论文标题
使用智能语音消息系统的农业知识管理:物理和人类传感器的组合
Agricultural Knowledge Management Using Smart Voice Messaging Systems: Combination of Physical and Human Sensors
论文作者
论文摘要
在农业知识管理系统中使用物联网(IoT)是提高农业效率的最有希望的方法之一。但是,农业中现有的物理传感器受到监测农作物特征的各种变化的限制,对于普通农民来说可能很昂贵。我们提出了物理传感器和人类传感器(五种人类感官)的组合。通过使用自己的眼睛,耳朵,鼻子,舌头和手指,农民可以检查其农作物和设备的特征和条件(叶子,疾病,害虫,故障或故障设备的颜色)的各种变化,并以口头描述他们的观察结果,并用音频录制式设备(例如智能手机)捕获描述。语音记录可以通过Web服务器转录为文本。通过数据和文本挖掘来分析物理和人类传感器(语音消息)捕获的数据,以创建和改善农业知识。使用物理和人类传感器的农业知识管理系统鼓励农民之间共享和转移知识,以提高农业的效率和生产力。我们将这样的农业知识管理系统(智能语音消息系统)应用于北海道的一个温室蔬菜农场。对积累的语音消息和对农民的采访的定性分析证明了该系统的有效性。这项研究的贡献包括一种新的,实用的方法,用于“所有物品的农业互联网(IOE)”,以及在我们在真正的蔬菜农场进行试验实验的结果证明其有效性的证据。
The use of the Internet of Things (IoT) in agricultural knowledge management systems is one of the most promising approaches to increasing the efficiency of agriculture. However, the existing physical sensors in agriculture are limited for monitoring various changes in the characteristics of crops and may be expensive for the average farmer. We propose a combination of physical and human sensors (the five human senses). By using their own eyes, ears, noses, tongues, and fingers, farmers could check the various changes in the characteristics and conditions (colors of leaves, diseases, pests, faulty or malfunctioning equipment) of their crops and equipment, verbally describe their observations, and capture the descriptions with audio recording devices, such as smartphones. The voice recordings could be transcribed into text by web servers. The data captured by the physical and human sensors (voice messages) are analyzed by data and text mining to create and improve agricultural knowledge. An agricultural knowledge management system using physical and human sensors encourages to share and transfer knowledge among farmers for the purpose of improving the efficiency and productivity of agriculture. We applied one such agricultural knowledge management system (smart voice messaging system) to a greenhouse vegetable farm in Hokkaido. A qualitative analysis of accumulated voice messages and an interview with the farmer demonstrated the effectiveness of this system. The contributions of this study include a new and practical approach to an "agricultural Internet of Everything (IoE)" and evidence of its effectiveness as a result of our trial experiment at a real vegetable farm.