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05992190.pdf

Kyeong-og Kim, Jong-chan Kim, Kyeong-jin Ban Dept. of Computer Engineering Sunchon National University

Suncheon, Korea [email protected], [email protected],

[email protected]

Eung-kon Kim*, Moon-suk Jang Dept. of Computer Engineering

Sunchon Nation University Suncheon, Korea

kek@ suncheon.ac.kr, [email protected]

Abstract—U-IT based technologies are being used in all areas including health, medical care, distribution, transportation, fisheries and agriculture. In relation to these information communication technologies, fusion technologies between IT and traditional industries are rising as a new topic. However, it is true that U-agriculture does not benefit compared to other industries in terms of the improvement of the quality of life through ubiquitous computing. In this paper, a greenhouse environment monitoring system was proposed that would store greenhouses' environment information in DB, compare and analyze optimum growth environment information with items desired by users using linear regression analysis and DIF analysis to manage crop growth environments in real time. This system provided continuous monitoring of optimum growth environments without users' firsthand visiting to greenhouses and thus the efficiency of agricultural product cultivation has been improved as agricultural products were protected from natural disasters.

Keywords-greenhouse; USN; monitoring system;

I. INTRODUCTION

Thanks to the development of Internet technologies, recently, studies are being actively conducted on the configuration of systems to manage greenhouses through the Web to enable farmers to measure, control and monitor greenhouses without firsthand visiting greenhouses. Ubiquitous computing is a representative IT technology which is being applied to all areas in society including the government, the military, health and agriculture. In particular, in Western advanced countries, diverse USN technologies are being incorporated into agriculture as agricultural systems have been commercialized. However, it is true that Korean agriculture technologies do not benefit in terms of the improvement of the quality of life through ubiquitous computing compared to other industrial technologies. In the case of existing greenhouse monitoring systems, there is inconvenience that users should permanently stay at distant places and the risk of malfunctions of machines exists. Therefore, most users are very inconvenient during the night or when they are outside their farms[1, 2].

In this paper, we proposed a greenhouse environment monitoring system that will collect environment information and biometrics from various sensors attached to the inside/outside of greenhouses such as temperature sensors, soil sensors and moisture sensors. The greenhouse environment

monitoring system compared and analyzed optimum growth environment information with items desired by users using linear regression analyses and DIF analyses of collected sensor data to manage crop growth environments in real time. Users can use greenhouse environment data and information for optimum growth environments in real time to control temperatures and moisture appropriately. Using the information in this paper, farmers can prevent natural disasters such as cold-weather damage and withering and continuously provide optimum growth environments to improve the efficiency of agricultural product cultivation.

II. RELATED STUDIES

A. Monitoring systems applied to agricultural environments in foreign countries The Real-time Monitoring using Field Server in Japan uses

the Field Server developed by Matsushita Electric Co. in Japan which is an automatic monitoring system composed of sensors and CCD cameras including the CPU, AD converter, DA converter, ethernet controller, high brightness LED, temperature/humidity/photon density/soil moisture/soil temperature/EC mount/leaf dew/ultraviolet ray sensors. This Field Server is being utilized in monitoring diverse agricultural products and it enables sending receiving data and monitoring in real time at remote places through sensor data middleware called SSG(sensor Service Grid)[3].

Among agricultural product cultivation environment management systems in Korea, the cultivation management system established by Dongbu Information Technology is composed of USN for monitoring and controlling agricultural products' growth environment information and RFID systems for managing information on individual crops[4,5,6].

For growth environment monitoring, multiple sensor nodes to measure temperature, humidity and luminance are installed in horticulture facilities by kind and sensing information is sent to the management server and the base station connected by wireless LAN.

Intel Research Berkeley Lab developed a system that automatically controls temperatures, humidity and the amount of sunshine using sensors and established a monitoring system

*corresponding author : Eung-kon Kim

2011 Fifth FTRA International Conference on Multimedia and Ubiquitous Engineering

978-0-7695-4470-0/11 $26.00 © 2011 IEEE

DOI 10.1109/MUE.2011.44

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to measure growth environmental factors to produce good quality wine in a vineyard in Oregon, USA[7,8].

The remote sensor nodes in the vineyard collect environmental data such as temperature, humidity and luminance and sense activities occurring in the vineyard. Collected data are recorded in the sensor node installed in the shovel of farm workers and if the shovel is placed in the barn, the data recorded in the shovel will be loaded onto the central database. Through the measured data, the highest and lowest temperatures by hour are calculated and soil moisture is measured to supply water.

Phytech Co. in Israel developed sensors and software to monitor plant growth information and cultivation environments and applied them to farms for roses, grapes, tomatoes and black pepper. The information collected by the sensors was used in improving cultivation methods such as watering periods and amounts and forecasting yields and it enabled automatic water supply and temperature adjustments in greenhouses. The sensors applied to tomato farms are composed of electronic water measuring devices, growth measuring sensors, stem change sensing sensors, leaf temperature sensors, environment sensors and soil moisture measuring sensors.

In addition, Hibri Agricultural University in Israel developed an automatic control system to measure the thickness of leaves and supply water in amounts necessary at right times (Smart Irrigation Control System) based on the idea that the thickness of plant leaves would determine the amount of water necessary.

As many studies using sensors have been conducted as such, sensors and robots (unmanned helicopters and rice-planting robots) for agriculture are being developed and diverse applications using them are being developed.

B. Greenhouse environment management system

The greenhouse environment management system makes DB with sensing information transmitted from terminal proxy servers by farm through various kinds of sensing information collected from the inside/outside of greenhouses. Through information analysis, it provides various kinds of statistical and forecasted information, transforms collected sensing data to be understandable by users using comparison and analysis tools by farm to provide processed information on real time environmental factors to producers and related consultants.

The composite environment control system for greenhouses enables composite operations of devices considering mutual relationships between individual environmental conditions and through controllers, it makes operating devices move to have greenhouse environments meet control criteria by setting control criteria and measuring the greenhouse environment the most suitable to crop cultivation through sensors. If these processes are repeated, greenhouse environments can be maintained optimally. However, to maintain various environment conditions at optimum states, judgments should be made compositely and operating devices should be operated compositely. The greenhouse environment control method can divide 24hours a day into up to 6 cycles to independently enter

set values for operating devices such as ventilation, room heating and ceiling devices by cycle and the starting time of each cycle can be set up by astronomical time (sunrise, sunset) or fixed time. In addition, indoor temperature/humidity setting conditions may be optimized based on external meteorological environments (sunshine, wind direction, wind velocity, outside temperatures, rainfall, humidity). Various greenhouse operating devices connected to electric panels are controlled in real time in linkage with control programs loaded on the controller based on collected sensor values, control values are stored and CO2 concentrations in greenhouses are measured and controlled.

III. GREENHOUSE ENVIRONMENT MONITORING SYSTEM DESIGN AND IMPLEMENTATION

A. greenhouse environment monitoring system design The greenhouse management system collects diverse sensor

information received from various kinds of sensors, integrate the data and store it in the greenhouse database. It makes greenhouse information into databases to support the formation of optimum growth environments for crops being cultivated through monitoring and control services and supports greenhouse monitoring and control services. Figure 1 is a configuration diagram of the greenhouse environment monitoring system.

To collect plant growth environment information, this system installs a weather sensor group consisting of temperature sensors, humidity sensors and external sunshine sensors plus CO2 sensors, nutrient solution measuring sensors(EC, pH, supplied amounts of solution, discharged amounts of solution) in greenhouses with wires and manages individual nodes in the form of mesh topology through USN middleware software. To wirelessly collect data transmitted from leaf temperatures, fruit temperatures and stem temperatures in greenhouses, USN networks were installed and gateways were installed at the ends of greenhouses.

The control system establishes DB in the UI server and transmits it to the server and stores so that the operating time and the numbers of control of ventilation and room heating systems for controlling plant cultivating greenhouse environments, insulation systems for saving energy, light blocking curtain control systems based on external intensities of light, flow fan systems that control air flows in facilities, hot water/room heating water temperature control systems and all motors installed in production greenhouses.

The data analysis method can store growth environment monitoring and control related data and manage plant growth environment and biometric information, the growth information monitored by producers and quantity DB. In addition, it was implemented with linear regression analysis and DIF analysis to produce statistical and forecasting information through data analysis so that users can extract/compare/analyze desired items by incorporating SQL into stored DB.

The environment control system for greenhouses can operate devices compositely considering correlations between individual environmental conditions. Based on experiences, knowledge which is the results of studies is made into

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information to set up control criteria and the greenhouse environments the most suitable to crop cultivation are measured through sensors in order to operate operating devices through controllers so that greenhouse environments meet the control criteria. If these processes are repeated, greenhouse environments can be maintained optimally. However, to maintain various environment conditions at optimum states, judgments should be made compositely and operating devices should be operated compositely. The greenhouse environment control method can divide 24hours a day into up to 6 cycles to independently enter set values for operating devices such as ventilation, room heating and ceiling devices by cycle and the starting time of each cycle can be set up by astronomical time (sunrise, sunset) or fixed time. In addition, indoor temperature/humidity setting conditions may be optimized based on external meteorological environments (sunshine, wind direction, wind velocity, outside temperatures, rainfall, humidity). Various greenhouse operating devices connected to electric panels are controlled in real time in linkage with control programs loaded on the controller based on collected sensor values, control values are stored and CO2 concentrations in greenhouses are measured and controlled.

Figure 1. Greenhouse environment monitoring system configuration diagram

B. Implementation of the greenhouse environment monitoring system The greenhouse environment monitoring system proposed

in this paper enables users to monitor and remote-control greenhouse environments using the Web so that the situations of subject greenhouses can be remotely monitored. By setting greenhouse environment control values and then automatically controlling greenhouse environments, diverse facility farm information can be obtained and utilized without going through separate information analysis processes utilizing remote monitoring systems without visiting farms. Using these monitoring systems, individual users can conveniently identify various sensing & measuring information through Internet. Figure 2 shows greenhouse environment management information histories.

Figure 2. Greenhouse environment management information

IV. CONCLUSION AND FUTURE WORKS

The web based greenhouse environment remote monitoring system proposed in this paper enables users to monitor and remote control greenhouse environments using the Web so that the situations of subject greenhouses can be remotely monitored. The greenhouse environment monitoring system enables individual users to remotely see greenhouse environment information in real time without firsthand visiting farms and since using this monitoring system, individual users are enabled to conveniently identify various sensing and measuring information through Internet, clear cost saving effects can be obtained through saving labour. Using the green greenhouse monitoring system prevented natural disasters in advance and thus the efficiency of agricultural product cultivation has been improved.

As future tasks, development for upgrading and advancing agricultural technologies will be necessary to have global competitiveness and for our agriculture to survive in the environment where more and more agricultural products are being allowed for import with the execution of FTA.

ACKNOWLEDGMENT

The paper is a result of a study conducted as part of the Local Innovative Human Resources Cultivation Project by the Ministry of Education, Science and Technology and the Korea Industrial Technology Foundation.

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REFERENCES

[1] H. J. Kang, M. H. Lee, H. Yoe, “Designof efficient routing method for USN basedLarge-scale Glass Greenhouses,” Software Engineering Research, Management & Applications, 2007. SERA 2007. 5th ACIS International, pp. 523-528, Aug, 2007.

[2] J. Burrell, T. Brooke, R. Beckwith, " Vineyard Computing: Sensor Networks in Agricultural Production," Pervasive Computing, IEEE, Vol.3, Issue 1, pp.38-45, jan, 2004.

[3] http://model.job.affrc.go.jp/FieldServer/

[4] F. Ian,. Akyildiz et al., “A survey on Sensor Networks,”IEEE Communications Magazine, Vol. 40,No. 8, Aug. 2002.

[5] M.H. Lee, K.B. Eom, H. J. Kang, C.S. Shin, and H. Yoe, “Design and Implementation of Wireless Sensor Network for Ubiquitous Glass Houses,” Computer and Information Science, 2008. ICIS 08. Seventh IEEE/ACIS International Conference, pp.397-400, May. 2008

[6] C. S. Shin, Y. W. Lee, M. H.Lee, J. W. Park, and H. Yoe, “Design of Ubiquitous Glass Green Houses,” ISORC 2009.

[7] http://www.phytech.com [8] http://berkeley.intel-research.net

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04402800.pdf

Greenhouse Asset Management Using Wireless Sensor-Actor Networks V. Lakshmi Narasimhan1, Alex A. Arvind2, and Ken Bever3

Department of Computer Science, 1University of Western Kentucky, Bowling Green, KY 42101, USA 2University of Northern British Columbia, Prince George, BC, Canada, 3Chief Technical Officer,

MIMOSA, Emails: [email protected], [email protected] Abstract: Greenhouse plays an increasingly important role in modern horticulture in order to meet the needs of the world’s growing and demand driven economy. The primary issue of greenhouse based horticulture is to manage the greenhouse environment optimally in order to comply with the economic and environmental requirements. This paper discusses the advantages of using asset management strategy along wireless sensor-actor network technology for such cost-effective and environmental friendly greenhouse management. Keywords: Greenhouse management, asset management, sensor-actor networks. 1. INTRODUCTION An agricultural greenhouse can be considered as a man-made system to emulate a suitable ecosystem in order to grow crops. Initially, greenhouse technology was driven mainly by the desire of the rich people for out-of-season fruits and flowers [18]. Later, due to widespread industrialization, commercial horticulture began to develop all over the world starting with Europe and the United States [18]. In modern horticulture, greenhouses play an increasingly important role to meet the demand-driven economy. The primary issue of greenhouse based horticulture is to manage the greenhouse environment optimally in order to comply with the economic and environmental requirements [17]. Although technological advancements offer innovative solutions for specific issues, achieving optimal management of overall greenhouse is generally difficult. The latter involves making complex decisions on investments, crop production processes and controlling the dynamically changing environmental conditions. Better decisions can often be made based on sufficient knowledge and insight of the system of study [2]. A greenhouse asset management system can provide knowledge and insight required to operate the greenhouse in an optimal level. Efficient control of the greenhouse environment requires a control system which is adaptive, accurate, and cost effective. Such a control system can be built using wireless sensor-actor network technology [19], which offers local processing and storage

capabilities, wireless communication, and comes in highly portable sizes. Greenhouse management often involves continuous monitoring and activation of different units, such as heating, cooling, lighting, water/soil gradient, etc., in order to maintain suitable climate for the plants. These activities sometimes require human presence in the greenhouse in order to observe the condition and activate appropriate units that may be undesirable for many reasons. With the advancement of computing and wireless sensor- actuator systems, it is quite possible to perform such tasks anywhere, any time [7]. This paper discusses the advantages of using asset management strategy and architecture along wireless sensor-actor network technology for effective greenhouse management. Particularly, the paper illustrates the benefits of deploying a sensor- actor network along with an integrated asset management system in a greenhouse environment. We illustrate 1) how a sensor network can facilitate greenhouse management, 2) how it can be integrated with the Internet for remote monitoring and operation, 3) how it can be enhanced with a database and software tools to exploit the collected data for effective management of greenhouse and 4) how capacity building (financial management, scalability, etc) in greenhouse environment can be effected. The rest of the paper is organized as follows: section 2 provides an overview of a typical greenhouse and their operational requirements. A brief description of the common conceptual object model is provided in section 3, followed by the development of a CCOM model for greenhouse sensor network in section 4. A typical Greenhouse sensor network information management architecture is described in section 5, followed by a case study in section 6. The conclusion summarizes the paper and offers pointers for further work in this area. 2. OVERVIEW OF THE GREENHOUSE ASSET ENVIRONMENT The main objective of an agricultural greenhouse is to have maximum productivity with minimum use of energy and other resources in order to be economical and environmentally friendly.

International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies

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International Conference on Mobile Ubiquitous Computing, Systems, Services and Technologies

0-7695-2993-3/07 $25.00 © 2007 IEEE DOI 10.1109/UBICOMM.2007.43

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From the cost perspective, greenhouse management involves primarily three types of costs: (i) initial infrastructure cost (setup cost) and (ii) material cost during crop cultivation (seed, water, fertilization, etc.), and (iii) climate and pest control cost. The later two costs can be collectively referred to as the operating cost and most of the present day investments are planned based on the operating cost [20]. Setup cost is one-time or long-term investment, whose value has direct effect on the operating cost. Material costs are generally fixed and low compared to the total cost. For example, in most cases, the cost of fertilization in greenhouse is between 1 to 2% of the gross value of product compared 10 to 20% for field crops [18]. Thus the major part of the operating cost goes to climate and pest control. Both setup cost and operating cost involves human cost and modern trend is to reduce the human cost by the way of computerized automation [20]. The objective of climate control is to protect the crops from external climate that is harmful to the crops and to provide the climate that is favorable for the growth of crops. Pest control system protects the crops from pests (insects, mites, diseases, weeds, and vertebrates) [24]. Since the artificial environment created by the greenhouse often favors the rapid development of pests and weeds [18], climate control and pest control need to be integrated suitably in order to achieve optimal control of both. Greenhouse asset includes the following: Humans who work on the greenhouse Greenhouse land and building Input materials such as seeds, fertilizers, water,

pesticides, biocontrol agents (predatory mites, pirate bugs, soil-dwelling mites, and parasitic insects), etc.

Control systems such as climate control and pest control

o Hardware – sensors, actors, connectors, interface boards, input and display panels, routers, computers, generators, transformers, etc.

o Software – communication, data filter and fusion, etc.

Crops that grow inside the greenhouse Output products such as, flowers, fruits,

vegetables, etc., and Data and information management system.

3. GREENHOUSE CONTROL SYSTEMS

Any control system has two main set of components, namely, a sensor or monitoring component to collect data and an actuator component to perform specific actions as a response to the collected data (or to execute a predetermined strategy). To understand the sensors and actuator components used for greenhouse climate control system, we briefly review the ecosystem requirement for plant growth. Photosynthesis is the most important factor in plant growth and it requires light, water, and carbon dioxide [18]. So, high transmission of light in the waveband from 400nm to 700nm is essential to maximize the photosynthesis rate. The amount of such radiation entering the greenhouse depends on the shape, structure, and material of the house and, the amount of absorption depends on the distribution and orientation of the leaves of the plants. Apart from natural daylight, artificial light is increasingly used to supplement or substitute prolonged daylights in greenhouses. So, lighting system is an important component in greenhouse climate control. Supplies in terms of water, fertilizer and any other nutrients have also been considered as parts of the greenhouse climate control system. Fertilizers typically provide, in varying proportions, plant nutrients such as nitrogen, phosphorus, and potassium, calcium, sulfur, magnesium, etc. Maintaining suitable temperature is another important factor in plant growth. Many factors could influence the temperature inside a greenhouse, such as, exterior temperature, sunlight, wind speed and its direction, etc. In order to maintain the required temperature, both heating and cooling systems are required. Cooling system may be employed through ventilation or, fan, and heating system may be implemented in terms of roof heating, fan heating, metal, pipe, water, steam, or air heating, decomposition of manure and compost, etc. Thus, cooling system and heating system are essential components of a climate control system. Water and temperature will cause change humidity within a greenhouse and it is necessary to maintain suitable relative humidity, which measures the amount of water vapor a gas is currently being held in comparison with the amount it can hold at a given temperature. The third component involved in photosynthesis is CO2 and it can be obtained by decomposition of organic matter, natural gas, propane, kerosene, respiration of human being, or pure CO2 from

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chemical industries. Since the late 60s, most greenhouse growers use either liquid compressed CO2 or CO2 produced by burning of liquid fuel or gas [18]; hence, carbon dioxide generator is another component in the climate control system. The pest control system also has sensors to monitor the crops for pest identification and eradication. Once a pest is identified, the pest control system is activated to deal with it. Many techniques are being used for pest control, which include, sanitation, screening, biological control, and chemical control [24]. Biological control techniques use living organisms to reduce the incidence of pest organisms. Chemical control techniques use chemicals to kill or disrupt their normal development. Summarizing, a typical greenhouse climate control system has the following subsystems: Lighting system, Cooling system, Heating system, Carbon dioxide generation system, Watering system and Fertilization system. These systems will be activated based mainly on the temperature, relative humidity, light, wind speed and direction, and water level inside the greenhouse. The devices used to measure these quantities are referred as sensors. Given that greenhouses are considerably large in size and that a federation of greenhouses are possible, a network of sensors are therefore essential to monitor and govern a greenhouse management system. 4. SENSOR-ACTOR NETWORK BASED GREENHOUSE CONTROL SYSTEMS Wireless sensor-actor or sensor-actuator network is a collection of sensor and actor nodes linked by a wireless medium to perform distributed sensing and acting tasks [19]. The sensor nodes collect typical information about the physical world (e.g., humidity and temperature) and communicate over a network environment to a computer system, which is called, a base station. Based on the information collected, the base station takes the decisions (in some cases the actors themselves take decisions) and then the actors perform appropriate actions upon the environment. This action allows users to sense and control the environment from anywhere, at any time. Further, the networked sensor information typically provides a better overall perspective of the environment than a single sensor- based source of information. With the advent of wireless technology, such sensors and actors can be connected over a wireless network system (e.g., Bluetooth, WiFiWide).

Wireless sensor-actor network has many advantageous over conventional control systems, which include the following: One of the major limitations of the current

automation system for greenhouse management is the amount of wiring involved in connecting sensors to actuating systems (actors) [21]. Wireless sensor-actor network technology eliminates this problem.

Many existing control systems for greenhouse maintain the environment at known set-points. Wireless sensor-actor based control system for greenhouse is amenable to have more flexible and adaptive control over the environment due to its communication, computing, controlling, and storage capabilities.

As the connection between effective maintenance management techniques and significant improvements in efficiency and profitability becomes evident, system health monitoring and prognostics are getting increased attention in modern enterprises [22]. Effective system health monitoring and prognostics requires critical data of the system environment. A suitably designed wireless sensor-actor network can collect and provide such data in a timely manner.

Since wireless sensor-actor systems are designed to accommodate addition and deletion of nodes with minimal effort, changing the system in accordance with the changes in demand is relatively easy to implement compared to conventional systems.

By allowing flexible coordination, wireless sensor-actor based control systems offer system-wide scalability at low cost.

The above advantages favor the use of wireless sensor-actor based system design for greenhouse control systems. A typical greenhouse contains several sensors for measuring humidity, temperature, pressure, carbon dioxide, light, motion, etc., and contains several actors, such as, air conditioners, floodlights, sprinkler and water management facility, plant decks, air blowers, fans, CO2 production units, etc. As shown in figure 1, these sensors and actors can communicate among themselves and to the base station, through wireless media. The base station is then connected to the Internet so that it can be accessed from anywhere, at any time. A test bed for monitoring the sensor readings from a remote location for conducting experiments on the growth

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rate of tobacco plants have been reported in [23]. If the base station is located farther away from the greenhouse, then small systems such as, Stargate nodes along with RFID tags [12] can be used as routers to communicate to the base station. The base station usually maintains the database and can also act as a web server so that the data can be entered and/or visualized from remote locations using handheld devices. A typical architecture of a wireless sensor-actor network based greenhouse climate control is shown in Figure 1. The placement of the sensor and actor nodes plays a crucial role in the design of the network. For example, different sensors in a given greenhouse can report different temperature at any time depending on their locations and, consequently, the location and number of sensor and actor nodes are to be determined by this requirement. The numbers and locations can influence the quality of sensor readings. Although there are techniques available to extract the true values from the observed values, the task of data collection and management becomes challenging when the participating nodes (either sensor or actuator) start to deviate from normal operation. As a consequence, an unusual sensor reading could trigger a system-wide diagnostic process, which can typically use historical data in order to identify the system status. A typical sensor- actor based control system operation is shown in Figure 2. The collection of sensor data, called sensor scheduling, involves such issues as time to collect data, duration of collection, and their accuracy, all of which depend on operational and economic requirements. 5. GREENHOUSE ASSET MANAGEMENT SYSTEM Asset management encompasses a set of processes, tools, performance measures, and related decision support system in order to establish an optimum way of manage assets and achieve the desired sustainable outcome [25]. In other words, asset management concerns the seeking of the best return on investment. This process calls for the maintenance of a detailed registry for all equipments as a common repository (called, the global asset registry) and historical information including operation, repair, and compliance records on the various assets. These information sets are typically held over an information management environment (typically over distributed databases or data warehouses) and they need to be integrated with suitable asset health monitoring, quality

control and risk management systems, before they are embedded into a suitable decision support system. 5.1 A Brief Description of CCOM for Sensor Network Modeling The objective of the Common Conceptual Object Model (CCOM) is to provide a formal representation of a system of interest in order to understand and communicate with it. It is a high level model, which is impendent of the implementation technology and associated constraints and therefore it must use notations that are widely known. Unified Modeling Language (UML) [10, 26] is a popular modeling environment, which is heavily used in software engineering and CCOM is a derivative that is tailored towards asset modeling problems. Briefly, CCOM provides a clean means to describe various entities in an enterprise and their inter-relationships. 5.2 A CCOM Model for Greenhouse Sensor Network Figure 3 describes the CCOM model for a greenhouse sensor network, wherein the term Enterprise is the representation for the Greenhouse as an ensemble entity, while Table 1 describes the various entities in a greenhouse. Figure 4 captures the characteristics of each component and the relationships between them.

Item Description Enterprise Describes the greenhouse as an

ensemble entity GHSite Describes each greenhouse site and

its characteristics GHSiteType Describes a greenhouse site types Asset Describes assets AssetType Describes asset functionalities Sensor Describes sensors SensorType Describes sensor types and their

characteristics SensorLocation Describes sensor location Actor Describes actors ActorType Describes actor types and their

characteristics ActorLocation Describes actor location AssetModel Describes asset models and their

characteristics Asset Manufacturer

Describes asset manufacturers

AssetAgent Describes asset agent (for maintenance at a given GHSite)

GHSiteDB Describes greenhouse database at a given GHSite

Table 1: Description of Entities in a Greenhouse

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6. ARCHITECTURE FOR GREENHOUSE INFORMATION MANAGEMENT The sensor network information management architecture is presented in Figure 4, where the Input Section manages data acquisition (including cleaning and formatting of sensor data) and sensor network management (including wireless connectivity management). The Asset Registry contains three modules, namely, a Data warehouse to store cleaned sensor data, a Catalog Service to access data sets and a Data Management service to facilitate federated data warehousing and federated catalog maintenance and management. The architecture is designed to conform with the principles of the Model Driven Architecture [4] and, in addition, in conformance with modern Standards on Open System Architecture (for Condition based Maintenance) [9, 14]. The Information Exploitation Section has several modules containing a number of tools to support decision making [6], report generation, financial status generation and visualization (see [3, 5, 11] for the kinds of information that could generated). The Output Section facilitates query management, query optimization and MIMOSA/ISO complaint data exporting facilities. The Data Acquisition performs Sensor-actor network management, Sensor output, Wireless connectivity & Feature extraction. The Data Storage performs Distributed storage, Metadata management, Classification of data sets using MIMOSA/ISO compliant schemas. The Exploitation Section performs Report generation (Asset registry view), Annotation service (Asset quality view) and Interaction view generation. The Tools and Techniques performs Horticulture data analysis tools, Decision support systems (what-if questions are analyzed here) and Asset financial status generator. The Catalog Service provides (federated) catalog and Metadata repository 7. CONCLUSIONS This paper describes a wireless sensor network environment for managing agricultural greenhouses. A CCOM model of the greenhouse system has been developed. In addition, a four-layer information management architecture containing modules that collects and cleans data, an integrated asset registry,

tools & technologies for information exploitation and output management to handle customers has been detailed in this paper. We are currently working on following up on the MIMOSA Standards [8, 13, 15, 16] and ISO Standards [1] and enhancing them to suit greenhouse information management. The issues to be addressed include, conditional monitoring and facilitation for diagnostics and prognostics of various asset types inside the greenhouse, including plants, machinery and others. We intend to develop operational IT systems, in addition to developing international Standards in these areas. 8. REFERENCES 1. ISO 13374-1:2003, Condition monitoring and

diagnostics of machines – Data processing, communication and presentation – Part 1: General guidelines.

2. Using Mineset for Knowledge Discovery Barry G. Becker IEEE Computer Graphics and Applications, July/August 1997

3. Updates and view maintenance in soft real-time database systems. Ben Kao, K. Y. Lam, Brad Adelberg, Reynold Cheng, Tony Lee. Proceedings of the eighth international conference on Information and knowledge management.

4. Model-Driven Architecture: Vision, Standards and Emerging Technologies. John D. Poole. ECOOP 2001.

5. Benyahia I, Potvin, J-Y. (1998) Decision support for vehicle dispatching using genetic programming. IEEE Transactions on Systems, Man and Cybernetics, Part A. 28(3), 306-314.

6. Guo B, (2003) Knowledge representation and uncertainty management: applying Bayesian belief networks to a safety assessment expert system. Proceedings of the 2003 International Conference on Natural Language Processing and Knowledge Engineering. pp 114-119.

7. Dreyfus L P, Ahire S L, Ebrahimpour M. (2004) The impact of just-in-time implementation and ISO 9000 certification on total quality management. IEEE Transactions on Engineering Management. (51)2, 125-141.

8. Machinery Information Management Open System Alliance, http://www.mimosa.org

9. Open System Architecture for Enterprise Application Integration (OSA-EAI) Version 3.0d, http://www.mimosa.org

10. OSA-EAI Common Conceptual Object Model (CCOM) V3.0 http://www.mimosa.org

11-26 Please get these from the authors

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Figure 2: Operation of a Sensor-Actor Network

Receive Data from Sensors

Analyze it (with old Data)

Decide Actions

Send Commands to Actors

Internet Base Station Remote

User Greenhouse Sensor

Actor

Figure 1. A Wireless Sensor-actor Network Based Control System

Asset Registry

Information Exploitation Section

Input Section

Sensor Network

Data Acquisition

Catalog Service

Data Storage (Data Warehouse)

Output Section

Query optimization and Management

Standards (MIMOSA/ISO) Compliant Data Exporter

Visualization Environment

Decision Support Systems

Tools and Techniques

Report Generation

Data Management

Actors

Fig.4: Greenhouse Information Management Architecture

Enterprise EntId UserId

GHSiteType TerrainId GeoId Mobile +/-

GHSite

Asset AssetId

GHType SiteId

AssetType FunctionId

Sensor SensorId SensorAge

SensorType FunctionId Metric

SensorLocation Location (x,y,z) NearestactorRelativity NearestSensorRelativity

AssetModel GHSiteDB entId userId

AssetManufacturer ManId

AssetAgent

Actor ActuatorId ActuatorAge

ActorType FunctionId Metric

ActorLocation Location (x,y,z) NearestSensorRelativity NearestActorRelativity

*

1

*

*

* 1

* *

Figure 3: CCOM model for a green house sensor network

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05674751.pdf

Paprika Greenhouse Management System for Ubiquitous Agriculture

Jeong-hwan Hwang Dept. of Information and Communication Engineering

Sunchon National University Suncheon, Republic of Korea

[email protected]

Hyun Yoe*

Dept. of Information and Communication Engineering Sunchon National University Suncheon, Republic of Korea

[email protected]

Abstract—This paper proposes the ‘Paprika greenhouse management system’ based on wireless sensor network technology, which will establish the ubiquitous agricultural environment and improve the productivity of farmers. The proposed ‘Paprika greenhouse management system’ has WSN environmental sensors and CCTVs at inside/outside of paprika greenhouse. These devices collect the growth-environment related information of paprika. The system collects and monitors the environmental information and video information of paprika greenhouse. In addition to the remote-control and monitoring of the greenhouse facilities, this system realizes the most optimum paprika growth environment based on the growth environmental data accumulated for a long time.

Keywords-wireless sensor networks; ubiquitous agriculture; greenhouse; paprika)

I. INTRODUCTION

The ubiquitous agriculture has its purpose on enhancing the productivity by combining IT technology with agriculture, examining the safety of agricultural crops by systematically managing the distribution/consumption of crops and making the process of distribution/consumption transparent[1].

Wireless Sensor Networks (WSN) technology can realize advancement of productivity, safety and the level of human living by applying it to various industries[2][3]. In particular, it is labor-intensive industry compared to other industry, and when applying WSN technology to agricultural area which lacks IT technology application, added value and productivity of agriculture can be increased[1][4].

This paper proposes ‘paprika greenhouse management system’ based on wireless sensor network, which is an integrated management system applying the WSN technology to the paprika growth environment management and control. The proposed system improves productivity by maintaining optimized environment for growth and development through information on environment for paprika greenhouses and growth and development of the crop, and it not only reduces production cost by optimizing management of production components but also provides convenience to producers through wire-wireless remote automatic control of environment for growth and development of paprika.

This research paper is comprised of followings. Chapter 2 will explain the ‘paprika greenhouse management system’ based on wireless sensor network. Finally, Chapter 3 will give conclusion to close the research paper.

II. PAPRIKA GREENHOUSE MANAGEMENT SYSTEM

A. System structure The proposed ‘Paprika greenhouse management system’ is

comprised of physical layer, middle layer and application layer. The physical layer is comprised of sensors, CCTV and greenhouse facilities as in Figure 1. The middle layer supports the communication between physical layer and application layer. It makes the greenhouse information into database and provides with monitoring and control service, maintaining the growth environment of paprika at optimum status. The application layer is comprised of interfaces which support the greenhouse environment monitoring and greenhouse facility control service.

Figure 1. Paprika Greenhouse Management System Structure

B. Implementation In order to collect the environmental information of paprika

greenhouse, WSN sensors for soil, environment, and temperature and humidity of leaves were installed at inside/outside of greenhouse as shown in Figure 2. These sensors will form the wireless network together with WSN sensor gateway in the greenhouse. In addition, in order to maintain optimized environment for growth and development of crops, electric lights, fan heaters, ventilators, devices for overhead flooding, and ceilings, environment control facilities are installed in greenhouses as shown in Figure 3.

* Corresponding Author

978-1-4244-9807-9/10/$26.00 ©2010 IEEE ICTC 2010555

Figure 2. Environment Sensor and Soil Sensor

Figure 3. PLC Controller and Greenhouse Facilities

In order to system control and monitoring, Web GUI of paprika greenhouse management system for growth and development of paprika is realized as seen in the following Figure 4.

Figure 4. WEB GUI

Web GUI realized for tests. The values which were measured by the soil and weather sensors in greenhouses are illustrated in (a) and from (b), we can control the facility devices of greenhouses and check conditions. As the values of sensing which is previously mentioned, paprika greenhouse management server sends questions to paprika greenhouse database. When the value of conditions of equipment devices is 1, it appears to be On, and when it is, Off. (c) is the part to control CCTV, (d) the part to show the images collected through CCTV, and (e) the part to enter the standard value for automatic control of greenhouses.

C. Results As a result of applying the proposed system as mentioned

above to actual paprika greenhouses, information of environment and images in greenhouses is collected through sensors and image supervision camera, and GUI which is intuitive to users can monitor and control conditions of greenhouses. The following Figure 5 is a graph that shows data of environment to growth and development measured by installing the proposed paprika greenhouse management system to paprika greenhouse.

Figure 5. Paprika Greenhouse Environment Data Graph

III. CONCLUSIONS

This paper proposed ‘paprika greenhouse management system’ based on wireless sensor network as the system to manage the greenhouse environment in integrated way in the ubiquitous agricultural environment. To prove the proposed system, it was tested in paprika greenhouse by installing sensors including sensors for soils, environment, temperature and humidity of leaves and CCTV and was implemented. As a result of the implementation, monitoring and controlling of the environment for growth and development could be conducted through GUI and the results of sensors monitoring related to controlling greenhouses and controlling shows that there is no wrong operation. In addition, in monitoring rooting zone environment and information of bodies, there is need of consistent researches and supplementation in the method of system and sensor monitoring.

ACKNOWLEDGMENT

This research was supported by the MKE(The Ministry of Knowledge Economy), Korea, under the ITRC(Information Technology Research Center) support program supervised by the NIPA(National IT Industry Promotion Agency) (NIPA- 2010-(C1090-1021-0009)).

REFERENCES

[1] Yun-sik Shin, “A Study on Informatization Model for Agriculture in Ubiquitous Era”, MKE Research Report, 2006

[2] Cheol-Sig Pyo, Jong-suk Chea, “Next-generation RFID / USN technology development prospects”, Korea Information and Communication Society, Information and communication, p7-p13, 2007

[3] Chee-Yee Chong, Kumar, S.P. Booz Allen Hamilton, “Sensor networks: evolution, opportunities, and challenges”, Proc. IEEE, Vol.91 No.8, pp. 1247-1256, 2003

[4] Meong-hun Lee, Chang-sun Shin, Yong-yoon Jo, Hyun Yoe, “Implementation of Green House Integrated Management System in Ubiquitous Agricultural Environments”, Journal of KIISE, Vol.27 No. 6, pp. 21-26, 2009

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