WEKO3
アイテム
スマート農業におけるプラントデータネットワーク
https://doi.org/10.18997/0002000924
https://doi.org/10.18997/000200092472bb3c2b-c8be-44fa-ae86-d26ea9ec8d73
| 名前 / ファイル | ライセンス | アクション |
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jou_k_400.pdf (31.1 MB)
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| アイテムタイプ | 学位論文 = Thesis or Dissertation(1) | |||||||
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| 公開日 | 2024-08-26 | |||||||
| 資源タイプ | ||||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_db06 | |||||||
| 資源タイプ | doctoral thesis | |||||||
| タイトル | ||||||||
| タイトル | Plant Data Networks in Smart Farming | |||||||
| 言語 | en | |||||||
| タイトル | ||||||||
| タイトル | スマート農業におけるプラントデータネットワーク | |||||||
| 言語 | ja | |||||||
| 言語 | ||||||||
| 言語 | eng | |||||||
| 著者 |
Nurdiansyah Sirimorok,
× Nurdiansyah Sirimorok,
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| 抄録 | ||||||||
| 内容記述タイプ | Abstract | |||||||
| 内容記述 | Since it was first introduced in 1999 by computer scientist Kevin Ashton, the Internet of Things (IoT) has recently experienced rapid development. Sensor devices with a smartphone or other integrated devices bring enormous benefits and have changed human behavior, particularly time efficiency and effectiveness. Those development processes still face many constraints, particularly data distribution, security, and node placement into the IoT infrastructure. Those that make IoT vulnerable to intrusions can create damage in mistaken infrastructure management that can threaten IoT networks. We attempt to deal with those problems with several approaches to build a novel network architecture that can be implemented in an agricultural environment to monitor and collect data for increasing agricultural products. The thesis studies novel data network architectures in smart farming. Traditional methods like note-taking, oral transfer of knowledge, and plain sensor data collection are still prevalent. New data network architectures need to be correctly integrated. The thesis follows two approaches here. The first approach is the design of smart watering system based on predicion of soil moisture by using a ”Long Short-Term Memory” (LSTM) neural network, and LORA based remote communication. Training data where collected for 3 months on several plants, and as a result, plant stress states could be correctly identified to above 90%. Thus, Deep Learning can become a key intelligent component for the prospected smart watering system also in practice. The second approach is a novel communication network architecture inspired by the mycelium network. The communication between plants via the underground mycelium nework of fungi (better known as mushrooms) is known for years, but many of its aspects are still not understood. The thesis first explores the relation of such a mycelium network to TCP/IP-based internet and IoT networks. Then, a simulation environment in metaverse environment for mycelium growth and metabolism has been implemented. Experiments of the routing of plant attack signal in such a network were performed. The experiments show the succesfull routing of such signals to specific other plants. At the receiving plant, the farmer can take protective measures. Thus, the research points into a complete novel direction of smart farming by linking sensor signals, chemistry-driven routing principles, and virtualization, and showed its potential to improve safe operation of a farm. The findings from this approach reveal that the concept of a mycelium network in a virtual environment can be used as a solution to overcome the problems of routes in the network, distribution of data and signals, and communication between sensors in network infrastructure. This report proposes a more effective and efficient network system adapted from mycelium networks for smart agriculture. Furthermore, the network system concept we have developed can be a reference framework for building strong network infrastructure within the scope of IoT, especially Smart Farming. Furthermore, based on previous experiments, the results of predicted data collected from several types of sensors for the level of water content in the soil can be identified with an accuracy of up to 90%. This result is the main component for building a smart watering system in an agricultural environment. |
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| 目次 | ||||||||
| 内容記述タイプ | TableOfContents | |||||||
| 内容記述 | 1 Introduction| 2 Existing Transmitting Data in Traditional Farming| 3 Internet of Things (IoT) and Cloud Computing-based Smart Plants Watering System| 4 Mycelium Network Simulation for the Study of Communication Systems Concept| 5 Implementation of a virtual Mycelium Network for Smart Farming Security| 6 Conclusion and Future Works |
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| 備考 | ||||||||
| 内容記述タイプ | Other | |||||||
| 内容記述 | 九州工業大学博士学位論文 学位記番号:情工博甲第400号 学位授与年月日:令和6年6月28日 | |||||||
| 学位授与番号 | ||||||||
| 学位授与番号 | 甲第400号 | |||||||
| 学位名 | ||||||||
| 学位名 | 博士（情報工学） | |||||||
| 学位授与年月日 | ||||||||
| 学位授与年月日 | 2024-06-28 | |||||||
| 学位授与機関 | ||||||||
| 学位授与機関識別子Scheme | kakenhi | |||||||
| 学位授与機関識別子 | 17104 | |||||||
| 学位授与機関名 | 九州工業大学 | |||||||
| 言語 | ja | |||||||
| 学位授与年度 | ||||||||
| 内容記述タイプ | Other | |||||||
| 内容記述 | 令和6年度 | |||||||
| 出版タイプ | ||||||||
| 出版タイプ | VoR | |||||||
| 出版タイプResource | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |||||||
| アクセス権 | ||||||||
| アクセス権 | open access | |||||||
| アクセス権URI | http://purl.org/coar/access_right/c_abf2 | |||||||
| ID登録 | ||||||||
| ID登録 | 10.18997/0002000924 | |||||||
| ID登録タイプ | JaLC | |||||||
