RainWatch Project: Location-Awared Realtime Detection and
Notification of Rain on Internet-Based Sensor Network
Kaveevivitchai Sathita
Hideya Ochiai
Hiroshi Esaki
The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656, Japan
wan@hongo.wide.ad.jp jo2lxq@hongo.wide.ad.jp hiroshi@wide.ad.jp

Abstract— This paper introduces RainWatch project whichenable rain-sensitive users to monitor real time rain
information in area of users’ interest. Real-time detection andnotification of rain situation will allow users to takeappropriate preparation (e.g., evacuation from the area in caseof disaster prevention), which can prevent loss of lives anddamage on our properties. The RainWatch system stands on
top of Live E! data platform, which is a wide-area sensor
application testbed operated by multiple-organizations
distributedly with about 100 Internet weather stations. The
RainWatch system monitors the rain state around a certain
geographical point and makes notifications or warnings (e.g.,
the rain is approaching) in real-time to the users that haveinterest in the point. Strong needs for this application will
influence the design of the sensor networking infrastructure
regard to location-awareness and real-time-ness.

I.

INTRODUCTION

Internet weather stations have enabled realtime
collection of environmental data over wide geographicalareas. The collected data should be practically managed ina distributed manner because of operational reasons (e.g.,multiple-organizations) and of the vast data amount. On theother end, there will be many types of data retrieval
requests generated by user applications. To design thesystem that provides sufficient performance for thoserequests is one of the major issues in this research area.
This paper describes RainWatch Project as one of theapplications that provide information in term ofusers/sensors’ location-aware. This project is aimed toprovide useful-information for rain-sensitive end users via
e-mail or by other means; e.g., (1) the rain has been
observed within 6 km around this point, or (2) the rain isapproaching toward this point. This RainWatch service
extracts a small set (specified by geographical-area) of raw
data from the massive dataset, analyzes and summarizes it
into user-friendly format. In other word, RainWatch is theapplication, which aggregate interested raw data from thelocation-aware dataset. This application provides the idea
in designing Internet-based sensor networks applications.
RainWatch project is one of the approaches to tackle on
recent natural disasters, which causes lost of lives anddestructions; e.g., torrential rain, flash flooding and/or heatisland effects in the metropolitan. By observer (end-users)
able to receive prior notice about the rain that will occur

shortly, they can take appropriate actions in order tominimize those possible effects.
We recognize that there are existing methods which
provide rain forecast based on Surface Weather Observation,
Weather satellites, IR-image, Meteorological radar, together
with prediction models [1]. However, this RainWatch projecttakes advantage of real-time-ness of the system for watching
the current rain situation around Point of Interest (POI) andprovides the report or notification to the end-users. So they
can further take actions in preparation for the coming rain.
This output can be used in integral with other methods toprovide more accurate notifications or warnings for the endusers.
We deploy the RainWatch system over Live E! sensor
networking platform [2]. Sensor readings from about 100
Internet weather stations are distributedly managed on theLive E! data platform, and users can retrieve those data for
their own activities. By applying the RainWatch system tothe real sensor testbed, it is expected that we will get thebeneficial examples as follow:

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Workers in an outdoor construction site must careabout the rain status of their location for their own
safety. The workers can halt their work andmove out from the field before the rain hits thesite.
By previously knowing about the coming rain,
stores can pack up products that set outdoor toprevent them from damage
Stores can also enhance some sales such as
sale of umbrella by preparing it to be just in
grasp for the customers
Disaster prevention in case of flash flooding
can be achieved by prior warning
II.

LIVE E! PROJECTLive E! Project is an open research consortium
established by means of collaboration among industry andmany academic institutions. This project provides platform
for sharing digital environmental data, currently focusing on
weather data namely; temperature, humidity, pressure,rainfall, wind speed, and wind direction. These data arecollected by sensor nodes embedded with Internet

connectivity which allows the data to be available over the
network in real-time. Sensors are installed and operated
individually by interested stakeholders which allow them tobenefits from the collected data however the data is also
opened for the public.
Live E! has adopted three-tiered architecture formanaging the system (Figure 1). The system is composed of(1) sensor layer, (2) data management layer and (3)application layer. The sensors, at the bottom layer, observe
the environmental data and transmit the result to the data
management platform. The data management platform, at the
middle layer, is operated by multiple organizations
collaboratively over the Internet in a distributed manner. The
applications, at the top layer, fetch interested data from thedata platform. There are three main areas of application, foreducation material, for public services, e.g., disaster
reduction, and for business usages [3].

A.

System Overview

The RainWatch system works as an application of Live
E! Data platform. It periodically retrieves the current datafrom the platform, analyzes them and reports the result tothe end-users. The end-user is bound to a location pointed
by latitude and longitude coordinates, which in this paper
referred as Point of Interest (POI). The POI entity in the
RainWatch system registers all the sensors within its 20
kilometers radius and observes all the sensors’ rain
information. The POI summarizes the happening events inthe area from the observed rain information and reports thefollowing five statuses or events (like a watchdog) to theend-user:(1) No rain in its proximity(2) There is a rain in its proximity

The Live E! Data platform works as a testbed for suchapplications. In February 2009, Live E! Project has 106
weather stations across 13 countries, and the platform is
operated by 9 organizations. Kurashiki-city, Okayama, Japan
has high density of weather stations where 26 sensors are
deployed in 25km x 25km. The RainWatch system uses thedata of this area as its testbed, due to the number of its
sensors per square unit.

(3) The rain is moving toward the POI(4) The rain is moving outward from the POI(5) It is raining in all area around POI.
In case a sensor in its range detects the rain, it reports "(2)There is a rain in its proximity". At the same time, the POI
records the snapshot of rain-detected sensors and watchesout for the next report. If there is more than one sensor
detecting the rain, the POI will take (i) the location of
detected sensors, (ii) the time of detection and (iii) the rainstate into account for analyzing relationship among them. In
the case that the distance of first detected sensor is greaterthan the second detected sensor, it reports, "(3) The rain ismoving toward the POI". While the opposite case has
occurred, it reports, "(4) The rain is moving outward form
the POI".
B. System Architecture and Implementation

Figure 1: Live E! System Architecture

III.

RAINWATCH PROJECTRainWatch Project is one of Live E! Project applications.
This project is aimed to transform raw collected data toready-to-use information. It takes the Live E! Sensors’monitored rain states in user’s location aware, analyzes
relationship among known change-states at certain locations(e.g., rain to no_rain states) and finally reports warning or
useful notification to the end-users which will certainly
provide more benefits to the rain-sensitive end-users.

The RainWatch system architecture is illustrated in class
diagram as in Figure 2. There are two main objects in thesystem; (1) Sensor node, (2) Point of Interest.
An area of interest covers the area of Kurashiki-city,
approximately 25 x 25 square kilometers. A POI registers thesensor nodes which located in the area and classifies themaccording to its distance from the POI. The POI entity is also
own two lists named as RainList and HistoryList. These
RainList and HistoryList are the container of the sameelement type which is called RainListNode. The POI
retrieves rain information from all registered sensors every
60 seconds. If it detects change in state at any sensor, it will
create a RainListNode. A RainListNode keeps the following
information: (1) sensors in which the state change has

occurred, (2) the time of change, and (3) the status of change.
For instance, in case of sensor detects change in state fromno_rain state to rain state, the POI creates a RainListNodeand adds it to both its RainList and its HistoryList. However,if the sensor detects change in state from rain state tono_rain state, the POI creates a RainListNode and adds it to
the HistoryList, and removes the latest node with referredsensor from the RainList. Therefore, the RainList only keeps
the information about currently raining nodes while theHistoryList records every change that occurred. This
RainListNode is also used as input for the system to evaluate
the relationship of detected cases and report for the users.

Figure 2: RainWatch Class Diagram

C. Issues for the Internet-Based Sensor Networks
Live E! Data platform, in the area we apply the
RainWatch system, the data is updated every minute bymeans of Internet [4]. This feature allows the system toprovide realtime detection and notification of rain to the endusers, which makes this system unique among other legacy
rain forecast services. Thus, to make this system achieve
their highest ability, the base-system should have efficiency
in its real time data management for received location-aware
queries. In addition, it should be able to manage large scaleof the sensor system, which provides enormous dataset to thesystem.

IV.

DISCUSSION

RainWatch System has been tested with the pre-collected
rain information data in Kurashiki-city which composed of
26 weather sensors from Live E! testbed. The duration oftested data ranges from 1 day (January 1, 2008) to 1 month(January 1, 2008 – February 2, 2008). On the test scenario,
the system calls the pre-collected data in form of .csv file andputs them into the double hash tables according to timestampand sensor-id. Then the system reads the data out according
to timestamp, in the same way as working with realtime data.
The system then analyses the data and output the result. The
average performance is in O(n) yet the average memory
usage will be vary according to the duration of tested dataO(n2). However, on the completed system, it will work withthe real-time data only, consequently there will be no needfor extra storage beside for computation. From theexperiment data, we have detected 13 rain events at Nishi
Junior High School, which is referred, as our POI. 7 eventsare distinguished rain, and 6 are intermittent rain events withshort discontinuity. The average time from first detected rainreports until the rain reaches POI is 16 minutes. Yet the prenotifications received at end-user range from 4 minutes to 34
minutes (Figure 3). The findings indicated that size of theobserved area covered by sensors would have a direct impact
on the length of pre-notification to the end-users. The larger
coverage area with dense installations of sensors willdefinitely provide longer length of pre-notification which
will allow users more time to get ready for the coming rain.

Figure 3: Time interval between the first rain detection to its arrival at POI(Tested from January 1, 2008 to February 2, 2008)

V.

CONCLUSION AND FUTURE WORKS

RainWatch Project can help us to prepare for rain properly
and prevent us from possible damage of lives andproperties: e.g., the case of outdoor construction site, storesthat sell products outdoor, umbrella seller, public sewer
management [5]. In the current state, the RainWatch system
only analyzes the rainfall status around POI, which might
not be at best accuracy, but in the future, we are planning toenhance it to be finer and more accurate by taking otherfactors into account; e.g., wind speed, wind direction. We
deploy the RainWatch system on the Live E! testbed aroundKurashiki-city to evaluate its benefits as an application. Ifthe result indicates its usefulness, we can further conclude
that the base sensor network platform has a strong needs forsupporting location-awareness in retrieving data as well as
real-time updates with regard to scalability of the system, inother word, the number of deployed sensor nodes.
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