Newspaper article-based agent control in smart city simulations
- PDF / 1,918,641 Bytes
- 19 Pages / 595.276 x 790.866 pts Page_size
- 72 Downloads / 189 Views
Open Access
RESEARCH
Newspaper article‑based agent control in smart city simulations Euhee Kim1, Sejun Jang2, Shuyu Li2 and Yunsick Sung2*
*Correspondence: [email protected] 2 Department of Multimedia Engineering, Dongguk University-Seoul, Seoul 04620, Republic of Korea Full list of author information is available at the end of the article
Abstract The latest research on smart city technologies mainly focuses on utilizing cities’ resources to improve the quality of the lives of citizens. Diverse kinds of control signals from massive systems and devices such as adaptive traffic light systems in smart cities can be collected and utilized. Unfortunately, it is difficult to collect a massive dataset of control signals as doing so in the real-world requires significant effort and time. This paper proposes a deep generative model which integrates a long short-term memory model with generative adversarial network (LSTM-GAN) to generate agent control signals based on the words extracted from newspaper articles to solve the problem of collecting massive signals. The discriminatory network in the LSTM-GAN takes continuous word embedding vectors as inputs generated by a pre-trained Word2Vec model. The agent control signals of sequential actions are simultaneously predicted by the LSTM-GAN in real time. Specifically, to collect the training data of smart city simulations, the LSTM-GAN is trained based on the Corpus of Contemporary American English (COCA) newspaper dataset, which contains 5,317,731 sentences, for a total of 93,626,203 word tokens, from written texts. To verify the proposed method, agent control signals were generated and validated. In the training of the LSTM-GAN, the accuracy of the discriminator converged to 50%. In addition, the losses of the discriminator and the generator converged from 4527.04 and 4527.94 to 2.97 and 1.87, respectively. Keywords: Control signal, Simulation, Smart city, Word2Vec, LSTM-GAN
Introduction Information and communication technologies (ICTs) play an important role in the development of smart and sustainable cities, which is an encompassing framework that includes not only physical infrastructure, but also human and social factors [1]. Smart cities are one of the main research topics based on Internet of Things (IoT) technology [2, 3]. In particular, the applications of smart cities require various integrated algorithms [4]. The diverse resources of smart cities are analyzed and utilized through technologies such as IoT, big data, social networks, and cloud computing, which improve the quality of the lives of citizens [5]. The development of smart cities currently involves the design and implementation of transportation, energy, traffic control, security, and other areas. The cost of physically installing these systems is very high in terms of both money and resources. However, controlling agents by © The Author(s) 2020. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction
Data Loading...
