Using Geofencing for a Disaster Information System ShivsagarGondil, Guide ,IEEE, Saraswati Yadav, Member,IEEE, Komal Wagh, Member, IEEE,Shreya Thakur, Member, IEEE Abstract—This paper proposes a disasterinformation system with the geofencing equipment to spotthe association of users as well as provide in a row of the risk in favour ofthem. The system is collected of client-server planning; the head waiter collectdanger information from a variety of information sources and the client watchesthe user on the way to inform the in sequence as the need arise. To notice theuser’s society the client creates a virtual barrier called geofencing at thedangerous region based lying on the danger information stored into the headwaiter, and monitor the user’s entrance as well as outlet of the fence. so the schemecan deliver warning and advices suitable to specific users failing. Weimplemented a prototype system and evaluated the accuracy of the system. Thelocation of the user was detected among high correctness while incoming thefence, but the correctness was low when exiting the fence. Keywords—geofencing;location-based services; navigate user swift; iOS application I. INTRODUCTION Japan suffers big damage from natural disastersevery year.
The cause of this is due to no correct information to the peoplewho need it. There is a report entitled “Evacuation instructions andquestionnaire survey about evacuation directive” by the Japanese Cabinet Office1. Table I and Table II show the questionnaire results.
In Table I, theyasked the behaviors when people knew evacuation instructions or evacuationdirectives. The answer “Remained in their houses” was the first place. In TableII, top reasons for this were “They thought evacuation was dangerous because ofheavy rain during the night” and “They did not think that they suffer from thedisaster”. Thus, it is obvious that the current information delivery method isnot suitable to residents. In particular, the current evacuation advices andinstructions do not inform risk enough, because the scope of these advices andinstructions are too wide.
If a system can deliver directlysuch risk information only to people who need it, the damage may be possiblyreduced. This research aims at developing a system that detects people’smovement and delivers risk information. For this purpose, we inspected theaccuracy of detection of people’s movement using geofencing, which dynamicallydefines geographic area of interest. By using geofencing, it is possible todetect entries and exits of people at the specific area. Thus our system candeliver what is happening at a particular area directly to the users. TABLE I.
THE BEHAVIOR WHEN PEOPLE KNEW EVACUATION INSTRUCTIONSOR EVACUATION DIRECTIVES (KANI CITY) (THE TOP FOUR ITEMS) TABLE II. THE REASON WHY PEOPLE REMAINED IN THEIR HOUSE INSTRUCTIONSOR EVACUATION DIRECTIVES (KANI CITY) (THE TOP FOUR ITEMS) II. THE GOAL Our system delivers riskinformation timely to specific users who are in the area where a disaster hasoccurred or may occur with high probability.
We assume that each user has asmart phone with position detection and Internet connection capabilities.Because the users usually handle their smart phones, they can also acquireinformation smoothly when a disaster occurs. Moreover, it is possible to detectthe user’s current location and receive information on the disaster from theInternet. 978-1-5090-0806-3/16/$31.00 copyright 2016 IEEE ICIS 2016, June 26-29, 2016, Okayama, JapanIII. THE PROPOSED METHOD A. What isgeofencing Geofencing is a mechanism thatmakes a virtual fence in a specific area 2.
The application sets a geofenceat a dangerous area and gives risk information to the user. Fig. 1 shows themovement against a geofence. Fig.1.
Geofencing action example In order to define a fence, thecoordinate (latitude and longitude) of the place are required. A circular areais defined by the coordinate and radius. A geofence is set to the circular area3. B. How touse the geofencing The system using geofencing ispossible to deliver the disaster information to the user who has just enteredthe fence. In this research, we implement geofencing with the Core Locationframework of iOS. This framework provides a detection of the entries and exitsof the user with the observation of a specific geographic region. Thegeographic region is an area defined by a circle with a specified radius arounda known point on the earth.
Every time the user crosses the boundary of theregion, the system generates an event for our application. This enables thenotification of the disaster information. That is, by using the observations ofgeographical area, it is possible to detect user behavior in the same manner asthe definition of geofencing.
Moreover, the system does notreport the event until the user goes into the region further from the boundaryplus a system-defined cushion distance. This cushion value prevents the systemto generate numerous events while the user is traveling close to the boundary.The cushion distance is determined by the hardware and the locationtechnologies that are currently available 4.The system navigate the user tocome out from disaster affected area. IV. SYSTEM CONFIGURATION The system is composed ofclients, a server and information sources. Fig. 2 shows the system structure.
Fig. 2.System structure Each client is an applicationprogram running on iOS.
It connects to the Internet and obtains the informationfrom the server. Moreover, it defines a geofence based on information from theserver, and notifies disaster information to the user. The client isimplemented by using Xcode7 and swift2, and tested by iOS simulator and realiPhone6. The server is a web applicationrunning on Linux (Centos7). It is composed of Apache, MariaDB, and PHP. Theserver acquires disaster information from information sources. It analyzes theinformation and stores the result in a database.
The database is used to definea fence by the client. An information source is the RSSfile of Weather Warnings and Advisories that Yahoo! JAPAN provides 5. The RSSfile, provided in the RSS 2.0 format, contains “Special alert,” “WeatherWarnings,” or “Advisories” across Japan. The RSS file is updated regularlyaccording to the information announced by the Japan Meteorological Agency. V. PROCESSING FLOW As an example, suppose that thepossibility of flood increased due to a heavy rain continued for long time. Asthe result, a flood warning has been issued to the area.
Then, the server’s PHP programacquires the warning by means of RSS files from the Internet. Then, it storesthe disaster information in the database. On the other hand, a clientperiodically accesses the server to check new information. The server programretrieves the database based on the client’s request and returns the resultincluding location data to define a fence in a JSON format.
In this research,we assume that the specification of the fence is decided on the server-side.The client sets the fence by using the CLCircularRegion class.Then, the client startsmonitoring of the entry and exit of the user to the fence by calling thestartMonitoringForRegion method of the CLLocationManager object.
When the userenters the fence, the locationManager:didEnterRegion method is invoked. Then,the client warns the user that you have entered the dangerous area. When theuser exits the fence, the locationManager:didExitRegion method is invoked.Then, theclient notifies the user that youhave exited the dangerous area. Fig.
3 shows a flowchart. Fig. 3.Work flow of the system When thewarning is cancelled, the client finds no warning on the server. Then, it callsthe stopRangingBeaconsInRegion method of the CLLocationManager object to stopmonitoring of the entry and exit of the user to the fence. Fig. 4 shows thescreen when operating in the foreground.
Fig.4.Screen shot at foreground When operating in the background,the notification is performed using the notification banner. In the background,”Background fetch” of “Background Modes” is used to acquire disasterinformation automatically. Background fetch enables the application toregularly download and process a small amount of contents from the network.Fig. 5 shows the screen when operating in the background.
Fig. 5.Screen shot at backgroundVI. EXPERIMENT A. Methodof the experiment Thisexperiment was conducted to confirm whether information delivery works actuallyusing geofencing.
This subsection describes our experiment method. A usercarried a real iPhone device, and defined a fence. Then the user entered andexited the fence.
The fence was installed in a circle whose radius was 100mcentered on Tokyo Senju Campus of Tokyo Denki University. The fence size wasdetermined for small-scale disasters such as landslips. The measuring range was 300m from the centerof the fence. We recorded the behavior of the application while moving every10m distance. The measurement was done three times with Wi-Fi on and off.
B. Resultof the experiment Table III shows the experimentresult, and Fig. 6 shows the place where notice movement was done. The “NA” inTable III denotesthat the system did not detect the entry or exit of the fence, and then theuser could not receive risk information. TABLEIII. RESULT OF THE EXPERIMENT Fig. 6.
Location where notice of movement was doneIn the case that of Wi-Fi was on,the user got information at the entry or exit of the fence. However, thelocation was not accurate. When entering the fence, the user was notified atthe location of 120-130m, while the radius of the fence was 100m. That is, therisk information was delivered to the user at the location of 20m-30m outsideof the fence. When exiting the fence, the userwas notified at the location of 220-230m.
That is, the notification of the exitwas at a distance of more than 100m from the fence.On the other hand, in the casethat of Wi- Fi was off, the user did not get any information for both entry andexit of the fence. C.Consideration When entering the fence withWi-Fi on, risk information was delivered to the user at 20-30m front of thefence. It is considered that the error occurred due to the buffer region of thefence and the positioning error of the GPS. However, the notification wasperformed at a position before entering the fence, it is possible to providethe information before the user enters a dangerous area. When exiting the fence with Wi-Fion, the notification was performed at the location more than 100m away from thefence.
We consider the reason of the error for exit is different from that forthe entry. More study is necessary. The system could not detect theentry and exit of the fence in the case that of Wi-Fi is off. This is becausethe location is computed more precisely using information from the Wi-Fi by thelocation information service provided for iOS devices. VII.
RELATED WORK The term “geofencing” is usedfrom around 2000. It appeared in research literature by Munson and Gupta 6 in2002. Geofencing is one of core technologies today for location-based services(LBS) including advertising, tracking, and risk management. Szczytowski 7proposed an approach based on combining geofencing with social networkingsystems (SNS) to organize unstructured information collected from SNS. Yelneand Kapade 8 designed a help-me application running on an android operatingsystem based on geofencing.
Detection accuracy and power consumption are veryimportant for geofencing applications. Nakagawa et al. 9 proposed a methodfor position detection whose activation frequency is determined by speed towardthe target spot. Alsaqer et al. 10 investigated accuracy and battery-use ofEsri’s geo-trigger service in small, outdoor, geo-fenced areas. VIII. CONCLUSION A system to present disasterinformation based on person’s movement was proposed.
We implemented anexperimental system by using geofencing and evaluated the system in an urbanarea. We confirmed that our system notifies disaster information when a userenters the fence with Wi-Fi on by the experiment. The location was at 20-30moutside the fence. When exiting the fence with Wi-Fi off, we found that theinformation is delivered at the place more than 100m outside the fence.
Wi-Fiis necessary for precise detection of location by using geofencing.Forlarge-scale disasters, the fence will be several kilometers of length. Furtherstudy is necessary to evaluate the system in case of larger fence sizes. Improvementof the location accuracy is also very important to deliver risk informationtimely to users. Our system should be able to define multiple fences at thesame time to support real natural disasters.
Information sources also should beadded to our system, including government agency announcements and socialnetworking services.It also navigate the user.