Study on an Agricultural Environment Monitoring Server System using Wireless Sensor Networks

This paper proposes an agricultural environment monitoring server system for monitoring information concerning an outdoors agricultural production environment utilizing Wireless Sensor Network (WSN) technology. The proposed agricultural environment monitoring server system collects environmental and soil information on the outdoors through WSN-based environmental and soil sensors, collects image information through CCTVs, and collects location information using GPS modules. This collected information is converted into a database through the agricultural environment monitoring server consisting of a sensor manager, which manages information collected from the WSN sensors, an image information manager, which manages image information collected from CCTVs, and a GPS manager, which processes location information of the agricultural environment monitoring server system, and provides it to producers. In addition, a solar cell-based power supply is implemented for the server system so that it could be used in agricultural environments with insufficient power infrastructure. This agricultural environment monitoring server system could even monitor the environmental information on the outdoors remotely, and it could be expected that the use of such a system could contribute to increasing crop yields and improving quality in the agricultural field by supporting the decision making of crop producers through analysis of the collected information

A Wireless Sensor Network-Based Ubiquitous Paprika Growth Management System

Wireless Sensor Network (WSN) technology can facilitate advances in productivity, safety and human quality of life through its applications in various industries. In particular, the application of WSN technology to the agricultural area, which is labor-intensive compared to other industries, and in addition is typically lacking in IT technology applications, adds value and can increase the agricultural productivity. This study attempts to establish a ubiquitous agricultural environment and improve the productivity of farms that grow paprika by suggesting a ‘Ubiquitous Paprika Greenhouse Management System’ using WSN technology. The proposed system can collect and monitor information related to the growth environment of crops outside and inside paprika greenhouses by installing WSN sensors and monitoring images captured by CCTV cameras. In addition, the system provides a paprika greenhouse environment control facility for manual and automatic control from a distance, improves the convenience and productivity of users, and facilitates an optimized environment to grow paprika based on the growth environment data acquired by operating the system

A Data-Based Fault-Detection Model for Wireless Sensor Networks

With the expansion of smart agriculture, wireless sensor networks are being increasingly applied. These networks collect environmental information, such as temperature, humidity, and CO2 rates. However, if a faulty sensor node operates continuously in the network, unnecessary data transmission adversely impacts the network. Accordingly, a data-based fault-detection algorithm was implemented in this study to analyze data of sensor nodes and determine faults, to prevent the corresponding nodes from transmitting data; thus, minimizing damage to the network. A cloud-based “farm as a service” optimized for smart farms was implemented as an example, and resource management of sensors and actuators was provided using the oneM2M common platform. The effectiveness of the proposed fault-detection model was verified on an integrated management platform based on the Internet of Things by collecting and analyzing data. The results confirm that when a faulty sensor node is not separated from the network, unnecessary data transmission of other sensor nodes occurs due to continuous abnormal data transmission; thus, increasing energy consumption and reducing the network lifetime

IoT-Based Strawberry Disease Prediction System for Smart Farming

Crop diseases cannot be accurately predicted by merely analyzing individual disease causes. Only through construction of a comprehensive analysis system can users be provided with predictions of highly probable diseases. In this study, cloud-based technology capable of handling the collection, analysis, and prediction of agricultural environment information in one common platform was developed. The proposed Farm as a Service (FaaS) integrated system supports high-level application services by operating and monitoring farms as well as managing associated devices, data, and models. This system registers, connects, and manages Internet of Things (IoT) devices and analyzes environmental and growth information. In addition, the IoT-Hub network model was constructed in this study. This model supports efficient data transfer for each IoT device as well as communication for non-standard products, and exhibits high communication reliability even in poor communication environments. Thus, IoT-Hub ensures the stability of technology specialized for agricultural environments. The integrated agriculture-specialized FaaS system implements specific systems at different levels. The proposed system was verified through design and analysis of a strawberry infection prediction system, which was compared with other infection models

Introduction of Infection Prevention Tracheal Intubation Protocol during the COVID-19 Pandemic Is Not Associated with First-Pass Success Rates of Endotracheal Intubation in the Emergency Department: A Before-and-After Comparative Study

Aerosols and droplets have put healthcare workers performing airway management at high risk of contracting coronavirus disease 2019 (COVID-19). Experts have developed endotracheal intubation (ETI) guidelines and protocols to protect intubators from infection. We aimed to determine whether changes in the emergency department (ED) intubation protocol to prevent COVID-19 infection were associated with first-pass success (FPS) rates in ETI. We used data from the airway management registries in two academic EDs. The study was divided into pre-pandemic (January 2018 to January 2020) and pandemic (February 2020 to February 2022) periods. We selected 2476 intubation cases, including 1151 and 1325 cases recorded before and during the pandemic, respectively. During the pandemic, the FPS rate was 92.2%, which did not change significantly, and major complications increased slightly but not significantly compared with the pre-pandemic period. The OR for the FPS of applying infection prevention intubation protocols was 0.72 (p = 0.069) in a subgroup analysis, junior emergency physicians (PGY1 residents) had an FPS of less than 80% regardless of pandemic protocol implementation. The FPS rate of senior emergency physicians in physiologically difficult airways decreased significantly during the pandemic (98.0% to 88.5%). In conclusion, the FPS rate and complications for adult ETI performed by emergency physicians using COVID-19 infection prevention intubation protocols were similar to pre-pandemic conditions

Cardiac arrest associated with pneumorrhachis and pneumocephalus after epidural analgesia: two case reports

Abstract Background Epidural analgesia has become a common procedure to provide excellent pain relief with few complications. Pneumorrhachis and pneumocephalus are rare complications of unintentional dural puncture and injection of air into the subarachnoid or subdural space. No cases of cardiac arrest associated with these complications have been reported in the literature previously. Case presentation We report cases of pneumorrhachis and pneumocephalus in two Korean women who previously visited a local pain clinic and underwent epidural analgesia. Thereafter, they were admitted to the emergency department with cardiac arrest. Cardiopulmonary resuscitation was performed on these patients, and return of spontaneous circulation was achieved. The brain and spine computed tomographic scans showed pneumorrhachis and pneumocephalus, respectively. These cases demonstrate that pneumorrhachis and pneumocephalus may occur after epidural analgesia, which may be associated with cardiac arrest in patients. Conclusions If cardiac arrest occurs after epidural analgesia, pneumocephalus and pneumorrhachis should be considered as its cause. Although epidural analgesia is a common procedure, caution is warranted during this procedure