Advanced Science and Technology Letters Vol.150 (AST 2018), pp.93-96 http://dx.doi.org/10.14257/astl.2018.150.22
A Study on Efficient Methods of Classification and Services Based on Data Recorded by Drones Seong Ho Park, Khan Muhammad, Ijaz ul Haq, Mi Young Lee and Sung Wook Baik1* Digital Contents Research Institute, Sejong University, Seoul, Republic of Korea 1College of Software and Convergence Technology, Sejong University, Seoul, Republic of Korea {shpark3797, khanm3797, hijaz3797}@gmail.com
[email protected] 1*
[email protected]
Abstract. In the last few years, an exponantial growth is noticed in the use of Unmanned Aerial Vehicles or drones for various fields such as weather casting, filming and journalism, surveillance and agriculture. However, the data generated by drones are not organized and utilized very well yet, making the process of searching drone-related data for specific enviroments, time consuming and difficult. Therefore, in this paper we propose an approch for classification and appropriate managment of the data captured by drones in such a way that acces to specific type of data and its dissemination becomes easy for users. Keywords: Drone, Big data, Data categorization, Data dissemination
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Introduction
Unmanned aerial vehicles (UAVs) have been used for different purposes such as collecting multimedia data in weather casting, surveillance and agriculture. The drone enables the pilot to remotely control it from the ground without directly connecting to the vehicle and can make automatic or semi-automatic flights depending on the preprogrammed route and the geographical information. In the early stages, drones were used for military purposes only, but it was expanded to different markets, industries and personal stations, such as broadcasting stations, agriculture, reconnaissance, shipping, and leisure cultures [1]. Nowadays, drones are able to collect data in various types (text, images and videos) depending on the equipment they are mounted on. Hence, we can easily categorize drone data as Big Data due to its needs in modern era [2]. In this paper, we classify data captured by drones based on its environment. The collected data is uploaded to a big data portal site, which suggests different ways to distribute the data to the analyst and easily utilize various tasks.
*
Corresponding Author
ISSN: 2287-1233 ASTL Copyright © 2018 SERSC
Advanced Science and Technology Letters Vol.150 (AST 2018)
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Characteristics of Drone Data
The volume of data captured by drone is increasing day to day due to its usage in various fields such as broadcasting shooting, relay industry, enrichment industry, education, military reconnaissance, shipping industry and leisure sports depending on the equipment to be installed in the drone [3-9]. It is also used in various industries by utilizing drones as a versatile [10]. Besides the growing rate of the data, the format of the data is also a challenging task to handle, because a drone can generate and store various data forms such as texts, images and videos.
Drone Data
Disaster
City
Village
Farm
River
Sea
Quarry
Sport
Fig. 1. Data captured by drones can be classified into eight classes based on various environments, including disasters, cities, villages, farms, rivers, seas, quarrys, and sports.
2.1 Drone Data Category The proposed classification approach for drone data is based on the environment in which it captures the data. The reason to classify and manage this data is to ensure its availability and easy access for users. Therefore, due to the above reason drone data need to be collected, organized and utilized in analysis. Data classification is essential to facilitate this process.
Fig. 2. Sample images taken by drones; classified into different classes based on the environment.
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Advanced Science and Technology Letters Vol.150 (AST 2018)
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Managing and Distributing Drone Data on Portal Sites Drone Data Management Method
The drone data management on big data portal sites can manage a large amount of data that cannot be compared to the storage size of sites that are usually provided. Therefore, storing and managing large amounts of data requires some special management methods that complete the characteristics of managing big data rather than simply sizing the database. The management of drone data should be of high quality, capable to reliably gather the data continuously, and should have the data organized into an environment that matches the content to be provided to the analysts. 3.2
Drone Data Distribution Method
The current literature does not contain any method that can provide drone data in an organized form e.g., classified data based on the equipment of drone, data types (text, image and video) and environment. Such system is also in demand that can produce new value for drone data and provide it to consumers. Therefore, in this paper we proposed an approach to distribute drone data so that drone data can be collected and supplied to big data portal sites that can provide data to data analysts and the drone data can be used for distribution as well as for second content production [11].
Image
Video
Big data Portal Database
Text
Big data Portal Site
Drone Data
Fig. 3. The data is categorized by the recorded environment and then stored in a big data portal site database for analysis of analysts.
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Conclusion and Future Work
In this paper, we proposed an efficient approach for classification of data recorded by drone and to facilitate distribution of these data using big data portal site for data analysts. Using this approach, we can generate more data which can be helpful to different applications. In the future work, we will explore more efficient methods to collect data and introduce more classes for classification of drone related data. We will also explore different data augmentation methods for increasing the size of collected data. Acknowledgement. This work was supported by the Korea Institute for Advencement of Technology (KIAT) grant funded by the Korean government (Motie : Ministry of Trade, Industry&Energy) (No. N0002431).
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