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.

There has been much research and various attempts to apply new IoT technology to agricultural areas. However, IoT for the agriculture should be considered differently against the same areas such as industrial, logistics. This paper presents the IoT-based agricultural production system for stabilizing supply and demand of agricultural products while developing the environment sensors and prediction system for the growth and production amount of crops by gathering its environmental information. Currently, the demand by consumption of agricultural products could be predicted quantitatively, however, the variation of harvest and production by the change of farm's cultivated area, weather change, disease and insect damage etc. could not be predicted, so that the supply and demand of agricultural products has not been controlled properly.To overcome it, this paper designed the IoT-based monitoring system to analyze crop environment, and the method to improve the efficiency of decision making by analyzing harvest statistics. Therefore, this paper developed the decision support system to forecast agricultural production using IoT sensors. This system was also a unified system that supports the processes sowing seeds through selling agricultural products to consumers.The IoT-based agricultural production system through correlation analysis between the crop statistical information and agricultural environment information has enhanced the ability of farmers, researchers, and government officials to analyze current conditions and predict future harvest. Additionally, agricultural products quality can be improved because farmers observe whole cycle from seeding to selling using this IoT-based decision support system.

Behavior is one of the most commonly used indicators of illness; however, few studies have investigated how different common diseases affect animal behavior. This experiment was conducted to investigate behavioral and clinical alterations in growing pigs experimentally infected with Salmonella spp. during a 4-week post-infection period. A total of 48 growing pigs were divided into one of the three treatment groups (1) control, (2) infection with Salmonella Typhimurium or (3) infection with Salmonella Enteritidis. Individual pigs’ behavior was recorded daily (0900 to 1100 and 1600 to 1800 h) using a video-recording system. Pigs in both infected groups had lower weight gain and feed intake during week 0 to 2 and 0 to 4 experimental period. Bacteriological data revealed that pigs in both infected groups persistently shed bacteria throughout the period of study. Oral infection of growing pigs with S. Typhimurium and S. Enteritidis significantly reduced the frequency of morning large (except week 1) and small movement throughout the study period. In the evening, significantly lowest frequency of movements were observed in the S. Enteritidis-infected group compared with the control. The standing and sitting frequency were significantly lower in both infected groups only at the morning of week 4. Infection with Salmonella spp. led to a significant reduction in the frequency and duration of morning eating and drinking throughout the experimental period, with the exception of 4th week drinking duration. The lowest frequency of evening eating during week 1 and 4 was recorded in both infected groups; whereas, the duration differed only at week 1. The evening drinking frequency only tended to decrease in response to S. Typhimurium infection at week 1. This study shows that, pigs infected with Salmonella spp. had poor performance, shedding high levels of Salmonella with their feces and reduced feeding and drinking activity, which are adaptive responses to infection and may help caretakers to detect ill health.

Wireless Sensor Network (WSN) technology is one of the important technologies to implement the ubiquitous society, and it could increase productivity of agricultural and livestock products, and secure transparency of distribution channels if such a WSN technology were successfully applied to the agricultural sector. Middleware, which can connect WSN hardware, applications, and enterprise systems, is required to construct ubiquitous agriculture environment combining WSN technology with agricultural sector applications, but there have been insufficient studies in the field of WSN middleware in the agricultural environment, compared to other industries. This paper proposes a context-aware middleware to efficiently process data collected from ubiquitous greenhouses by applying WSN technology and used to implement combined services through organic connectivity of data. The proposed middleware abstracts heterogeneous sensor nodes to integrate different forms of data, and provides intelligent context-aware, event service, and filtering functions to maximize operability and scalability of the middleware. To evaluate the performance of the middleware, an integrated management system for ubiquitous greenhouses was implemented by applying the proposed middleware to an existing greenhouse, and it was tested by measuring the level of load through CPU usage and the response time for users’ requests when the system is working.

Many hog farmers are now suffering from high pig mortality rates due to various wasting diseases and increased breeding costs, etc. It is therefore necessary for hog farms to implement systematic and scientific pig production technology to increase productivity and produce high quality pork in order to solve these problems. In this study, we describe such a technology by suggesting a ubiquitous hog farm system which applies WSN (Wireless Sensor Network) technology to the pig industry. We suggest that a WSN and CCTV (Closed-circuit television) should be installed on hog farms to collect environmental and image information which shall then help producers not only in monitoring the hog farm via the Web from outside the farm, but also facilitate the control of hog farm facilities in remote locations. In addition, facilities can be automatically controlled based on breeding environment parameters which are already set up and a SMS notice service to notify of deviations shall provide users with convenience. Hog farmers may increase production and improve pork quality through this ubiquitous hog farm system and prepare a database with information collected from environmental factors and the hog farm control devices, which is expected to provide information needed to design and implement suitable control strategies for hog farm operation.