonomous decisions in the absence of human interventions. IoT enabled solutions generate and process enormous volumes of heterogeneous data exchanged among billions of nodes. This results in Big Data congestion, data management, storage issues and various inefficiencies. Fog Computing aims at solving the issues with data management as it includes intelligent computational components and storage closer to the data sources.

Description and classification for facilitating interoperability of heterogeneous data/events/services in the Internet of Things

2017 ◽  
Vol 256 ◽  
pp. 13-22 ◽  
Author(s):  
Hyung-Jun Yim ◽  
Dongmin Seo ◽  
Hanmin Jung ◽  
Moon-Ki Back ◽  
InA Kim ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Heterogeneous Data ◽  
The Internet ◽  
The Internet Of Things

scholarly journals Crop Management with the IoT: An Interdisciplinary Survey

Agronomy ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 181 ◽  
Author(s):  
Giuliano Vitali ◽  
Matteo Francia ◽  
Matteo Golfarelli ◽  
Maurizio Canavari
Keyword(s):  
Machine Learning ◽  
Internet Of Things ◽  
Crop Management ◽  
Cropping System ◽  
Heterogeneous Data ◽  
Machine Learning Techniques ◽  
The Internet ◽  
Crop Fields ◽  
Learning Techniques ◽  
The Internet Of Things

In this study, we analyze how crop management will benefit from the Internet of Things (IoT) by providing an overview of its architecture and components from agronomic and technological perspectives. The present analysis highlights that IoT is a mature enabling technology with articulated hardware and software components. Cheap networked devices can sense crop fields at a finer grain to give timeliness warnings on the presence of stress conditions and diseases to a wider range of farmers. Cloud computing allows reliable storage, access to heterogeneous data, and machine-learning techniques for developing and deploying farm services. From this study, it emerges that the Internet of Things will draw attention to sensor quality and placement protocols, while machine learning should be oriented to produce understandable knowledge, which is also useful to enhance cropping system simulation systems.

IoT4Emergency

2021 ◽  
Vol 46 (1) ◽  
pp. 33-36
Author(s):  
Julie Dugdale ◽  
Mahyar T. Moghaddam ◽  
Henry Muccini
Keyword(s):  
Internet Of Things ◽  
Emergency Management ◽  
Real Time ◽  
International Workshop ◽  
The Internet ◽  
Time Data ◽  
Time Requirements ◽  
Safety Systems ◽  
Crises Management ◽  
The Internet Of Things

The increasing natural and man-induced disasters such as res, earthquakes, oods, hurricanes, overcrowding, or pandemic viruses endanger human lives. Hence, designing infrastructures to handle those possible crises has become an ever-increasing need. The Internet of Things (IoT) has changed our approach to safety systems by connecting sensors and providing real-time data to managers, rescuers, and endangered people. IoT systems can monitor and react to progressive disasters, people's movements and their behavioral patterns. The community faces challenges in using IoT for crises management: i) how to take advantage of technological advancements and deal with IoT resources installation issues? ii) what environmental contexts should be considered while designing IoT-based emergency handling systems? iii) how should system design comply with various levels of real-time requirements? This paper reports on the results of the First International Workshop on Internet of Things for Emergency Management (IoT4Emergency 2020), which speci cally focuses on challenges and envisioned solutions in using smart connected systems to handle disasters.

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