Sensor service grid as real-time monitoring infrastructure andits application to soil moisture observation in Thailand
Kiyoshi HONDA1 , Aadit SHRESTHA1 , Apichon WITAYANGKURN1 ,Rassarin CHINNACHODTEERANUN1 and Masaru MIZOGUCHI2

Abstract:Sensor Service Grid (SSG) makes it possible tocollect soil moisture sensor data from farms distributed invarious parts of the world. It is useful for agricultural fieldmanager and crop-soil researchers. SSG is the core system
in Sensor Asia Initiative for easy setup and managementof sensors. It realizes “sensor plug & play” which covers sensor node installation, registration, calibration equation and other sensor metadata, as well as visualization ofprocessed sensor data. In order to evaluate the efficiency
of SSG, a spinach field monitoring system has been setup
near Chiang Mai, Thailand which collects soil data including moisture, temperature and electrical conductivity, together with meteorological observation data. We have confirmed that the data was accumulated in a SSG server overthe Internet, and it was accessible by everyone easily. Thissystem is currently utilized as a practical tool to secure
the food safety between agricultural producers in Thailand
and consumers in Japan. The real time information canbe browsed easily by Japanese consumers using a mobilephone. Moreover, the system is extremely useful to stimulate researches on application of soil sensors.
Key Words : Sensor Service Grid (SSG), Sensor Observation Service (SOS), soil sensors, real-time data collection,
sensor metadata

1. Introduction
An initiative called Sensor Asia, started at the Asian Institute of Technology (AIT), Thailand has been promoting high density sensor observation networks. Sensor Service Grid (SSG) is a core system of the initiative to realize
sensor plug & play, covering from installation of sensor
nodes to visualization and publishing sensor data to applications. SSG services are also capable of storing sensor
metadata and configuring sensor nodes on-site or remotelyfrom the server itself. Thus automatic configuration andcomplete control of the data paths from the beginning to
the application end is possible. University Co-operatives
in Japan, together with Sojitz Co., Ltd. started to importspinach from Thailand several years ago. The producer
1 Remote Sensing and GIS, Asian Institute of Technology, Pathumthani,
Thailand. Corresponding author: Kiyoshi HONDA
2 Department of Global Agricultural Sciences, University of Tokyo, 1-1-1
Yayoi, Bunkyo-ku, Tokyo 113-8657, Japan.
2010 年 1 月 6 日受稿 2010 年 5 月 21 日受理
土壌の物理性 115 号, 25–28 (2010)

in Thailand is SWIFT Co., Ltd., which contracts farmers
in Chiang Dao District, Chiang Mai province in Northern
Thailand. SWIFT has been applying European Good Agricultural Practices (EuroGAP) for producing safe food aswell as for environment conservation and rural development. However, a real time monitoring system is thought
to be required because the confidence on food safety especially imported food among consumers in Japan is now in
critically low level. We have installed a sensor observation
system using SSG at one of the spinach fields to monitor
the practices of producers, to provide images and information to Japan real time, and thus to confirm the efficiencyof SSG. The system contributes to secure the food safety
and to foster the confidence among consumers (Honda etal., 2008, Internet URLs indicated in References ).

2. Implementation Overview
The details of the sensors used at Chiang Dao field inChiang Mai are as follows:(i) A weather station (Davis Instruments) with rain,wind speed/direction, air temperature, humidity, solar radiation and UV radiation.
(ii) A network camera and fieldserver (Hirafuji et al.,2007).
(iii) CO2 sensor from SenseAir(iv) 2 heat flux sensors.
(v) 4 soil moisture sensors (3 Decagon 5TE, and 1
Decagon ECH20-TE sensors which are capablemeasuring soil moisture, soil temperature and electrical conductivity deployed at depths of 4 cm, 8 cm,16 cm and 32 cm, connected to Decagon Em50 datalogger).
The data from these sensors are being collected in fieldside agent box based on Sensor Observation Service (SOS)(Na and Priest, 2007) called SOS Station. The SOS Station is capable of collecting data from different sensor interfaces and storing them in an internal database, and also
syncing the data in real-time to SSG servers. The SOS Station is in communication with the SSG server using an Internet connection from near-by primary school, Phatthana

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Station to users via SSG is shown in Fig. 2. The SOS
Station collects data from the sensor systems connected toit and stores it in a local database. The data is sent to theSSG server from which users can view it in graphs andmaps. The data can also be obtained in standard XML
O&M document. At the same time easy configuration andcontrol of SOS Station can either be done locally or fromremote locations by connecting through the SSG server.
All data and configuration information are synchronized
between the SOS Station and the SSG server.

Fig. 1 Sensor setup at Chiang Dao spinach field, Chiang Mai.

Ton Nam Khun Khong School, 400m away. Under theproject of “School Net” in Thailand, the school has an IPSTAR satellite internet service provided by Thaicom Plc.,even in such remote area. The field site deployment of sensors is shown in Fig. 1.
A WiFi connection covering 400 m has been establishedfrom the school to an agricultural research center, LumNam Khun Khong Agricultural Research Station, adjacentto the spinach field. The last section of the network to thesensor setup is covered by an 80 m long Ethernet cable, asline-of-sight could not be obtained for the WiFi.

3. Sensor Service Grid (SSG)
SSG is a sensor data middleware which provides users
with a platform to receive data from remote field sensor
networks. As it follows OpenGIS standards and specifications (OGC, Inc.), other applications can be built based onthe SSG. The SSG implementation has been designed torun in two parts – one at the sensor node in the field, i.e.
the SOS Station, and the other at the SSG central server.
The SOS Station is a combination of sensor systems with asmall Linux Box which gives a high capability for storingsensor data and provides data connectivity to outside serverusing standardized data exchange protocols. The SOS Station is based on Sensor Observation Service (SOS) and thesensor data can be obtained in SensorML Observation andMeasurement (O&M) encodings (Honda et al, 2009).
The overall structure and information flow from SOSThe SOS Station has the capability to collect data fromseveral types of sensor systems, weather stations and dataloggers using various interfaces. As shown in Fig. 3,
feeder systems have been developed separately for theaforementioned devices. The feeder templates are open,
supporting an open system and easy installation; any device manufacturer can utilize these templates. The webserver implemented on the SOS Station gives access to all
sensor data as well as device and sensor configuration. A
command service linked to the SSG provides remote administration and configuration capabilities. A SOS Station
owner with proper authorization can control the systemfrom anywhere. All data is synchronized to SSG serverusing messaging service. Synchronization is done not onlyfor the sensor data and metadata, but also for sensor anddevice configuration.
The primary work of the SSG implementation at the central server is the collection of data from all SOS Stations
around the world, the management of all such stations, andthe dissemination of information collected through the Internet. One of the main features of Sensor Asia is userfriendly data visualization. After the SOS Station is registered at the SSG, and it starts sending data, the positionof SOS Station will automatically appear on the Web GIS
map, together with its list of sensors as shown in Fig. 4.

Fig. 2 Information flow from SOS Station to users via SSG.

Fig. 3 SOS Station service layer diagram.

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研究ノート：Sensor service grid and its application to soil moisture observation in Thailand

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Fig. 4 SSG showing the remote field location of SOS Station on Web GIS map.

The data being received from the SOS Station can easily be viewed in real-time in the form of simple dials andgraphs. Sensor configuration setup automatically creates
this visual interface.

4. Application to Soil Sensor
Deploymenttion data have been successfully accumulated in a SSG
server over the Internet. The data on the server is accessible by everyone. Currently, the data is being displayed ina university’s canteen as well as on a home page designed
for mobile phones.

Once deployed in the field as in Chiang Dao, the SOS
Station can be used to register the soil moisture and othersensors at the SSG central server. Sensor set can be added
or changed easily with a user-friendly interface; the calibration equation and other parameters can be set by user or
pre-set settings selected appropriately to obtain the correct
sensor output.
The data from a Decagon 5TE sensor deployed at Chiang Dao is shown in Fig. 5. The output of this sensor is acomplex convoluted value which then needs to be deconvoluted to obtain the three sensor parameters of soil temperature, electrical conductivity and soil moisture. SSG
has provisions to pre-set complex calibration equations andother sensor metadata so that the user can just select theproper sensor and required output type from a drop downmenu. In case the calibration equation needs to be changed
due to a different soil type or because of re-calibration at
field, there is also a provision to over-ride the preset equation by user. Fig. 6 shows the soil moisture sensor parameters as well as the calibration equation that has been presetin SSG server. The generation of automatic graphs and dials is enhanced by options of graph type such as round meter or scale, the minimum and maximum values, the digit
display format etc..
Once the soil moisture sensors are configured and registered at sensor site, the SOS Station can be controlled
and configured remotely from the SSG itself. Accessing toSOS Station (local access) and SSG (global access) is almost transparent to users. They can control sensor configuration and access to sensor data by accessing either SOS
Station or SSG. This overcomes the problem of local setting difficulties at the sensor site. SOS Station owners canaccess their sensor data locally or globally.
Soil sensor data, together with meteorological observa-Fig.
5 SSG interface showing de-convoluted data from
Decagon 5TE sensors, as well as the battery power of Em50 datalogger (Data acquired midday of 28 October, 2009).

Fig. 6 Decagon 5TE sensor parameters and calibration equationpreset in SSG server.

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5. Conclusions(2010)

Kameoka, T. and Shimamura, H. (2007): Field server project.

One of the problems in setting up soil sensors or any
other type of sensors in the field and their operation isthat the work requires highly skilled engineers. It resultsin high installation cost and eventually will hinder the deployment of high density sensor networks. SSG has beendeveloped to solve this issue by supporting “sensor plug& play”, registering sensor nodes, archiving, publishing,and visualization. These functions are important to lower
the cost of installation and the make soil sensor deployment as a simple off-the-shelf endeavor for everyone. SSG
supports SOS as a base technology to standardize sensor
information exchange within and outside of the system.
SSG and related infrastructure are ideal for soil observations using various sensors and dataloggers as well as forother types of monitoring applications. The test site at Chiang Mai province has proved that SSG is quite useful infrastructure for application in the study of soil sensors.

In Proceedings of the 2007 International Symposium on Application and Internet Workshops (Saint 2007 Workshops), 1519 January 2007, Hiroshima, Japan. IEEE Computer Society:
Washington, DC, USA, 2007; ISBN 0-7695-2757-4/07.
Honda, K., Shrestha, A., Chinnachodteeranun, R., Mizoguchi, M.,
Shimamura H. and Kameoka. T. (2008): Spinach field monitoring for bridging Thai producer and Japanese consumer under sensor Asia. In Proceeding of SICE Annual Conference,
The University Electro-Communications: Tokyo, Japan, 2008,2582 – 2585.
Honda, K., Shrestha, A., Witayangkurn, A., Chinnachodteeranun,R. and Shimamura H. (2009): Fieldservers and sensor servicegrid as real - time monitoring infrastructure for ubiquitous sensor networks. Sensors, 9: 2363 – 2370.
Na, A. and Priest, M. (2007): Sensor observation service (OpenGIS Implementation Standard). Open Geospatial Consortium
Inc., OGC 06-009r6, Wayland, MA, USA.
URL of the home page for mobile phone users: http://chiangdao.
sensor-asia.net.

References

URL of the home page of Sensor Asia : http://www.sensor-Hirafuji, M., Ninomiya, S., Kiura, T., Fukatsu, T., Hu, H.,

asia.net.

Yoichi, H., Tanaka K., Sugahara, K., Watanabe, T., Ehsani, R.,

要旨

世界の農場に設置された土壌センサーのデータを GIS 上でリアルタイムに一覧できると，農地管理者や作物 · 土壌系の研究者にとって，大変便利である．開発したセンサーサービスグリッド（SSG）はこれを実現するセンサーアジア構想の中核のシステムである．SSG ではセンサーの登録，補正式やその他のセンサーメタデータの管理，可視化などに関するセンサープラグ＆プレイが実現されており，容易に土壌センサーデータをリアルタイムに収集し，管理することができる．この SSG の有効性を検証するために，タイ王国チェンマイのホウレンソウ草畑に圃場モニタリング装置を設置し，現地の気象条件と一緒に畑土壌の水分 · 温度 · 電気伝導度をリアルタイムで測定できるようにした．実証実験の結果，開発した SSG により，測定データがインターネット経由でデータサーバに蓄積され，誰もが簡単にデータ閲覧できることが確認された．現在，このシステムは，タイの農作物生産者と日本の消費者で食の安全を確保する１つのツールとして実際に利用されており，携帯電話で現地の情報を確認できる．SSG は土壌センサーの応用開発研究を促進させる上できわめて有用である．
キーワード：センサーサービスグリッド（SSG）, センサーオブザベーションサービス（SOS）, 土壌センサー, リアルタイムデータ収集, センサーメタデータ