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RETRACTED ARTICLE: Smart indoor crop grower based on smart database using IoT

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This article was retracted on 12 September 2022

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Abstract

We propose a new type of smart server based smart indoor crop grower using IoT(Internet of Things). The proposed smart indoor crop grower provides visual information for intuitively knowing the current cultivation status, as well as IoT-based sensor control, sensor data processing, communication control controller, smart server based sensor data storage, and building the optimal cultivation environment. It consists of a smart app that allows the user to know the real-time situation information of the smart indoor crop grower and to control the grower according to the situation. In particular, the FCM (Firebase Cloud Messaging) function was used to quickly notify the user in the event of an emergency with the grower, and the grower was constructed by applying an image processing technique to extract the growth status information of the cultivated grain. In addition, functional expansion was secured by configuring a programming function module to enable active coping even when a sensor is added. The proposed algorithm was applied to a self-produced smart indoor crop grower to confirm the superiority of its performance through experiments. The proposed smart indoor crop grower can be used as a basic resource for strengthening agricultural technology capabilities by developing technologies that are central to the agricultural field.

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References

  1. Ahmed N, De D, Hussain I (2018) Internet of things (IoT) for smart precision agriculture and farming in rural areas. IEEE Internet Things J 5(6):4890–4899

    Article  Google Scholar 

  2. Ban F, Wu D, Hei Y (2018) Combined forecasting model of urban water consumption based on adaptive filtering and BP neural network. Int J Soc Humanist Computing (IJSHC) 3(1):34–45

    Article  Google Scholar 

  3. Choi Y-C, Chang I-H (2019) The Smart Farm in the Age of the Fourth Industrial Revolution. Korean Ins Commun Sci (Inf Commun) 36(3):9–16

    MathSciNet  Google Scholar 

  4. FireBase(2018) https://firebase.google.com/docs/cloud-messaging/concept-options?hl=ko

  5. forbiz Media (2019). http://www.forbiz.net/news/articleView.html?idxno=17522

  6. Joo H-J, Jeong H-Y (2017) Growth analysis system for IT-based plant factory. Multimed Tools Appl 76(17):17785–17799

    Article  Google Scholar 

  7. Kim S-J (2017) Development of IoT Based Home Appliances Individual Power Control Smart Switch and Smart Consumer Service. J KIIT(Korean Ins Inf Technol) 15(9):117–124

    Google Scholar 

  8. Kim SC (2018) Korean smart farm for agricultural innovation. Korean Auton Soc Mon Public C, Public Policy 151:62–64

    Google Scholar 

  9. Paliwal N, Vanjani P, Liu JW, Saini S, Sharma A (2019) Image processing-based intelligent robotic system for assistance of agricultural crops. Int J Soc Humanist Computing (IJSHC) 3(2):191–204

    Article  Google Scholar 

  10. Raut R, Varma H, Mulla C, Pawar VR (2017) Soil monitoring, fertilization, and irrigation system using IoT for agricultural application, Intelligent Communication and Computational Technologies pp 67-73

  11. Samsung display news room homepage (2018). http://news.samsungdisplay.com/16707

  12. SjaakWolfert L G, CorVerdouw, M-J B(2017) Big Data in Smart Farming – A review, Agricultural Systems, AGRICULTURAL SYSTEMS, Elsevier Science B.V,153: 69–80

  13. Yu H-J, Son C-H (2019) Recognizing Apple Leaf Diseases via Segmentation-Aware Deep Convolutional Neural Networks for Smart Farm. J KIIT(Korean Ins Inf Technol) 17(6):73–83

    Google Scholar 

Download references

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Correspondence to Young Jae Lee.

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This article has been retracted. Please see the retraction notice for more detail:https://doi.org/10.1007/s11042-022-13854-4

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Kim, J., Lee, Y.J. RETRACTED ARTICLE: Smart indoor crop grower based on smart database using IoT. Multimed Tools Appl 80, 34313–34331 (2021). https://doi.org/10.1007/s11042-021-10790-7

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  • DOI: https://doi.org/10.1007/s11042-021-10790-7

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