Verification of a Prototype System to Recognize Agricultural Operations Automatically based on RFID

Transcription

1 Verification of a Prototype System to Recognize Agricultural Operations Automatically based on RFID Koji Sugahara 1,2, Teruaki Nanseki 2 and Tokihiro Fukatsu 1 1 National Agricultural Research Center, National Agriculture and Food Research Organization, Tsukuba, Japan, sugak@naro.affrc.go.jp 2 Faculty of Agriculture, Kyushu University, Fukuoka, Japan Abstract Efficiently recording data of agricultural operations has been required for process control, quality control, and labor management in agriculture. The purpose in this paper is to clarify the possibility and the problem on a method to recognize and record agricultural operations automatically based on RFID (Radio Frequency Identification) as an automatic identification technology. A prototype system to recognize agricultural operations using small RFID tags and wearable RFID reading devices was developed, and basic operational tests on the system were carried out in order to verify the effectiveness of this method. The wearable device put on by the worker reads the identification data (ID) of the RFID tags which are stuck to the various objects such as machinery, facilities, materials, plants, and fields, while at the agricultural operation. This device continuously sends the data of the object ID and the reading time to the database server via wireless LAN. This server recognizes each task in the agricultural operation by matching the task pattern as combinations of the specific objects to these time-series data which are recorded by reading the RFID tags. The prototype system applied two types of RFID tags: microwave type (2.45GHz) and electromagnetic type (13.56MHz). As a result of the operational tests on this system, it was possible to recognize the tasks from the time-series data which were recorded while at the simple operations. However, it was clarified that there were some problems to be solved for further development of a practical system, on RFID reading, data sending, and task detecting. Keywords: agricultural operations, automatic recognition, RFID, wearable device, task pattern Introduction It is important for farmers to record their agricultural operations, for farm management, production control, plant protection, and so on. Additionally if the data management is computerized, the data analysis for process control, quality control, and labor management is possible. However, inputting the data of various agricultural operations by PC is a troublesome task for farmers, especially the elderly. Therefore, efficient methods to record and input the data of agricultural operations have been required. Agricultural data-input systems using Internet cell-phones have been developed and put to practical use (for example, Sugahara and Omatsu, 2004, Yokoyama, 2005). Those systems are available even during field operations, but fully utilizing them is not easy for the persons who are not used to handling of cell-phones. 215

2 To be able to record the data of agricultural operations more easily, quickly, and efficiently, we devised a method to recognize and record agricultural operations automatically based on RFID (Radio Frequency Identification) as an innovative automatic identification technology (Nanseki, et al., 2003). The purpose of this study is to clarify the possibility and the problem on this method (Nanseki, et al., 2007). We developed a prototype system to recognize agricultural operations using small RFID tags and wearable RFID reading devices, and we carried out basic operational tests of this system in order to verify the effectiveness of the method. System Design In this study, we propose a system to recognize and record agricultural operations automatically, by automatic identification of the objects in the operation with RFID and detection of the tasks with pattern matching to task patterns. It is based on a method which was devised by Nanseki, et al. (2003) and patented in Japan (No ), as follows: 1) RFID tags containing unique identification data (ID) are attached to the objects, such as implements, machinery, facilities, materials, plants, fields, and so on, which the worker uses and touches in the process of the agricultural operation. 2) Task patterns are defined as combination or sequence of the specific objects which the worker touches, in order to detect each task in the agricultural operation. The task patterns are determined beforehand. 3) The worker puts on a wearable RFID reading device (reader). When the individual object is touched while at the agricultural operation, the reader reads the RFID tag on the object and records its ID and reading time. 4) The item of the task can be distinguished by matching the records of the objects which the worker touches to the task patterns. This system might be able to cover various operations, not only in agriculture. Table 1 shows the concrete examples of operations and applications which can be covered by the system. Table 1. Possible agricultural operations and applications covered by the system. Operation Object items (with RFID tags) Application Pesticide preparation Pesticides (bottles, bags, boxes), shelves, scales, measuring cups Support of pesticide choice for the pests Check and warning of pesticide misuse Pesticide or fertilizer application Pesticides, fertilizers, machines (sprayers, spreaders), fields, plants Support of appropriate and reasonable agricultural chemicals application Machine operation Parts of the machine (handles, levers, buttons, keys, attachments) Navigation of the machine operation Prevention of the operation mistakes Sawing or planting Seeds (bags, boxes), seedling trays, sawing or planting machines, fields Confirmation of crop cultivars, planting time and place Harvest Harvesting machines, container cases, baskets, fields, plants Confirmation of harvesting time and place Traceability of the products Prototype system Based on this system design, we developed a prototype system to recognize agricultural operations using small sticker RFID tags, wearable RFID reading devices, and wireless networking. Fig. 1 shows the architecture of this system. 216

3 Recognition server to recognize the operations サーバー RFID Reading record DB Data Wireless LAN Wireless LAN AP Data sending Wearable devices which the workers put on RFID readier PDA Data Reading Objects for the operation (Pesticide bottles etc.) Fig. 1. The architecture of the prototype system to recognize agricultural operations. Tag Tag 1) In advance, the RFID tags are stuck to the objects which are used in the agricultural operations. The names and the kinds of these objects are inputted with these tags ID (object ID) to the database (DBMS: Microsoft Access 2003) in the recognition server (OS: Microsoft Windows Server 2003). 2) The task patterns as combination or sequence of the object ID and kinds are defined and are inputted to the database. 3) The wearable devices are composed of a RFID reader which can be put on the worker s arm and a PDA which can be connected to wireless LAN (Wi-Fi). The reader put on by the worker reads the object ID of the RFID tags while at the agricultural operations. The PDA continuously sends the data of the object ID and the reading time to the recognition server via wireless LAN. 4) The application of the recognition server (server application) receives these data and stores them to the database. It detects each task in the agricultural operation by matching the task pattern to these time-series data which are recorded by reading the RFID tags. 5) The server application can show the time-series data of the touched objects and the detected tasks while at the agricultural operation, on the web pages. The prototype system supports two types of small passive-type RFID tags: microwave type (2.45GHz) and electromagnetic type (13.56MHz) (Table 2). Fig. 2 shows the RFID tags and the reading devices of this system. The recognition server can administrate the data from both types of the RFID devices in the same way. Table 2. RFID tags and readers which were applied to the prototype system. Type of RFID RFID tag RFID reader Microwave type (2.45GHz) µ-chip (inlet sticker) Hitachi, Ltd. µ-chip reader with built-in antenna Hitachi, Ltd. Electromagnetic type (13.56MHz) Britem TS-L102CC Lintec Corporation WIT-150-T (wristwatch type) Welcat Inc. 217

4 13.56MHz RFID 2.45GHz RFID tags 13.56MHz RFID 2.45GHz RFID Fig. 2. Two types of the RFID tags and reading devices of the prototype system. Basic Verification In order to verify basic performance of the prototype system, we carried out the operational tests on the assumption of the simple tasks that a worker picks up three different pesticide bottles from a shelf. In advance, the task patterns and the object ID of three bottles and a shelf were inputted to the database. After the RFID tags were stuck to these objects, the test worker read the tags using the wearable device put on his arm while picking up the bottles from the shelf. The tests were set on two cases of reading the tags consciously by checking confirmation sound and light on the reader, or unconsciously. Using the stored data by reading the tags on the objects, it is possible to identify the objects and to detect the tasks (Fig. 3). When the worker tried to read the tags consciously, all of the tags could be read accurately and all of the tasks could be detected. On the other hand, when unconsciously, the percentage of accurate tag reading was 88-96% and the percentage of accurate task detecting was 75-92% in the case of using the microwave-type RFID devices (Table 3). This result shows that successfully reading the RFID tags in the operation is required in order to detect the tasks accurately. 218

5 Raw data of RFID tag reading Processed data of task detecting Fig. 3. The time-series data of RFID tag reading and task detecting. The example data on the web pages of the server application. Table 3. Results of the operational test of the prototype system to detect the trial tasks. Trial Pesticide 1 Pesticide 2 Pesticide 3 Subject A 1 Detecting rate 2 75% 3 4 Subject B 1 Detecting rate 2 83% 3 4 Subject C 1 Detecting rate 2 92% 3 4 Symbols : Rightly detecting : Not detecting the pesticide : Not detecting the shelf Discussion As applications of ubiquitous computing technologies, a lot of systems to support the various operations in living and working environments have been proposed. However, the researches on how to recognize the workers operations and tasks have been not sufficient. Therefore, the scientific data collection and analysis on the actual operations in the workplaces is required. We developed a prototype system to recognize agricultural operations automatically based on RFID, and we carried out the basic operational tests of this system, in order to verify the effectiveness of the method to recognize agricultural operations. As a result, it was possible to detect the tasks from the time-series data which were recorded while at the simple operation. 219

6 However, it was clarified that there were some problems to be solved for further development of a practical system, on RFID reading, data sending, and task recognizing. In order to detect the tasks accurately, it is required to read the RFID tags on the objects rightly. For this purpose, there is a method to touch and read the tags consciously by hearing confirmation sound or seeing confirmation light of the reader while at the operation. We will verify the range of conscious motion to read the tags while at the various operations and the range of effect of such motion to the efficiency of the operations. On the other hand, the workers would prefer a method to detect the tasks without requiring conscious motion, if possible. In order to realize this method, it would be required to improve the system for increase of the detecting rate of RFID tags and to devise an algorism to estimate the tasks by using the fragmentary RFID reading records. In production and management in agriculture, this system is available not only for recording the operations, but also for navigation of the operations, process control, labor management, cost accounting, and so on. For example, collaborating with the Navigation System for Appropriate Pesticide Use (Nanseki, et al., 2005), it might be possible to identify the pesticides to use accurately and to give the workers warning at their pesticide misuse. It is necessary to study what kind of workplaces the system to recognize the operations can be applied for, not only in agriculture but also in the other fields. References Nanseki, T., K. Sugahara, and T. Fukatsu (2007) Farming Operation Automatic Recognition System with RFID, Agricultural Information Research 16(3): (in Japanese) Nanseki, T., K. Sugahara, T. Watanabe, et al. (2005) A navigation system for appropriate pesticide use: design and implementation, Agricultural Information Research, 14(3): (in Japanese) Nanseki, T., M, Hirafuji, and K. Sugahara (2003) Equipment, method and program for agricultural operation record management, Japanese patent No Sugahara, K. (2005) Traceability system for agricultural products using RFID and mobile technology. Proceedings of the International Seminar on Technology Development for Good Agricultural Practice in Asia and Oceania, Tsukuba, Japan: Sugahara, K., K. Sato, and Y. Kono (2007) Traceability system for agricultural products distribution based on RFID technology. Proceedings of EFITA/WCCA 2007, Glasgow, UK: CD-ROM. Sugahara, K. and S. Omatsu (2004) Traceability system for agricultural products using RF-ID and mobile phones. Proceedings of AFITA/WCCA 2004, Bangkok, Thailand: Sugahara, K., T. Nanseki, and T. Fukatsu (2007) Development and verification of a prototype system to recognize agricultural operations automatically using RFID. Proceeding of the Joint Meeting on Environmental Engineering in Agriculture 2007, Tokyo: CD-ROM (in Japanese) Yokoyama, K. (2005) Promoting the good agricultural practice movement through interactive and seamless communication based on user-friendly mobile information technology. Proceedings of the International Seminar on Technology Development for Good Agricultural Practice in Asia and Oceania, Tsukuba, Japan: