Hyun Yeo

Design and implimentation of pig farm monitoring system for ubiquitous agriculture

The ubiquitous pig farm monitoring system is designed so that it can be applied to modern agriculture, which is becoming bigger and more advanced. In the immediate previous research, a large scale ubiquitous pig farm monitoring system was designed and it was applied to actual pig farms. It was possible to realize the system, where the raising efficiency of pig was maximized by installing the temperature/humidity sensors and video camera, transmitting the measured information to caretaker in real time. When the measured environmental information values detected by the sensor would get out of optimum raising environment of pigs, the system transmitted the content to the caretaker. Simultaneously, the environment control facilities such as humidifier, air conditioner and window opener/closer were activated in order to maintain the environmental information at uniform and pleasant values.

Design and Evaluation of Soil pH IoT Sensor Attribute for Rice Agriculture in Central Africa

The IoT platform is a crucial middleware that allows us to walk safely in the field of IoT agriculture. The Rice Intensification System (SRI) uses less water and improves rice yield through the synergy of several agronomic management practices around the world. Rice is a staple crop for many countries and is one of the three main food crops in Central Africa. Environmental stresses such as drought, salinity, disease, acidity and iron toxicity can limit growth and performance. In Central Africa, rice is grown mainly in the lowlands. Africa consumes 11.5 million tons of rice per year, of which 33.6% is imported. Import trends showed only a slight decrease of 55 000 tones, while rice production increased by 2.3 million tones. And Central Africa’s average self-sufficiency reached 37.9%. This is new way of more production in agriculture sector for saving a life have to be researched. The most natural one being the use of different machine in farm by connecting different sensors, connected devices, developing intelligent breeding systems as much as possible. In the paper, an architecture based on IoT agriculture is proposed after analyzing of soil organic. This work includes the expansion of rice management scales, including human resources, water and agricultural land; response strategies to irrigation during the drought; and the application of several agricultural water resources. Finally, it presents a architecture for IoT agriculture services based on cloud sensor infrastructure. Our results show that rice should be planted in lowland rice production systems in Central Africa.

Structuring CAMA (Context Area Mobile Applications) in SOA (Service Oriented Architecture) and MDA (Modern Driven Architecture)

Model Driven Architecture (MDA), as we consider the growing significance and utility of modeling in the development of software and solutions, it reflects the benefits of MDA to transform one PIM into several PSMs, each for platform or technology in which the final system will be deployed, and the automatic code generation that implements the system for those platforms from the corresponding PSMs. Service-oriented architectures (SOA) are also presented as the key to business agility, especially when combined with a model-driven approach. Model-Driven Architecture (MDA) is a well-developed idea that fits well with SOA, but as of today, it has been a specialized technique that is beyond practical application scope of most enterprises. Our view is that MDA aims at giving detailed framework for software production. The framework given, a unified modeling architecture, which illustrates how the two architectures can be brought together into one, was presented in this study.

Building Scalable View Module of Object-Oriented Database

Many researchers and developers have studied object-oriented relational database management systems (ORDBMS) in the past ten or so years, few have published their results that reveal the inside workings of an ORDBMS. Leading database software companies integrated object-oriented features in their DBMS products only recently. These companies do not make the technical core of their products public. Most academic researchers, on the other hand, have worked on ideas, methodologies and analysis of ORDBMS, but few have shown the database engine of a working system. This paper presents a propotype ORDBMS engine that supports objects in databases, including user-defined types, inheritance, and polymorphous method invocaiton. Although a prototype, it is implemented in Java, fully functional and can be extended should additional modules be added in the future. The system is composed of three major components: the query-command module, the view module, and the database module.

Self-Healing Multi Agent Prototyping System for Crop Production

An agent is a computer system capable of flexible and autonomous action in dynamic, unpredictable and typically multi-agent domains. Most distributed computing environments today are extremely complex and time-consuming for human administrators to manage. Thus, there is increasing demand for the self-healing and self-diagnosing of problems or errors arising in systems operating within today’s ubiquitous computing environment. This paper proposes a proactive self-healing system that monitors, diagnoses and heals its own internal problems using self-awareness as contextual information for crop production monitoring system in the future. The proposed system consists of Multi-Agents that analyze the log context, error events and resource status in order to perform self-healing and self-diagnosis. To minimize the resources used by the Adapters which monitor the logs in an existing system, we place a single process in memory. By this, we mean a single Monitoring Agent monitors the context of the logs generated by the different system components. For rapid and efficient self-healing, we use a 6-step process. The effectiveness of the proposed system is confirmed through practical experiments conducted with a prototype system.

A Novel Methodology for Ubiquitous Agricultural Environments Using the Agricultural Knowledge Cloud

Generally, most of agricultural works have to consider not only fixed data related with a cultivated crop, but also various environmental factors which are dynamically changed. Therefore, a farmer has to consider readjust the fixed data according to the environmental conditions in order to cultivate a crop in optimized growth environments. However, because the readjustment is delicate and complicated, it is difficult for user to by hand on a case by case. To solve the limitations, this paper proposes a novel methodology for ubiquitous agricultural environments using the agricultural knowledge cloud.