of a set of interactive web-based tools in three advisory decision-making systems. (ADS) These ADS .... technician during his IP monitoring visits. It offers tools for ...
An Intelligent System for Therapy Control in a Distributed Organization José Joaquín Cañadas, Isabel María del Aguila, Alfonso Bosch, and Samuel Túnez Department of Languages and Computation. Universidad de Almería. 04120. Almería, España. E-mail: {jjcanada, imaguila, abosch, stunez}@ual.es Teléfono:++34950015988 Fax:++34950015129
Abstract. This paper describes a decision-making system for phytosanitary control advicing. The solution adopted consists of developing a Web-accessible information system based on a multi-agent architecture, integrating knowledgebased techniques and classical information analysis and management techniques. CommonKADS was used for the design of some knowledge-based agents. Internet implementation and integration was done in a knowledge-based system implementation environment, with programs executed on the Web server.
1 Introduction This work belongs to a project1 developed over the last three years, the purpose of which is to apply the most recent innovations of information technologies and communications to the agriculture sector, in order to modernize it. Production factors need to be efficiently manipulated while minimizing any negative impact. This project consists of three subprojects coordinated by the Universities of Almería, Murcia and Granada. Three areas of interest have been defined, which correspond, respectively, to the spheres of action of each university and subproject: a) Optimization of the combined use of irrigation and fertilizers. b) Evaluation of the aptness of soils for cultivation using soil assessment techniques. c) Phytosanitary therapy control for crops produced according to the Integrated Production Quality Standard. The main objective of this project is the design, development and implementation of a set of interactive web-based tools in three advisory decision-making systems. (ADS) These ADS are responsible for advisory services within the scope of each subproject. Figure 1 shows a general view of the system proposed in the project. The agents responsible for specific tasks can be described using the following levels: 1) A tasks and processes level, where the agents that implement the different ADS tools are located. 2) An interface level that allows access by final users. 3) An information 1
“An Intelligent Decision Support System for the South-East Spanish Agricultural Environment” Reference: 1FD97-0255-C03-03 financed by the CICYT and the EC.
access level, holding the mechanisms of query and interaction for information sources located in the databases and in Geographic Information Systems. This paper focuses on the ADS developed at the University of Almería (highlighted elements in Figure 1). The developed agents cover the advisory requirements in the distributed organization necessary for monitoring the Integrated Production quality standard. These agents integrate knowledge-based techniques and classical information analysis and management techniques. WWW INTERFACE
General Interface Specific Interface
Specific Interface
Specific Interface
TASKS Agents Rules Extractor Advice Generator
Decisions Generator
Tuning Agents
Phytosanitary Strategy Selection Therapeutic Planning
Technician Support Report
Distributed Control Plans
Generation
INFORMATION
Inference Merge Data
Phytosanitary Information Management
G.I.S.
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Fig. 1. General architecture of the intelligent decision-making system.
Our group had previously developed the EXPLA knowledge-based system (KBS) [11], for chemical pest control advisory services, developed using Smart Elements as implementation environment. The implementation uses knowledge-based techniques, the object-oriented paradigm and database access. The combined use of these techniques allows complex applications in very different spheres to be approached, satisfying a set of requirements which are not always easily managed in conventional systems. The combination of knowledge-based techniques and databases provides a clear separation between the knowledge base and the facts recorded in a database,
facilitating maintenance and portability of the applications. The combination of knowledge-based techniques with the object-oriented paradigm, allows the principles of data abstraction and encapsulation to be used for structuring knowledge. The dynamic object-based design combined databases allows a high degree of independence from the domain, which favors its reusability. Nowadays there is much interest in incorporating KBS onto the Internet, and several different alternatives have been proposed for it. In [9], the KBS development and execution environment is JESS (Java Expert System Shell), an inference engine inspired by CLIPS, written in Java and which, therefore, can be combined with any Java program and executed on the Internet. In the work of [2] and [7], the potential offered by Internet and the Web and its associated technologies as an environment for development and implantation of expert systems is analysed. In our case, the solution adopted, with very satisfactory results, is based on the use of the Smart Elements environment already known to the group, together with the Web technology necessary to implement the KBS on the Internet. This paper is structured as follows: first the problem context is analysed, and the need for a distributed organization is stated; next, the agent architecture used in the system is described; and finally, the design of certain of the most important agents of the architecture proposed are dealt with at length, highlighting the communication established among them and integration in the Internet of the knowledge-based agents.
2 Integrated Production Quality Standard In this section we briefly describe the organization of Integrated Production (IP), the basic reason why a distributed agent architecture becomes necessary. IP is understood as an agricultural production system that uses natural production resources and mechanisms to the maximum. Biological and chemical methods are carefully selected taking into account the requirements of society, profitability and environmental protection. To maintain these agricultural production techniques, a mark of quality called Integrated Production has been created that is carried out according to the Spanish office of patents and trademarks. IP includes extensive regulating standards, as well as monitoring and inspection by the corresponding authorities. Figure 2 shows the IP use case diagram, in which three wide interaction scenarios stand out: grow, market and inspect, along with the growers and technicians involved in the process. When a group of growers (IPG) decides to adopt the IP quality standard, it must submit to discipline in growing implying intervention by technicians, marketing controls and periodical reviews by the certifying companies to see that the standard is being complied with.
INTEGRATED PRODUCTION Grower
MARKET Stockholder
GROW EXTEND SAMPLING
VISIT CROP Agricultural technicians from IPG
EXTEND EXTEND
USE APPLY CONTROL ACTIONS
EXTEND RECORD DATA OF VISIT INSPECT Agricultural technicians from local government agencies
Fig. 2. Integrated production quality marking
In general, the grow use case considers the crop as a complex system, made up on one hand by the field/greenhouse, the plants, the parasites (pests and diseases) and the auxiliary fauna (useful fauna). This system is affected by external variables (climate, humidity, market price of the fruit, …) and to maintain balance, control measures may be applied which are especially respectful of the crop, the useful fauna and the environment. Among interactions during growing, three tasks linked to integrated control of parasites affecting the crop appear. This control is carried out in weekly visits by the agricultural technician, in which he decides what action to take on the crop. The technician must take a sample of the state of the crop, understanding this as the system made up by the plants, the pests and the auxiliary fauna and other factors that enable him to estimate the risk induced by the different harmful agents, and when there is imbalance, advise treatment. The information tools developed in this work assist the agricultural technicians and the growers in all the monitoring and decision-making tasks indicated above, as shown in the following sections. In future work, the ADS will be extended to the rest of the use cases in the diagram, such as marketing and inspection.
3 Distributed Multi-Agent Architecture To assist in all the aspects of monitoring, advising and management related to phytosanitary control in the scope of the Integrated Production Quality Standard, an information system based on a multi-agent architecture is proposed. As indicated
above, some of the agents require knowledge-based techniques; therefore, we have used CommonKADS [8] for the entire KBS analysis and design process. One important result of the organizational analysis carried out was the confirmation that the experts clearly differentiate between two large tasks in the grower advisory process. In the first, a decision is made on whether it is necessary to use chemical control on a crop and, if so, the product to be applied is selected. This gave rise to two subsystems or agents that are dealt with separately: a) Decide whether it is necessary to take action on the crop and b) Decide what kind of action.
DB
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Phytosanitary Information Management
Technician Support
Phytosanitary Strategy Selection
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B Therapeutic Planning
API 1 API 2 API N
A Inspect
Fig. 3. Agent Architecture: A) centralized, B) peripherical
Figure 3 shows the ADS agent architecture. Along with the agents that implement the tasks above, there are other agents defined for the distributed organization and that are responsible for IP monitoring. Two agent categories are established: centralized and peripherical. The first are located on the servers of the Data, Knowledge and Software Engineering Research Laboratory at the University of Almería. They are available at http://saepi.ual.es/saepi/ and enable the study of several pests and diseases of the target crops (tomatoes and grapevines). The second are located in the servers and or work stations of each of the Grower Groups devoted to Integrated Production (IPG). The purpose of each of these agents is described briefly below: • Management of Phytosanitary Information: its purpose is to offer the phytosanitary information and tools necessary for agricultural technicians and growers to easily generate tailored reports on plant-care products appropriate to the condition of their crops. • Selection of Phytosanitary Strategy: the purpose is to provide a decision on whether or not it is necessary to take action on a crop and if so, propose a specific phytosanitary strategy. There are two ways of using the agent: the first is interactively on the Web by the technicians or growers (generally inexperienced beginners), for complete analysis of a problem to obtain a decision on the need for action on the crop and a complete report of the consultation. The second is by communication with the Agent for Agricultural Technician Support to validate a
•
•
•
•
decision made by the technician (usually experienced), that is, compare his own decision, based on data from samples collected during his visit to the crop, with the proposal offered the Phytosanitary Strategy Selection Agent, which strictly follows the IP protocol. Treatment Planning: if the Phytosanitary Strategy Selection Agent indicates need to take action on the crop, the type of treatment to be applied must be determined. This agent’s purpose is to build up a treatment plan by abductive assembly of therapeutic conjectures, where the best conjectures (phytosanitary products applicable to the problem) are selected, building up the treatment plan necessary to correct a problem. Agricultural Technician Support: its objective is to provide a working environment on the Web that facilitates all the tasks that must be performed by the agricultural technician during his IP monitoring visits. It offers tools for collecting the sampling information related to different pests and diseases that may affect the crop and records the type of action recommended by the technician in situ during his visit. One important feature of this agent is that it automatically checks that action, by communicating with the Phytosanitary Strategy Selection Agent. Report Generation: the purpose is to generate a series of results in the form of reports prescribed by the IP Quality Standard. These reports are necessary to control the greenhouses in so far as visits, types of action recommended, products applied, etc. They also enable periodical summaries to be produced and alarms to be sent out as phytosanitary warnings on possible risk of a certain pest or disease. Inspection: its purpose is to facilitate some of the IP Quality Standard certifying company tasks, checking on compliance with the standard and the assignment of the corresponding quality certifications.
The following sections deal in more depth with the design of the most important agents in the system: Phytosanitary Information Management, Phytosanitary Strategy Selection and Treatment Planning. 3.1 Phytosanitary Information Management Agent The management of phytosanitary information is approached as a traditional data management problem. This agent offers the phytosanitary information and the tools necessary for the agricultural technicians and growers to easily generate tailored reports on the most appropriate products for the condition of their crops in general, and on the products permitted under the IP Quality Standard. The phytosanitary information is stored on an extended relational database server with an interface for Web queries using dynamic forms. It enables generation of tailored reports, about which the reliability of the information given and its frequent updating by the Plant Health Services should be mentioned. Its design is shown in the diagram in Figure 4.
Legal Information Web Explorer
Update & Filter Front End
INTERNET
Web Explorer
Back End
Web Server
DBMS
DSS Bridge LAN/WAN Fig. 4. Management of Phytosanitary Information
3.2 Phytosanitary Strategy Selection Agent The Phytosanitary Strategy Selection and Therapy Planning agents described below were designed using knowledge-based techniques, forming a KBS devoted to advising growers and agricultural technicians on whether or not to take action on a crop and what type of action to be taken. Two operating modes have been developed for this KBS: one interactive and the other automatic in communication with the Agricultural Technician Support agent. The interactive operating mode employs Web forms to provide the KBS with the appropriate information on the growing status of the crop and the physiological condition of the pest or disease necessary to provide a decision. Expert knowledge and the IP standard are represented by sets of rules stored in knowledge bases. Depending on the problem to be studied, the system uses the knowledge bases that contain the knowledge related to that type of problem. Agricultural technicians usually solve the problem in a way analogous to the proposal implemented in TERAP_IA [1], establishing elemental problems (pest or disease present in a crop) and analyzing them to establish what they consider therapeutic objectives. The inference process analyzes the rules, prompting for the values that it needs to evaluate them and concludes with a decision on each of the therapeutic objectives. One result of the system evaluation was that this way of using it is best for growers and beginner agricultural technicians. However, experienced technicians do not usually use the interactive Web interface, but make their decision on action to be taken “in situ” during the visit to the crop, quickly and without consulting the helping decision-making system, based on their own skill and experience. Nevertheless, in reality, they often do not consider all of the many factors that Integrated Production establishes to recommend action. Therefore, communication has been established between the Technician Support agent and the Phytosanitary Strategy Selection agent to enable the information from the sample taken by the technician during his visit to
the crop to be automatically analyzed by this agent and offer a report on the action to be taken. This allows the experienced technician to validate and revise his own decision with the one he would have obtained if he had made an interactive query and whether he is systematically considering all the restrictions of the IP. DB Bridge Grower
Web Explorer
Server-side Program
Smart Elem. Library
Rule & Knowledge Base
Junior Technicians Technician Support Agent
DSS Server
Senior Technicians Fig. 5. Phytosanitary Strategy Selection
Figure 5 shows the functional diagram, which was implemented using the following components: 1) The Smart Elements implementation environment and its C function library. 2) Executable programs on the server for execution and integration on the Web. As indicated in Figure 5, these programs are executed on the Web server, processing the input data supplied by the grower or technician on HTML forms and calling up the Elements Environment library functions that enable loading the knowledge bases, suggesting the hypotheses, launching the inference process and showing the results. 3.3 Therapy Planning Agent The construction of the treatment plan is closely related to the phytosanitary information management system and is carried out by an agent of abductive assembly of therapy conjectures [11], which selects the best conjectures by multi-criteria aggregation techniques [4], building up a set of actions that represent the treatment of the overall problem. One key feature is the evaluation of phytosanitary products by the phytosanitary information management agent, in which criteria established by experts and the relative importance of such criteria are applied.
4 Conclusions and Future Work In this paper we have presented the development of an ADS for phytosanitary control in Integrated Production using a distributed architecture of software agents. This ADS is part of the results of the research project “An Intelligent Decision Support System for the South-East Spanish Agricultural Environment”, financed by the EC and by the Spanish Ministry of Science and Technology and jointly developed by the Universities of Murcia, Granada and Almería (Spain) over the past three years. In this project, a set of integrated Web tools are offered for advising and assisting growers and agricultural technicians in making decisions on phytosanitary control, fertirrigation and soil evaluation. We have described the most important features of the design and implementation of the ADS where some agents were implemented using classic information analysis and management techniques and others with knowledge-based techniques. CommonKADS was used for the analysis and design of the latter; organizational context analysis established what are the intensive knowledge tasks in the grower advisory process: the definition of therapeutic objectives and the generation of a treatment plan. The Web ADS offers all the phytosanitary information and has the tools necessary for agricultural technicians and growers to analyze several pests in grapevines in Murcia and tomatoes in Almería. One aspect of implementation to be highlighted is KBS integration in the Internet through use of the Smart Elements environment already known to the research group, along with the necessary Web technology. This solution is easily transferable to other application domains. In the future, it is planned to extend the distributed agent architecture to aspects of IP Quality Standard inspection and marketing of the fruit, which are not currently included in the ADS. And concerning the ADS development and usage environment, it is also planned to include management of Web users and monitor system queries made and the decisions obtained by it for each farm.
5 Acknowledgments This study was performed with financial support from the Spanish Ministry of Science and Technology (CICYT) and EC (project 1FD97-0255-C03-03). We also gratefully acknowledge the collaboration of the Provincial Delegation of the Ministry of Agriculture and Fishing of Almería.
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