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- 저자 : Renshan Jia (검색결과 2 건)
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A Student Based Biometric Application
Renshan Jia 사단법인 미래융합기술연구학회 2019 아시아태평양융합연구교류논문지 Vol.5 No.4
The latest developments in technology especially in the field of computer science provided a new scope for IOT (internet of things). IOT makes use of sensors and the internet it is a combination of hardware and software functioning together. The identification of a person is becoming importance day to day due to various reasons. Some reasons may be security reasons while some others reason may be to identify the persons easily rather than asking them individually which a time taking process. Hence, more importance was been giving to make the identification of a person more automatic and the process can be made more easy. The important factors to be considered for identifying a person are the facial expressions or structures, biometric and the iris of a person. Hence, in the current article an attempt has been made to automate the attendance system automatic by collecting the fingerprints of the students and the attendance of students are made automatic. This application was being developed with the IoT model and the results are more encouraging.
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Remote Monitoring of Heading Rice Growing and Nitrogen Content Based on UAV Images
Yu Zhang,Zhongbin Su,Weizheng Shen,Renshan Jia,Jiling Luan 보안공학연구지원센터 2016 International Journal of Smart Home Vol.10 No.7
Rice heading is the critical stage of the growth of rice, rice plants are relatively large, field canopy, poor resistance, and coincided with the high temperature and rainy weather, pests and diseases are more prone period. Therefore, the use of UAV to monitor the growth status of rice, easy to understand rice growth and nutritional status, in order to achieve high-quality, high yield, efficient purpose. This article is the field experiments under different nitrogen levels, using UAV monitoring multispectral images of rice, by reference remote sensing spectral indices, derived green normalized difference vegetation index (GNDVI) relative to other spectral index is more suitable for rice field biomass inversion modeling. At the same time, this study is based on the inversion model, implemented the rice growing and nitrogen content graded by ISODATA methods in ENVI. Achieved classification on rice growth and nitrogen remote sensing thematic map in ArcGIS, to provide timely and accurate information for rice seedling diagnosis and management decision, has reached the purpose of rice production precise management.
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