GreenVMAS: Virtual Organization Based Platform for Heating Greenhouses Using Waste Energy from Power Plants.

The gradual depletion of energy resources makes it necessary to optimize their use and to reuse them. Although great advances have already been made in optimizing energy generation processes, many of these processes generate energy that inevitably gets wasted. A clear example of this are nuclear, thermal and carbon power plants, which lose a large amount of energy that could otherwise be used for different purposes, such as heating greenhouses. The role of GreenVMAS is to maintain the required temperature level in greenhouses by using the waste energy generated by power plants. It incorporates a case-based reasoning system, virtual organizations and algorithms for data analysis and for efficient interaction with sensors and actuators. The system is context aware and scalable as it incorporates an artificial neural network, this means that it can operate correctly even if the number and characteristics of the greenhouses participating in the case study change. The architecture was evaluated empirically and the results show that the user's energy bill is greatly reduced with the implemented system.

Monitoring Activity for Recognition of Illness in Experimentally Infected Weaned Piglets Using Received Signal Strength Indication ZigBee-based Wireless Acceleration Sensor.

In this experiment, we proposed and implemented a disease forecasting system using a received signal strength indication ZigBee-based wireless network with a 3-axis acceleration sensor to detect illness at an early stage by monitoring movement of experimentally infected weaned piglets. Twenty seven piglets were divided into control, Salmonella enteritidis (SE) infection, and Escherichia coli (EC) infection group, and their movements were monitored for five days using wireless sensor nodes on their backs. Data generated showed the 3-axis movement of piglets (X-axis: left and right direction, Y-axis: anteroposterior direction, and Z-axis: up and down direction) at five different time periods. Piglets in both infected groups had lower weight gain and feed intake, as well as higher feed conversion ratios than the control group (p<0.05). Infection with SE and EC resulted in reduced body temperature of the piglets at day 2, 4, and 5 (p<0.05). The early morning X-axis movement did not differ between groups; however, the Y-axis movement was higher in the EC group (day 1 and 2), and the Z-axis movement was higher in the EC (day 1) and SE group (day 4) during different experimental periods (p<0.05). The morning X and Y-axis movement did not differ between treatment groups. However, the Z-axis movement was higher in both infected groups at day 1 and lower at day 4 compared to the control (p<0.05). The midday X-axis movement was significantly lower in both infected groups (day 4 and 5) compared to the control (p<0.05), whereas the Y-axis movement did not differ. The Z-axis movement was highest in the SE group at day 1 and 2 and lower at day 4 and 5 (p<0.05). Evening X-axis movement was highest in the control group throughout the experimental period. During day 1 and 2, the Z-axis movement was higher in both of the infected groups; whereas it was lower in the SE group during day 3 and 4 (p<0.05). During day 1 and 2, the night X-axis movement was lower and the Z-axis movement was higher in the infected piglets (p<0.05). Overall, the movement of infected piglets was altered, and the acceleration sensor could be successfully employed for monitoring pig activity.

Analysis of environmental stress factors using an artificial growth system and plant fitness optimization.

The environment promotes evolution. Evolutionary processes represent environmental adaptations over long time scales; evolution of crop genomes is not inducible within the relatively short time span of a human generation. Extreme environmental conditions can accelerate evolution, but such conditions are often stress inducing and disruptive. Artificial growth systems can be used to induce and select genomic variation by changing external environmental conditions, thus, accelerating evolution. By using cloud computing and big-data analysis, we analyzed environmental stress factors for Pleurotus ostreatus by assessing, evaluating, and predicting information of the growth environment. Through the indexing of environmental stress, the growth environment can be precisely controlled and developed into a technology for improving crop quality and production.

Study on the context-aware middleware for ubiquitous greenhouses using wireless sensor networks.

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.

Study of the ubiquitous hog farm system using wireless sensor networks for environmental monitoring and facilities control.

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.

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.

Independent inverse relationship between serum lycopene concentration and arterial stiffness.

OBJECTIVE: Emerging evidence suggests a role of lycopene in the primary prevention of cardiovascular disease. This study aimed to investigate the association of serum lycopene concentration with brachial-ankle pulse wave velocity (baPWV), a marker of arterial stiffness and markers of oxidative stress and inflammation. METHODS: healthy women (n=264, 31-75 yrs) were classified into tertiles according to serum lycopene concentration. Multivariate linear regression analyses were used to assess the relationship between serum lycopene and baPWV. RESULTS: Subjects in middle tertile (T2) and upper tertile (T3) had lower baPWV (1263+/-23 and 1265+/-14 cm/s vs. 1338+/-21 cm/s; p=0.009) and lower oxidized LDL (oxLDL) (53+/-3 and 55+/-3 U/L vs. 66+/-3 U/L; p<0.001) than those in lower tertile (T1). Subjects in T3 showed higher LDL particle size (24.3+/-0.08 nm vs. 24.0+/-0.07 nm, p=0.005) and lower C-reactive protein (hs-CRP) (0.80+/-0.25mg/dL vs. 1.27+/-0.24 mg/dL, p=0.015), compared with those in T1. Logistic regression analysis showed that baPWV decreased with the increment of lycopene concentration; log baPWV decreased by 0.21 cm/s (95% CI -0.168;-0.045, p=0.001) per unit change in lycopene. After adjustment for age, BMI, smoking, drinking, menopause and blood pressure, the estimated effect was attenuated by 35%, but remained statistically significant [-0.13 cm/s (95% CI -0.112;-0.018, p=0.006)]. Further adjustment for beta-carotene, alpha-tocopherol, oxLDL, LDL particle size, and hs-CRP increased the strength of the association [beta=-0.221 (95% CI -0.215;-0.012, p=0.029)]. CONCLUSION: This study supports the presence of an independent inverse relationship between circulating lycopene and baPWV. Additionally, reduced oxidative modification of LDL may be one of mediators on the mechanisms how lycopene reduces arterial stiffness.