WO2010131259A2

WO2010131259A2 - A monitoring system for capturing information relating to the wireless smart device for behavioral analytics

Info

Publication number: WO2010131259A2
Application number: PCT/IN2010/000231
Authority: WO
Inventors: Mehta Kumar; Sohoni Kedar
Original assignee: Informate Mobile Intelligence Pvt. Ltd.
Priority date: 2009-04-11
Filing date: 2010-04-09
Publication date: 2010-11-18
Also published as: WO2010131259A3

Abstract

The present invention relates to a monitoring system useful in behavioral analytics comprising of (i) a wireless smart device; (ii) an application running continuously in the background on the smart device, wherein the said application captures, stores and periodically transmits information at least (a) pertaining to usage of the smart device; (b) related to the device parameters of the smart device; or (c) stored on said smart device; and (iii) processing system to process, aggregate and analyze the captured information to generate behavioral statistics.

Description

A MONITORING SYSTEM FOR CAPTURING INFORMATION RELATING TO THE WIRELESS SMART DEVICE FOR BEHAVIORAL ANALYTICS

FIELD OF THE INVENTION

The present invention relates to a smart monitoring system for capturing information relating to the wireless smart device and particularly to a system and a method of capturing information relating to the wireless smart device usage for behavioral analytics.

BACKGROUND OF THE INVENTION

With advances in hardware and software technology, devices are getting smarter very rapidly and this trend is likely to continue in the future. More and more devices will exhibit 'intelligence' as they will also have smart software or in some cases a sophisticated operating system embedded into them. Smart device is any device which has an operating system. Such devices will be able to connect to the

Internet, send/ retrieve relevant data and also carry out multiple functions. Examples of such devices are e-book, net-book, tablet PC, portable audio/video player, television, automobile, or household devices like refrigerator/ washing machine, audio/ video system etc. Capturing usage of such devices through surveys will become more and more challenging. Hence an automated system of capturing and transmitting usage data will be essential. One of the most technically advanced devices in this category is the mobile phone device Traditionally, wireless devices, particularly mobile phones, are used for basic telephony. The growth in the industry with the Internet has led to a natural convergence of the telephony with other enterprise based data applications. The telecom industry has been one of the fastest growing industries in the last decade. Specifically, the mobile telephony sector has seen tremendous growth and has dramatically changed how people communicate with each other. But its not just communication, that has been revolutionalized. The mobile handset, no doubt, allowed people to make voice calls without being confined to their homes or offices but in its earliest avatar it was a clunky device which was not very versatile in its functionality. Over the years, the mobile device itself has undergone a radical change and today's devices are not just unrecognizable vis-a-vis their oldest counterparts, they are also small mobile computers capable of doing many more things than just make or receive voice calls. The mobile phone device of today has already started triggering a fundamental shift in the way we get informed, get entertained, manage our work and social connections, shop, pay and plan our finances and also plan our travels. It's emerging as the single most influential window to the external digital world.

This shift has of course been felt the maximum in the developed world where the mobile phone penetration is almost universal. But even in the developing world, the growth has been mind-boggling. Especially in markets like India and China, the very social fabric has been altered by the advent of the mobile phone. The device has been looked at as an agent for driving social change. The mobile networks has managed to bring the country closer and made it far easier for people to communicate with each other than what was possible just a few years back.

The mobile ecosystem is also witness to new business models and new companies which are putting together new products and services to serve the needs of hyper eager customers. On the one hand we have the device manufacturers who have packed in features in a device the size of the palm of your hand, absolutely unimaginable just a few years ago. Advances in computing power and storage have only helped this development. Then we have the telecom service providers who have created the vast infrastructure to support the ever growing global mobile population which as of date stands at over 4 billion! Content creators, aggregators and publishers haven't been far behind. They have adapted their businesses to the mobile medium in order to offer a seamless brand and product experience to the users.

The application developer community too has created myriad applications to bring the most out of the mobile device. Lastly, as user eyeballs start moving to the mobile medium from other media like television, print and the fixed Internet, advertisers are taking keen notice of the developments in the industry. They are coming up with ways to reach out to their target audience and get their message across. The mobile acts not just as brand building and a reminder medium, it also can be used as a 'call to action' medium due to its interactive nature. The inclusion of GPS in the phones has also given rise to some very innovative applications based on where the user is at a given point of time and 'what's around him'. The handset industry is also quite complex with multitude of devices and operating systems running various applications. Given the size and complexity of the industry, the need for decision making tools has risen tremendously. Handset user behavior is one of the critical areas that all the stakeholders in the industry are grappling with today. It is virtually impossible to understand through traditional market research survey methods, how people use their handsets and how and what type of content they consume. At the same time it's important to understand how consumers interact with their handsets and capture their user patterns to be able to get a better idea of current usage, which can prove invaluable in designing and improving products and services. The mobile Internet has seen huge growth in the last decade and pretty much everything that is possible on the fixed Internet is now possible on the smaller screen as well. Tracking this usage is of utmost importance to understand user preferences. A significant portion of time on the phone is also spent off the network, which means one doesn't need operator network connectivity for conducting those tasks. For example listening to stored music on the phone, clicking pictures through the camera functionality, listening to FM radio, playing downloaded games and so on can be very well done without any network. As a result, this behavior is not captured by anyone unless we try to do that through a survey, which can be very cumbersome. This offline behavior can serve as a very useful pointer for understanding latent demands and designing new products and services. Competitive information is another important aspect of decision making. While it's possible for a carrier today to get behavioral data for one's own users, the competitive data is lacking.

Thus, while the wireless devices industry has made huge strides, the measurement of the industry metrics has not kept pace. There is a dire need for a product which captures how exactly people use their handsets without taxing the user through long and cumbersome surveys. The industry needs reliable third party metrics delivered in a speedy manner so that business decisions can be more accurate and efficient. The handset vendors would know which phone features are being actually used and this would tremendously help in product development and optimization. The operators would get not just competitive information on network activities but would also get access to offline usage which would give pointers to further monetization and value added services. The content creators, aggregators and publishers would understand what is the content that is being consumed and by whom along with competitive analysis. This will help them in the process of creating and disseminating content in a much more effective manner. Advertisers are hungry for metrics related to media / content consumption. Behavioral metrics related to mobile would serve as a currency for deciding media plans and vehicles.

OBJECT OF THE INVENTION

The object of the present invention is to provide a system for capturing, and thereby storing and transmitting the information pertaining to smart device usage, or related to the device parameters of the smart device; and/or information stored on the smart device, particularly mobile phones.

SUMMARY OF THE INVENTION

DETAILED DESCRIPTION OF THE INVENTION

A preferred embodiment of the present invention is described with reference to the following accompanying drawings, wherein the same characters represent the same parts and wherein:

Figure 1 shows a flowchart of the process of capturing the information and processing the same using a mobile device. The present invention relates to a monitoring system useful in behavioral analytics comprising of (i) a wireless smart device; (ii) an application running continuously in the background on the smart device, wherein the said application captures, stores and periodically transmits information at least (a) pertaining to usage of the smart device; (b) related to the device parameters of the smart device; or (c) stored on said smart device; and (iii) processing system to process, aggregate and analyze the captured information to generate behavioral statistics.

With advances in hardware, devices are expected to get more and more sophisticated/ intelligent. They will have the capability to run various applications and connect to the Internet for data retrieval/ synchronization. A lot of such devices will run on open operating systems which will allow third party developers to create customized applications. This will enhance the overall utility of those devices. Smart monitoring application can be used to collect data on any such device with relevant modifications to the code. Eventually every such device is expected to have some footprint of the Internet embedded in them for seamless use. Examples of such devices would be e-book, net-book, tablet PC, portable audio/video player, television, automobile, or household devices like refrigerator/ washing machine, audio/ video system.

Referring to the figure 1, a preferred embodiment of the present invention is depicted using a mobile phone. The monitoring system comprises of a smart device (a mobile device), an application running in the background on the said device and software routines, programs or procedures to store, clean and process the data captured to generate behavioral statistics.

While running as a background process, the application keeps track of applications launched by the user in the foreground and associated features. Whenever it detects a new application, the application logs the start time and duration for which the application was launched. In addition, it tries to detect additional properties about the launched application. Information usage capturing is based on certain events occurring in the mobile device. An event as used herein is user activity on a mobile device. An event may encompass any user activity for which data can be gathered. Although information is not captured for all the generated events, rather it is captured only for those events which are prescribed as information capturing events. A new event occurs whenever a user initiates a new device activity. The following are few illustrative examples of events - launching various applications (Games, address book, calendar, Messaging, Email, Camera, Music player, Browser, Voice call), browsing a web page, communication over wireless voice or data channel, listening to music, taking pictures/ video using camera are events. It may include identification of Change in Battery strength, Bluetooth usage, Roaming status change, SIM card change.

Camera usage:

The application installed on the mobile device captures all camera usage details. Whenever user opens the camera application, the application detects the start of the camera and marks the start time of the application and also notes the total count and size of picture and video files in specified folders. It keeps monitoring whether the camera is closed by checking the current foreground application. When the application in the foreground changes, the application detects the change and calculates the total usage time, increase in count and size of picture and video files and stores the information.

Music/ Video usage:

The application captures all Music/ Video playback details. Whenever user opens the media (common term used for applications which can play music and/ or video) application, the application detects the start of it and marks the start time. It keeps monitoring whether the media application is closed by checking the current foreground application. When the application in the foreground changes the said smart application detects the change. Since all media applications are capable of running in the background, the application will not stop calculating the total usage time for the media application itself. In order to identify the currently played media file and its playback time, the application checks for file locks on all available media files in the system and uses it to mark the start time. When the file lock is released from a media file, it is considered as the end time of the song/video. Check for file locks will be done every minute. Any file which has playback duration less than a minute, it might not be detected by the application.

Information on the device: Phone book: Count of Phone book contacts can be retrieved from the logs available in the mobile device. In all postings, application would calculate the number of contacts available in the device and posts it to the server. SIM contacts cannot be retrieved from the logs. Application will post this data every 4 hours.

Messaging usage:

Messaging usages are collected using the logs available in the mobile devices. No message details are captured in the initial posting. In subsequent postings, SMS/ MMS which were sent after the installation time/ last posted time are retrieved from the logs and posted to the server and the current posting time is saved in persistent storage after the successful posting of the data.

Memory usage

Device memory & extended memory in the device are posted every 4 hours.

Cell information

In order to get the current location of the user, the application queries the nearby cellular tower using native APIs and uses that information to post data to the server. Email usage

Email usages are collected using the logs available in the mobile phone device. No email details are captured in the initial posting. In subsequent postings, emails which were sent/ received after the installation time/ last posted time are retrieved from the logs and posted to the server and the current posting time is saved in persistent storage after successful posting of the data. ,

Call usage

Calls usages are collected using the logs available in the mobile devices. No call details are posted in the initial posting. In subsequent postings, calls which were made after the installation time/ last posted time are retrieved from the logs and posted to the server and the current posting time is saved in persistent storage after successful posting of the data. This information is posted every 4 hours.

Bluetooth

When the application posts all the usage data at periodic intervals, the application fetches the current Bluetooth status and posts it to the server.

Batten When the application posts all the usage data at periodic intervals, the application fetches the current battery strength and posts it to the server.

At an appropriate time, the present invention submits such usage information to a central server which stores this information in a database. This information is further aggregated for generating business intelligence reports.

Other salient characteristics of this application are:

^■ The application is designed to be always-on and starts automatically when the phone is restarted without user intervention.

^■ The application is designed so the usage data is not lost when the phone is turned off or when there is communication failure with the central server.

^■ Automatic Internet Access Point (IAP) detection mechanism for avoiding loss of data due to selection of wrong access point by device user ■ The server side module implements sophisticated processes for maintaining accuracy of data by creating time corrections, removing duplicates and bad data.

^■ The server side module allows rapid analysis of data for providing Business Intelligence (BI) reports by aggregating data

Information capturing and transfer Though the application captures various user activities in the mobile device, it never captures any data, which would compromise user's privacy. Only usage patterns are captured and private data like text in an SMS is ignored.

Network connectivity in mobile devices can fluctuate at any time and there can be situations when the there is zero connectivity. During these situations, applications have to behave intelligently and implement a store & forward mechanism to avoid any kind of data loss. Data loss in any information would result in incorrect analytics. In order to avoid such situations, the application implements a store & forward mechanism to reduce the amount of data loss due to network issues. The application stores all collected data in persistent storage available in the mobile devices. In order to keep the storage memory utilization low in mobile devices, data will be purged once it is successfully posted to server. During network connection failures, application will skip the purging process and make it available for the subsequent postings. A critical limit (data size) has been set to the amount of data cached in mobile devices, beyond which the application will clean up the content and frees up the storage memory. This process is to avoid any issues in memory over-run/ failures while uploading data due to huge volume of data.

The information captured is collected in a file that can be transmitted via the network. The capture is almost instantaneously done for all the activities done in the device. For example, when a user accesses programs like Settings, Themes, Gallery, etc., the application captures the event immediately and stores it with timestamp along with details like the application name and the duration and the MSISDN in the persistent storage for later use. Since all aggregated data are time- stamped, server would be capable of rejecting any duplicate data posted by mobile devices. Usage aggregation happens as long as the application keeps running in the device. Accumulated data is posted to the server every 4 hours as a custom files such as XML or txt files over any wireless network such as HTTP protocol (this entire protocol, including the time may vary for some platforms/devices). Since thousands of devices would be posting data to the server, a unique identifier is embedded in each of the file to be recognized by the server. The unique identifier used here is the IMEI/ESN/UDID depending on the device and the platform on which the application runs. The application retains the collected usage data in conditions like "no data connectivity" and posts the same information during the subsequent posting cycle.

After processing, data is stored in various database tables. Data is stored in database through stored procedures.

Data Migration and data processing

After the device data is transmitted to the server data is migrated into various database stages on the central server system.

De-duplication The data is checked for duplicates since some devices are sending duplicate information due to random transmission problems. This duplication is known and is retained since for business intelligence, complete data is important. Duplicate data is accepted to avoid any data loss. Custom Stored procedures remove duplicate records periodically.

Data Cleaning

Some records are identified as idle usage of the device, which might be excess information and should be removed or flagged as 'deleted' for easy processing. Specific application records are identified in this process and marked as 'deleted'

Data Tagging

All application records are classified into categories for business intelligence reports. This process ideally is run every 24 hours and the data is transferred to production stage. Process of assigning tag to the application data records is done manually for the first instance and subsequently the process is automated. The tags are uploaded onto the server where they are used for tagging the actual data

Flattening

The term Flattening refers to collecting all linked properties of the usage data together with the categories and users information and storing it in a single record. Reporting Module (RM)

Reporting module performs behavioral analytics and generates various business intelligence reports. Reports are further categorized into Usage reports, QC reports and panelist reports.

The description of the present invention has been presented for purposes of illustration and description, and is not intended to be exhaustive or limited to the invention in the form disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiment was chosen and described in order to best explain the principles of the invention, the practical application, and to enable others of ordinary skill in the art to understand the invention for various embodiments with various modifications as are suited to the particular use contemplated.

Claims

Claims:

1. A monitoring system useful in behavioral analytics comprising of: a. a wireless smart device; b. an application running continuously in the background on said smart device, wherein said application captures, stores and periodically transmits information at least (a) pertaining to usage of said smart device; (b) related to the device parameters of said smart device; or (c) stored on said smart device; and c. processing system to process, aggregate and analyze said captured information to generate behavioral statistics.

2. A monitoring system as claimed in Claim 1, wherein said capturing and/or storing of information pertaining to usage of said smart device is initiated using at least a notification by said smart device.

3. A monitoring system as claimed in Claim 1, wherein said capturing, and/or storing information at least (i) related to the device parameters of said smart device; or (ii) stored on said smart device is initiated at periodic intervals.

4. A monitoring system as claimed in Claims 2 or 3, wherein said captured and/or stored information is transmitted at periodic intervals.

5. A monitoring system as claimed in Claim 1, wherein said processing system includes tagging, cleaning, and/or classifying said information, and converting said information into reports and/or metrics for business decision making.

6. A monitoring system as claimed in any of the aforesaid claims, wherein said smart device is a mobile phone.

7. A monitoring system as claimed in any of the aforesaid claims, wherein said smart device is an e-book, net-book, tablet PC, portable audio/video player, television, automobile, or household devices like refrigerator/ washing machine, audio/ video system.

8. A monitoring system as claimed in Claim 1, wherein said smart device includes at least a media player or camera.

9. A monitoring system as claimed in Claim 8, wherein captured information is media information including file name, time stamp and duration of media file being played on said smart device.

10. A monitoring system as claimed in Claim 9,wherein said capturing is done by checking the locked media file while said media player is running on the device.

11. A monitoring system as claimed in Claim 8, wherein captured information is camera information including pictures and size of said pictures or videos and size of video files recorded on said smart device.

12. A monitoring system as claimed in Claim 11 ,wherein said capturing is done by checking the count and size of picture and/or video files before and after the running of said camera application.

13. A monitoring system useful in behavioral analytics described herein with reference to the figures and examples accompanying the specification.