Dae-Heon Park

A Study on Greenhouse Automatic Control System Based on Wireless Sensor Network

The system proposed in this paper collects temperature of leaves and humidity on leaves of crop. As well as greenhouse environmental information such as temperature, humidity, etc. Crop diseases, especially, have deep relationship not only with indoor environmental factors but also with humidity lasting time on leaves and temperature of leaves. Accordingly, monitoring crop itself is as important as monitoring indoor environments. Using these collected greenhouse environmental data, indoor environments can be more effectively controlled, and monitoring crop itself can contribute to improve productivity and to prevent crops from damages by blight and harmful insects. In addition, it will be possible for farmers to do control plant growth through closely studying relationship between indoor environmental information and monitored information on crop itself. Collected data can be stored to database either in server installed in greenhouse or to remote server. It is made possible to collect information and control effectively and automatically greenhouse in the site or from a remote place through web browser. System components are: temperature sensor, humidity sensor, leaf temperature sensor, leaf humidity sensor, Zigbee based wireless sensor node, relay nodes for automatic control, and data server to store greenhouse information. The system is implemented using low power wireless components, and easy to install.

Wireless Sensor Network-Based Greenhouse Environment Monitoring and Automatic Control System for Dew Condensation Prevention

Dew condensation on the leaf surface of greenhouse crops can promote diseases caused by fungus and bacteria, affecting the growth of the crops. In this paper, we present a WSN (Wireless Sensor Network)-based automatic monitoring system to prevent dew condensation in a greenhouse environment. The system is composed of sensor nodes for collecting data, base nodes for processing collected data, relay nodes for driving devices for adjusting the environment inside greenhouse and an environment server for data storage and processing. Using the Barenbrug formula for calculating the dew point on the leaves, this system is realized to prevent dew condensation phenomena on the crop’s surface acting as an important element for prevention of diseases infections. We also constructed a physical model resembling the typical greenhouse in order to verify the performance of our system with regard to dew condensation control.

An in-depth analysis on traffic flooding attacks detection and system using data mining techniques

Recently, as network traffic flooding attack such as DoS and DDoS have posed devastating threats on network services, rapid detection, and semantic analysis are the major concern for secure and reliable network services. In addition, in a recent issue of the safety and comfort of vehicles and communication technologies for service is required. We propose a traffic flooding attack detection and an in-depth analysis system that uses data mining techniques. In this paper we (1) designed and implemented a system that detects traffic flooding attacks. Then, it executes classification by attack type and it uses SNMP MIB information based on C4.5 algorithm; (2) conducted a semantic interpretation that extracts and analyzes the rules of execution mechanism that are additionally provided by C4.5; (3) performed an in-depth analysis on the attack patterns and useful knowledge inherent in their data by type, utilizing association rule mining. Classification by attack and attack type based on C4.5 and association rules, automatic rule extraction and semantic in-depth interpretation, which are proposed in this paper, provide a positive possibility to add momentum towards the development of new methodologies for intrusion detection systems as well as to support establishing policies for intrusion detection and response systems.

Localization Algorithm Design and Implementation to Utilization RSSI and AOA of Zigbee

In this paper, we has implemented the localization algorithm through RSSI and AOA of Zigbee. The RSSI (Received Signal Strength Indicator) method is used for the localization of Zigbee and affected a lot by intensity, distance and interruption of signals. The combined algorithm of AOA (Angle of Arrival) and RSSI has been designed and implemented to make up the weaknesses of RSSI. As long as we knew, although the previous system has been implemented and used through the UWB (Ultra Wide-Band) or CSS communication methods, the firstly implemented system is the location recognition algorithm through RSSI and AOA of Zigbee. In this paper has obtained the result from the repeated tests to achieve the measurement of location with the accuracy of average 35 ~ 36 cm when the suggested system was placing the beacon on the four corners of 2 dimensional rectangular space with 4m wide and 2m long, and the receiver on the random space.

AoA Localization System Design and Implementation Based on Zigbee for Applying Greenhouse

In this paper, we showed AoA localization system design and implementation based on Zigbee for applying Greenhouse. The proposed system can be realized with low-cost. Our system can provide various applications in the Greenhouse. That can be output forecasts or equipment control by sector. In this paper, We build a testbed and has obtained the result from the repeated tests to achieve the measurement of location with the accuracy of average 35 cm.

Real-time cooling load forecasting using a hierarchical multi-class SVDD

In this paper, we propose a real-time cooling load forecasting system in order to overcome the problems of the conventional methods. The proposed system is a new load forecasting model that hierarchically combines Support Vector Data Descriptions (SVDDs). The proposed system selects an optimal attribute subset by our cooling load forecasting system that enables real-time load data generation and collection. The system is composed of two layers: The first layer predicts the time slots in three representative forms: morning, midday and afternoon. The second layer performs specialized prediction of each individual time slot. Since the proposed system enables both coarse-and fine-grained forecasting, it can efficient cooling load management. Moreover, even when a new time slot emerges, it can be easily adapted for incremental updating and scaling. The performance of the proposed system is validated via experiments which confirm that the recall and precision measures of the method are satisfactory.

One-to-One Embedding between Honeycomb Mesh and Petersen-Torus Networks

As wireless mobile telecommunication bases organize their structure using a honeycomb-mesh algorithm, there are many studies about parallel processing algorithms like the honeycomb mesh in Wireless Sensor Networks. This paper aims to study the Peterson-Torus graph algorithm in regard to the continuity with honeycomb-mesh algorithm in order to apply the algorithm to sensor networks. Once a new interconnection network is designed, parallel algorithms are developed with huge research costs to use such networks. If the old network is embedded in a newly designed network, a developed algorithm in the old network is reusable in a newly designed network. Petersen-Torus has been designed recently, and the honeycomb mesh has already been designed as a well-known interconnection network. In this paper, we propose a one-to-one embedding algorithm for the honeycomb mesh (HMn) in the Petersen-Torus PT(n,n), and prove that dilation of the algorithm is 5, congestion is 2, and expansion is 5/3. The proposed one-to-one embedding is applied so that processor throughput can be minimized when the honeycomb mesh algorithm runs in the Petersen-Torus.

Ad-Hoc Localization Method Using Ranging and Bearing

In Ad-hoc sensor networks, it is very essential for sensors to know their own positions exactly which provide the context to sensed data. Sensors in Ad-hoc sensor networks enable to locate their positions from a relatively small number of landmarks that know their coordinates through external means (e.g., GPS). In this paper, we assume that sensor nodes can measure the distances and relative bearings to neighboring nodes within their transmission range. The proposed method will utilize the distances and relative bearings to find the locations of nodes. Firstly, sensors nearest landmarks will locate their position and then in order nodes more hops far from landmark will. We utilize many landmark coordinates and multiple paths to a landmark to improve the accuracy of the position. Simulation results under the various conditions have been obtained and especially compared with the results using DV-hop and DV-distances.

Greenhouse Environment Monitoring and Automatic Control System Based on Dew Condensation Prevention

Dew condensation on the leaf surface of greenhouse crops causes diseases by fungus, and thus badly affecting the growth of the crops. In this paper, we present a WSN based automatic control system to prevent dew condensation in the greenhouse environments. The system is composed of sensor nodes for collecting data, base nodes for processing collected data, relay nodes for adjusting the environment inside a greenhouse and an environment server for storage and processing of collected data. Using the Barenbrug formula for calculating the dew point on the leaves, this system is realized to prevent a dew condensation phenomenon on the crops surface acting as an important element in diseases generation. We also constructed a test bed the usual greenhouse in order to verify the performance of our system with regard to dew condensation control.

Location-Based Intelligent Robot Management Service Model Using RGPSi with AoA for Vertical Farm

The purpose of this paper is that intelligent robot control service model is one of the service model for a complete auto control system in vertical farm. This model provides environment monitoring service based on context-aware without human intervention in vertical farm. These service need to provide necessary accurate locations indoor environment based on Ubiquitous Sensor Network (USN). It will precisely monitor crop growth environment by intelligent robot using the indoor localization algorithm based on Ratiometric Global Positioning System iteration (RGPSi) with Angle of Arrival (AoA). Therefore, this model makes it possible to shorten operate time and to decrease workforce in vertical farm. It also will contribute to the complete auto control system of vertical farm on a large scale.