PREFERENCE-AWARE UBIQUITOUS ADVERTISEMENT SCREEN Pekka Jäppinen Lappeenranta University of technology P.O.Box 20 53851, Lappeenranta Jari Porras Lappeenranta University of technology P.O.Box 20 53851, Lappeenranta ABSTRACT This paper presents a concept of an advertisement screen that is aware of the interests of the people in its proximity. The awareness is accomplished by fetching the preference information from the mobile devices of the people nearby the service. The information is used for deciding what kind of advertisement is shown on the screen at any given time. The structure and operation of the system is described. Description and functionality of simple prototype is shown. The performance of the system is evaluated based on simple prototype. Finally some enhancements along with future research paths are suggested. KEYWORDS Advertisement, Ubiquitous, Pervasive, Personalization, Mobile preferences, Privacy 1. INTRODUCTION The world we live in provides excessive amounts of information everywhere we go. Small walk on the city centre shows that streets are filled with advertisements, store windows contain data about products and a screen on broadcasting company building shows the latest news. The information in many cases is static and even when it is changing the change follows predetermined rotating pattern. For example a changing advertisement screen shows first a car advertisement, then clothing after that dental care and finally rotating back to car advertisement. Advertisers are thus hoping that their advertisement will fit to the interest area of a random passer-by. In order to provide meaningful advertisement for the people near the advertisement screen, the contents of the screen should change based on the interests of the users. One of the scenes in the science fiction movie Minority Report describes how the future might be with active information: John is walking in a shopping mall. As he passes different shops along the corridors, personalized advertisements are shown to him. Car, beer and traveling advertisements based on his personal preferences are presented. Everything is based on personal information fetched from the central supervision unit monitoring people. All advertisements are based on this information thus fulfilling the wishes of the user they are shown to. In order to create the Minority report like advertisement the advertisement screen has to know the preferences of the people on its vicinity. From the user perspective giving out preferences may be seen as a threat towards privacy. Thus the service should find out the user preferences without acquiring the user identity. In this paper we present an advertisement screen that shows advertisements based on the preferences of the users around. First we'll state the design principles of the advertisement screen service. We also discuss the problem for acquiring preference information in a ubiquitous service and why approaches used in traditional Internet based services are not viable. Then we describe our system and its implementation. Our IADIS International Conference e-Commerce 2007 99
Transcript
PREFERENCE-AWARE UBIQUITOUS ADVERTISEMENT SCREEN
Pekka Jäppinen Lappeenranta University of technology
P.O.Box 20 53851, Lappeenranta
Jari Porras Lappeenranta University of technology
P.O.Box 20 53851, Lappeenranta
ABSTRACT
This paper presents a concept of an advertisement screen that is aware of the interests of the people in its proximity. The awareness is accomplished by fetching the preference information from the mobile devices of the people nearby the service. The information is used for deciding what kind of advertisement is shown on the screen at any given time. The structure and operation of the system is described. Description and functionality of simple prototype is shown. The performance of the system is evaluated based on simple prototype. Finally some enhancements along with future research paths are suggested.
KEYWORDS
Advertisement, Ubiquitous, Pervasive, Personalization, Mobile preferences, Privacy
1. INTRODUCTION
The world we live in provides excessive amounts of information everywhere we go. Small walk on the city centre shows that streets are filled with advertisements, store windows contain data about products and a screen on broadcasting company building shows the latest news. The information in many cases is static and even when it is changing the change follows predetermined rotating pattern. For example a changing advertisement screen shows first a car advertisement, then clothing after that dental care and finally rotating back to car advertisement. Advertisers are thus hoping that their advertisement will fit to the interest area of a random passer-by. In order to provide meaningful advertisement for the people near the advertisement screen, the contents of the screen should change based on the interests of the users. One of the scenes in the science fiction movie Minority Report describes how the future might be with active information: John is walking in a shopping mall. As he passes different shops along the corridors, personalized advertisements are shown to him. Car, beer and traveling advertisements based on his personal preferences are presented. Everything is based on personal information fetched from the central supervision unit monitoring people. All advertisements are based on this information thus fulfilling the wishes of the user they are shown to.
In order to create the Minority report like advertisement the advertisement screen has to know the preferences of the people on its vicinity. From the user perspective giving out preferences may be seen as a threat towards privacy. Thus the service should find out the user preferences without acquiring the user identity.
In this paper we present an advertisement screen that shows advertisements based on the preferences of the users around. First we'll state the design principles of the advertisement screen service. We also discuss the problem for acquiring preference information in a ubiquitous service and why approaches used in traditional Internet based services are not viable. Then we describe our system and its implementation. Our
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service is based on the use of mobile device as a personal trusted device (PTD) that contains the personal information required for the personalization (Porras et al., 2004). Finally we'll analyze the system and its performance and suggest possible approaches for enhancing the service.
2. SYSTEM DESCRIPTION
The goal for the system is to provide advertisement on a public screen that is based on the interests of those who pass by the screen. Directed advertisements based on customer interests are used in several places in the Internet. Finding out the possible interest areas can be done in different ways. One method is to create a user profile via registration to the service, where user preferences are requested. Another way is to use cookies to trace the user behavior within the service. For example Amazon.com web store advertises the books to user based on the products that customer has bought or just looked at. An advertiser can also use cookies along its advertisement to create a profile based on the websites and internet services the customer has used. (Ghosh, 2001) Then there are service specific approaches e.g. Google selects the advertisements on the web page depending on the keyword entered for the search engine.
If we look at the aforementioned methods in Internet marketing, the selection of the advertisement topic bases either on user profile or on user action e.g. the used keyword on search. For the street advertisement these approaches are not viable. First of all, the customers of the service are random passers-by who are not actively accessing a service but rather just walking by. They might be visitors from other town and see the screen only once in their lifetime. It is not likely that they would register themselves on the advertisement service while they pass by the screen. Register beforehand to a local service that provides advertisement is as unlikely. Therefore there is no action that the selecting advertisement can base, nor a profile of user that can be used.
Even if the customer information could be acquired beforehand in the database of the service provider or on trusted third party, the problem about authentication will come up. Using passwords would require active involvement of the passer-by which is not acceptable. Automatic authentication can be done by using biometrics or special tokens. Biometric authentication would require big database towards which the biometric data is run through. This would raise a big question about privacy of the passers-by and raise alarming scenarios as was stated in Hunter's book World without secrets (Hunter, 2002). Tokens would be better from the customer point of view since they can be turned off or left home, in case the customer doesn't want to be identified. It is still questionable whether users are willing to give out their identity, even if it is in form of pseudonym and a token, in order to get directed advertisement.
So can we do it without authenticating the customer? Apart from getting the correct data from database that states the interests of the customer, the advertisement service do not actually need any identifying information. One approach is to have the preference information stored at the user's mobile device. Digital Aura (Ferscha et al. 2004) and Mobile Electronic Personality (ME) (Jäppinen, 2004) define such approaches. In digital aura concept the user preferences are transmitted to different ubiquitous services automatically to enhance for user to get more personalized services. ME defines methods for storing and accessing the personal information including profiles that are stored in mobile device, while protecting the privacy of user.
For the advertisement service these are viable approaches. The customer can remain anonymous and still get advertisement in the surrounding screens that are based on the profile.
The general architecture of the advertisement service consists of four functional units: preference provider (PP) that is on customer and preference requester (PR), service provisioner (SP) and advertisement provider (AdP) that provides the actual advertisements (Figure 1). Preference provider is a mobile device carried by the customer that holds the information about the customer's preferences and is capable for wireless communication. PP can be any kind of mobile device from mobile phone to personal server (Want et al. 2002) as long as the customer carries it most of the time.
Preference requester (PR) polls devices in its proximity to find out the preference providers from which it then fetches the preference information. PR delivers this information to service provisioner (SP). SP uses the gathered information to decide which advertisement it shows on the screen. The actual advertisement for the screen is acquired from the Advertisement Provider. In the simplest form the decision of which advertisement is fetched and shown can base on the amount of occurrences of certain preference e.g. if clothing occurs in preferences the most times, then SP will show clothing advertisement. It is possible to develop more complex schemes on selecting the advertisement which can base on more than just single preference type.
All the service side parts can be bundled in to one device or they can be separated. There can be several PRs to cover bigger area for screens that can be seen farther away. There can also be several AdPs to cover different fields of products.
3. IMPLEMENTATION
The implementation of the prototype can be divided in customer and service side. On the customer side, PDA device running on Linux operating system is used as the preference provider. In the PDA, the preferences are stored in a single xml file, which follows the XML-schema 1. The device is running a program that responds to the queries, by sending the preference values from the XML file e.g. if user has selected clothing and Sports as his preferences these are sent to Preference requester.
The service side consists of external access point as a preference requester, a standard PC with flat screen as a service provisioner and various news services for sports data provisioning. All the parts are connected to each other via IP based network. While PR functionality could be easily implemented in the standard PC,
Figure 1. Overview of System
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external access point is used to enable possibility to add more PRs that gather the preference information and thus enhance the performance of the system in the future.
The message sequence chart of the running system is described in Figure 2. The communication between the PP and PR rely on Bluetooth wireless technology. Bluetooth has been adopted in most of the modern mobile phones as well as several PDAs. Its communication range of 10 meters fits perfectly for our system as the screen can be seen only from few meters (Bray and Sturman, 2001). For bigger screen a more powerful Bluetooth transmitters can be used at PR to have better coverage. Bluetooth also has useful service discovery protocol which can be used for finding out the devices that can provide preference information. In this version of the system this capability is not used, instead the personal information providing software is running on predetermined port over L2CAP layer. The used AdPs are web pages in Internet which are accessed using HTTP-protocol.
When the system is running the preference requester constantly sends Bluetooth inquiry message to find out Bluetooth capable devices. After every inquiry it stores the found Bluetooth device addresses in its cache with a time stamp and then tries to form a connection to the predetermined L2CAP port of the found devices. If connection forming is successful PR sends following message to the device: Information_request:Interests. Once the request arrives to the PP, it gets the preferences from xml file and returns: Information_reply:Interest:<interestType>. The Interest:<InterestType> sequence can repeated so that all personal interests are in the same message. PR saves the response in its cache under the corresponding device. After the request procedure has been done with all the found devices the current list of preferences is sent to service provisioner. After that the procedure is started again from inquiry. On this time the connection is tried only to new devices found on inquiry. For devices already existing in the cache only the time stamp is updated. Devices that are not any longer responding to inquiries are removed from the cache.
Initially SP connects to the AdP and fetches the page containing advertisement which SP then stores in its own cache along with time stamp and type information (e.g. cloth advertisement). Once SP gets the list of preferences from PR, SP shows on the screen the ads that fit in the interest area of the most users. In time to time SP checks whether there is new content at the AdPs. If several advertisements fit in the interest areas, the SP rotates the most fitting advertisement in predetermined intervals.
The main factor for the service performance is the Bluetooth connection between PP and PR. The total time (TBTtotal) that it takes to fetch the preference information from N devices is:
TBTtotal=Tinq+N(Tcon+Ttransmit)
Where Tinq is the time that it takes to inquiry the devices on the proximity of the screen, Tcon is the time for creating the connection to the PTD and Ttransmit is the time for transmitting the actual data from PP to PR. The time for inquiry depends on how many inquiry train switches will be repeated. The more inquiry trains the more likely it is that all the devices in the proximity are found. The Generic Access Profile of Bluetooth standard states that inquiring should take at least 10.24 second and no more than one minute (Kammer et al. 2002) . On our implementation three switches have been used which causes the total inquiry time (with the overhead from the program) to 11 seconds. Let's assume that the average person walks 1 meter/second and PR resides on the same location as the actual screen. If the customer is 10 meters from the actual screen (the nominal range of Bluetooth) walking towards the screen, after the inquiry is done, the customer would have already walked one meter past the screen. Therefore the customer does not gain any advantage from the delivered preferences. Occasionally the inquiry failed to find every Bluetooth devices.
After the inquiry, the creation of the connection, processing of the request at PP and transmission of the preference data to PR takes average of 1.1 seconds from which the connection forming takes 1 second. If there is 20 customers just standing in front of the screen it would take 11 + 20*(1) = 31 seconds in order to get the preference data from all of them. Even without inquiry it would take 20 seconds before the preference data would be delivered to the SP. Since the time between inquiry and connection to the last device is long, it is very likely that some of the devices are no longer at the communication range of PR thus causing some additional delay. On top of that there is the overhead for transmitting the data to the SP and then making the decision what to show on the screen. It is also good to remember that the Bluetooth connection is running on top of lowest possible layer in Bluetooth stack and does not use Service Discovery Protocol (SDP). Adding more protocol layers, like RFCOMM and OBEX, as well as support for SDP, would slow down the process even more.
There are some possibilities that can help the aforementioned problems. First of all Bluetooth 1.2 standard will provide improvement for inquiry times through enhanced inquiry. The reliability of finding the devices with inquiry is near 100% and the time needed for inquiry is reduced to 5 seconds. Bluetooth 1.2 introduces also interlaced inquiry, which halves the time required for inquiry to 2.5 seconds. Similarly the paging process is enhanced on Bluetooth 1.2 with interlaced page scan. Interlaced page scan halves the time needed for forming connection. Thus the use of Bluetooth 1.2 would reduce the needed times from 31 seconds to 2.5 + 20 (0.5) = 12.5 seconds, or to 10 seconds if inquiry is not needed. (Bierstein and Linsky, 2004) Even with these enhancements the application is too slow. Bluetooth 2.0 and 2.1 do not bring any speed up on connection forming. Extended inquiry response introduced in Bluetooth 2.1 standard can be used for finding devices that provide personal preference instead of using heavier SDP.
Adding some intelligence on PR's data sending to SP can enhance the system performance. For example the preference data can be sent to SP after five PPs have provided their data instead of going through all the found devices before sending data. More PRs can also be added to distribute the data fetching process. With more PRs it is also possible to utilize predictive Bluetooth network used on Bluetooth based guidance system, to find out the possible customers before they are in the proximity of the actual screen and preference fetching networks (Koponen et al. 2004). These solutions require more research to be conducted.
Besides the performance issues there are few other things that should be further research. One important research question is the categorizing of the interest areas. What is the proper detail level for such a service. Knowing that person is interested in clothes or sports does give just a rough idea and more accurate knowledge would likely be more beneficial. Besides basic interests there can be other factors that can be used to determine the proper advertisement to be shown. For example the gender can tell whether it is beneficial to show advertisement of men or women clothing. The context in which the person is may also affect on persons interests. During the vacation a person has different preference for lunch than during working hours. This is also something that could be taken into account (Jäppinen, 2006). Further research is required to find out other dependencies.
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The data transmitted currently can be thought insensitive and non-identifying. When more data is added and transmitted the customer privacy will become more of an issue. Further research is required to find out how much information about customers can be sent without providing so much data that a person can be identified. Furthermore automatic authentication of the advertisement services should be considered to protect customers against possible identity thieves and profilers. For example in Mobile electronic personality the data is ranked with a value stating how sensitive it is and services are divided in categories to define how sensitive data they can access automatically. The adequacy of such solution in case of advertising should be evaluated.
From technical point of view the model could be adopted to real use rather quickly. There are some other issues that have to be resolved. Currently there is no real business model developed on top of advertisement service. The cost for advertisers could be determined by the amount of times advertisement has been shown or by the amount of potentially interested customer. Another big question is, how the customers can be convinced to install an application in their mobile device that provides their preferences to the advertisement systems. Evaluation of the market potential and the interest of advertisers towards such a system also require research conducted by the economists.
5. CONCLUSIONS
In this paper we have described a preference-aware ubiquitous advertisement screen and its implementation. The advertisement screen is a service that provides advertisement based on the preferences of the people at the service's proximity. The preference information is fetched from the customer's mobile device using Bluetooth wireless technology. The provided service does not require any identifying information. Therefore the customers remain anonymous and their privacy is not intruded. The awareness of the service provides better customer satisfaction and shows the possible way to enhance the advertisement services of the future.
The implementation of the service showed some inadequacies on the Bluetooth wireless technology, when used in such a service. The time for finding the devices that hold the preferences was too slow, allowing the people walk by the screen before the content adaptation was accomplished. Version 1.2 of Bluetooth provides some help on the problem. Also implementation of user arrival prediction can further enhance the service performance.
While Bluetooth capability is common in mobile phones and PDA devices, it is by default turned off. Thus the devices cannot be found and the preference fetching is not possible. Due the modular architecture the preference information fetching is separated from the system, thus it is possible to add support for more than one preference provision scheme.
Besides performance enhancing the future work consists of adding more intelligence in the news provisioning. The service authentication on the mobile device side should also be researched when more data is stored in the mobile device. Finally the effects of additional features on the performance should be evaluated.
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