A Survey : Application of Big Data in the Travel and Tourism Industry

The development of information technology has increased the travel and tourism industry. The travel and tourism data are available in many sources such as telephone, social media, sensor system on the internet of things, and others. The application of big data has great potential in the development of the travel and tourism industry. Big data can take advantage of new things in making the right decisions and seeing opportunities in doing better business. This paper provides a survey that discusses big data in the travel and tourism industry. Big data is used to ticket price and demand prediction. In addition, big data is also used to build a tourism plans and recommender system with the personalized and adaptive method. Combination of using the internet of things and big data can help the industry to price their product. The result of this study is some of the implementation of big data in the travel and tourism industry. We conclude that big data can be used to explore new things in making the right decisions, seeing opportunities more observant, and doing business more efficiently

Download Full-text

Local Cultural IP Development and Cultural Creative Design Based on Big Data and Internet of Things

Mobile Information Systems ◽

10.1155/2021/5521144 ◽

2021 ◽

Vol 2021 ◽

pp. 1-9

Author(s):

Wei Bi ◽

Guangming Wang

Keyword(s):

Big Data ◽

Internet Of Things ◽

Simulation Analysis ◽

Design Method ◽

Tensor Decomposition ◽

Cultural Tourism ◽

Tourism Industry ◽

The Internet ◽

Creative Design ◽

The Internet Of Things

Relying on the development of cultural tourism resources and the development of cultural tourism industry to achieve regional industrial revitalization is an important way of implementing postdisaster reconstruction in areas suffering from major natural disasters. To this end, this article proposes a local cultural IP development and cultural creative design method based on big data and the Internet of Things to explore new ideas for postdisaster reconstruction in such areas. First, we collect traditional and modern cultural element data and carry out data cleaning and processing through the Internet of Things. Second, we use data mining to perform multilayer collaborative processing on regional cultural data based on ontology modeling and tensor decomposition. Based on our approach, local cultural categories can be effectively screened and filtered out. Finally, we establish a cultural IP development model based on the Internet of Things and verify the validity and applicability of the model through system testing and simulation analysis.

Download Full-text

Big Data Integration with IoT to Achieve the Challenges

Asian Journal of Computer Science and Technology ◽

10.51983/ajcst-2019.8.s3.2089 ◽

2019 ◽

Vol 8 (S3) ◽

pp. 45-49

Author(s):

V. Bhagyasree ◽

K. Rohitha ◽

K. Kusuma ◽

S. Kokila

Keyword(s):

Big Data ◽

Internet Of Things ◽

Real World ◽

Physical World ◽

Sensor Data ◽

The Internet ◽

The Future ◽

Iot Devices ◽

The Right ◽

The Internet Of Things

The Internet of Things anticipates the combination of physical gadgets to the Internet and their access to wireless sensor data which makes it useful to restrain the physical world. Big Data convergence has many aspects and new opportunities ahead of business ventures to get into a new market or enhance their operations in the current market. The existing techniques and technologies is probably safe to say that the best solution is to use big data tools to provide an analytical solution to the Internet of Things. Based on the current technology deployment and adoption trends, it is visioned that the Internet of Things is the technology of the future; while to-day’s real-world devices can provide best and valuable analytics, and people in the real world use many IOT devices. In spite of all the advertisements that companies offer in connection with the Internet of Things, you as a liable consumer, have the right to be suspicious about IoT advertisements. This paper focuses on the Internet of things concerning reality and what are the prospects for the future.

Download Full-text

Comparative analysis of clustering techniques in the internet of things

Global Journal of Information Technology Emerging Technologies ◽

10.18844/gjit.v10i2.4746 ◽

2020 ◽

Vol 10 (2) ◽

pp. 106-112

Author(s):

Ahmed Burhan Mohammed

Keyword(s):

Big Data ◽

Internet Of Things ◽

Clustering Algorithms ◽

Machine Language ◽

The Internet ◽

Data Set ◽

Keywords Internet ◽

The World ◽

The Right ◽

The Internet Of Things

One of the most important topics in the last decade is the Big Data (BD) and how to link it and benefit from its consumption in different fields, included as the introduction in this research analysis of the BD belonging to devices of the Internet of Things. The concept of managing objects and exploring devices is connected to the Internet and sensors deployed in the world, all these devices are pumping a lot of data through the Internet of Things (IoT) into the world. In order to make the right decisions for people and things, BD using data mining techniques and machine language algorithms help make decisions. The Internet of Things that insert large amounts of data need to be studied, analysed and disseminated in order to access valuable, useful and bug-free information for the purpose of making the right decision and avoiding problems. In this paper, two clustering algorithms simple K-means and self-organising map (SOM) in IoT are presented. Next, comparing the clustering models’ output in the IoT data set that improved the SOM is better than K-means, but it is slower in creating the model. Keywords: Internet of things (IoT), big data, machine learning, filtered cluster, K-means, SOM.

Download Full-text