scholarly journals Real-time Monitoring of Temperature and Relative Humidity and Visualization of Pest Survey Data for Integrated Pest Management in Collection Storage Area

2021 ◽  
Vol 37 (5) ◽  
pp. 440-450
Author(s):  
Ik-Gyun Im ◽  
Seong-Duk Lim ◽  
Gyu-Seong Han

Temperature and humidity data collection using real-time sensors and data loggers was conducted for integrated pest management in the collection storage and exhibition space of the Jeongnimsaji Museum, Buyeo. The real-time temperature and humidity monitoring system collected measurement data every 30 minutes and enabled real-time confirmation of the data through a linked application. If the temperature and humidity data measured in the real-time temperature and humidity monitoring system exceeds the set range, a push notification was sent to the mobile phone of the person in charge to provide status information to establish a continuous management system. Through this, it was possible to immediately recognize and take action when the temperature range exceeded the recommended relic temperature in August. We performed data visualization on the concentration of airborne fungus in the storage area and the inflow path and density of insects. Based on the recommended criteria presented by the National Institute of Cultural Heritage, The data on the spatial and temporal concentration of airborne fungus inside the collection storage were found to be maintained at a value below the standard recommended by the National Institute of Cultural Heritage (80 CFU/m3). Also, as a result of the insect inflow survey, no insects were captured inside the storage area, and in the case of the exhibition space, insects such as Scutigera coleoptrata, Loxoblemmus arietulus, Diestrammena asynamora, Koreoniscus racovitzai were captured. Based on this, as a result of visualization according to the individual density of captured insects by area, it was confirmed that the main inflow paths of insects were the external entrance and the toilet area.

Author(s):  
Firdaus Hashim ◽  
Roslina Mohamad ◽  
Murizah Kassim ◽  
Saiful Izwan Suliman ◽  
Nuzli Mohamad Anas ◽  
...  

<span>Temperature and humidity are among the parameters that significant to the industrial and agricultural. Traditionally, these elements are monitored inefficiently through wired monitoring system that caused higher implementation and maintenance cost. In addition, the device to detect the temperature such thermometer is not suitable for real-time monitoring since it need a longer response time to measure. With the advent of wireless technology, the temperature and humidity are monitored remotely and effectively. This paper aims to describe the implementation of an embedded real-time temperature and humidity monitoring system, using Arduino for Internet of Things (IoT) application.  The system integrates the Arduino node with a dashboard system call Node-FRED, which interfaced to the LoRa radio through the Things Network gateway. This IoT application is deployed on both indoor and outdoor environment, to investigate the relation between the temperature and humidity level in order to manage the environment at more comfort level.</span>


2013 ◽  
Vol 333-335 ◽  
pp. 460-464
Author(s):  
Bo Xu ◽  
Yong Jun Zheng ◽  
Yan Xin Yin ◽  
Yu Tan

This paper introduced a system based on wireless network technology, which achieved node-to-node data collection and transmission. The ZigBee-based wireless network of the system adopted the chip CC2530 of TI company. The system developed applications based on Z-STACK for data collection and wireless transmission, it used VC++ to make a PC software for real-time monitoring of temperature and humidity. The research results show the feasibility of the system, and it would be widely used in the measure field of agriculture.


2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Yong He ◽  
Hong Zeng ◽  
Yangyang Fan ◽  
Shuaisheng Ji ◽  
Jianjian Wu

In this paper, we proposed an approach to detect oilseed rape pests based on deep learning, which improves the mean average precision (mAP) to 77.14%; the result increased by 9.7% with the original model. We adopt this model to mobile platform to let every farmer able to use this program, which will diagnose pests in real time and provide suggestions on pest controlling. We designed an oilseed rape pest imaging database with 12 typical oilseed rape pests and compared the performance of five models, SSD w/Inception is chosen as the optimal model. Moreover, for the purpose of the high mAP, we have used data augmentation (DA) and added a dropout layer. The experiments are performed on the Android application we developed, and the result shows that our approach surpasses the original model obviously and is helpful for integrated pest management. This application has improved environmental adaptability, response speed, and accuracy by contrast with the past works and has the advantage of low cost and simple operation, which are suitable for the pest monitoring mission of drones and Internet of Things (IoT).


2014 ◽  
Vol 651-653 ◽  
pp. 436-439
Author(s):  
Yun Jie Li ◽  
Yan Yu Wang ◽  
Jia Yin ◽  
Cheng Quan Pei ◽  
Xiao Li Ma

HIRFL is an all-powerful heavy ion accelerator which is built by IMP of Chinese Academy of Science. It bears a lot of research tasks for china. Its control and monitoring system is very complex and very important, directly determines whether HIRFL safe operation. This paper is to study its much control and monitoring system of temperature and humidity monitoring system. Began to study the basic structure of the hardware, a specific architecture and specific HMI is designed, as well as the situation in the field installation deployment.


2017 ◽  
Author(s):  
Junyu Yu ◽  
Peng Xu ◽  
Zitao Peng ◽  
Haonan Qiang ◽  
Xiaoyan Shen

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