Journals / Uluslararası Yönetim Bilişim Sistemleri ve Bilgisayar Bilimleri Dergisi / 2021 / Cilt: 5 - Sayı: 2

A Virtual Assistant Design and Application on Industrial Database

Pages
122–143
Publication Date
2021-12-31
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

With the virtual help system provided, the distance between natural language and computer language is shortened and people can get information quickly and easily.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The development and advancement of technology allows people to access information in a variety of ways.
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Key Findings & Data:Whether in commerce, marketing or communication, the amount and variety of data is increasing in every field.
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Conclusion & Impact:With the virtual help system provided, the distance between natural language and computer language is shortened and people can get information quickly and easily.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:virtual assistant · natural language processing · database

Abstract

The development and advancement of technology allows people to access information in a variety of ways. Whether in commerce, marketing or communication, the amount and variety of data is increasing in every field. Collecting this data in different fields and drawing conclusions based on the data has become very important for the development of individuals, companies, industries, and countries, and especially collecting this data in databases has become popular. In this paper, an industrial database was created, a wireless sensor network was set up using ZigBee protocol for data collection, the collection of data in the database was done quickly and cheaply, and a natural language processing based Virtual Assistant was created to query the data. Unlike other traditional rule-based methods, Virtual Assistant has a non-predetermined structure that allows Virtual Assistant to answer different types of questions from the user. The communication between the created Sensor Network, database and Virtual Assistant is done using XMPP message protocol. Again, with the help of this protocol, a system is presented to communicate with the user. With the method presented in the study, the data in the relational database was made queryable regardless of location and platform. With the virtual help system provided, the distance between natural language and computer language is shortened and people can get information quickly and easily.

Özet

The development and advancement of technology allows people to access information in a variety of ways. Whether in commerce, marketing or communication, the amount and variety of data is increasing in every field. Collecting this data in different fields and drawing conclusions based on the data has become very important for the development of individuals, companies, industries, and countries, and especially collecting this data in databases has become popular. In this paper, an industrial database was created, a wireless sensor network was set up using ZigBee protocol for data collection, the collection of data in the database was done quickly and cheaply, and a natural language processing based Virtual Assistant was created to query the data. Unlike other traditional rule-based methods, Virtual Assistant has a non-predetermined structure that allows Virtual Assistant to answer different types of questions from the user. The communication between the created Sensor Network, database and Virtual Assistant is done using XMPP message protocol. Again, with the help of this protocol, a system is presented to communicate with the user. With the method presented in the study, the data in the relational database was made queryable regardless of location and platform. With the virtual help system provided, the distance between natural language and computer language is shortened and people can get information quickly and easily.

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Cite This Article

ÇINAKLI, M., ARTA, M., DEMİRDAĞ, M., SEÇKİN, A. Ç. (2021). A Virtual Assistant Design and Application on Industrial Database. Uluslararası Yönetim Bilişim Sistemleri ve Bilgisayar Bilimleri Dergisi, Cilt: 5 - Sayı: 2, 122–143. https://ajindex.com/articles/416508

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References (9)

  1. Adalı, Eşref. 2016. “Doğal Dil İşleme.” Türkiye Bilişim Vakfı Bilgisayar Bilimleri ve Mühendisliği Dergisi 5(2). Akyildiz, Ian, Su WY, Y. Sankarasubramaniam, and E. Cayirci. 2002. “Wireless Sensor Networks: A Survey.” Computer Networks 38:393–422. doi: 10.1016/S1389-1286(01)00302-4.
  2. Ali, Anum, Ghalib A. Shah, Muhammad Omer Farooq, and Usman Ghani. 2017. “Technologies and Challenges in Developing Machine-to-Machine Applications: A Survey.” Journal of Network and Computer Applications 83:124–39. doi: 10.1016/j.jnca.2017.02.002. Al-Rasyid, M. Udin Harun, Sritrusta Sukaridhoto, Muhammad Iskandar Dzulqornain, and Ahmad Rifai. 2020. “Integration of IoT and Chatbot for Aquaculture with Natural Language Processing.” TELKOMNIKA (Telecommunication Computing Electronics and Control) 18(2):640–48.
  3. Anon. n.d. “Cisco Visual Networking Index: Forecast and Trends, 2017–2022.” Cisco. Retrieved August 21, 2021 (https://www.cisco.com/c/en/us/solutions/collateral/service-provider/visual-networking-index-vni/white-paper-c11-741490.html).
  4. Atzori, Luigi, Antonio Iera, and Giacomo Morabito. 2010. “The Internet of Things: A Survey.” Computer Networks 54(15):2787–2805. doi: 10.1016/j.comnet.2010.05.010. Baker, Nick. 2005. “ZigBee and Bluetooth Strengths and Weaknesses for Industrial Applications.” Computing & Control Engineering Journal 16(2):20–25.
  5. Bandyopadhyay, Debasis, and Jaydip Sen. 2011. “Internet of Things: Applications and Challenges in Technology and Standardization.” Wireless Personal Communications 58(1):49–69. doi: 10.1007/s11277-011-0288-5.
  6. Banks, Andrew, and Rahul Gupta. 2014. “MQTT Version 3.1. 1.” OASIS Standard 29:89. Bansal, Himanshu, and Rizwan Khan. 2018. “A Review Paper on Human Computer Interaction.” International Journals of Advanced Research in Computer Science and Software Engineering 8:53–56.
  7. Başarslan, Muhammet Sinan, and Fatih Kayaalp. 2021. “Sentiment Analysis on Social Media Reviews Datasets with Deep Learning Approach.” Sakarya University Journal of Computer and Information Sciences 4(1):35–49.
  8. Bhadgale, Anil M., Sanhita R. Gavas, and P. R. Goyal. 2013. “Natural Language to SQL Conversion System.” International Journal of Computer Science Engineering and Information Technology Research 3(2):161–66.
  9. Couderc, Benoît, and Jérémy Ferrero. 2015. “Fr2sql: Interrogation de Bases de Données En Français.” in 22ème Traitement Automatique des Langues Naturelles. Dener, Murat. 2019. “A New Home Gateway Design and A Sensor-Based Smart Home Application Including P