MOBILE TERMINAL AND METHOD FOR PROVIDING LIFE OBSERVATIONS AND A RELATED SERVER ARRANGEMENT AND METHOD WITH DATA ANALYSIS, DISTRIBUTION AND TERMINAL GUIDING

1 . A mobile terminal ( 102 , 104 , 106 ) for providing life observations, such as a smartphone, comprising a processing entity ( 220 ) for processing data, a memory ( 222 ) for storing data, a wireless transceiver ( 224 ) for wirelessly transmitting and receiving data relative to external entities, such as a communications network infrastructure, the mobile terminal further comprising

an observation logic ( 300 ), executed by said processing entity and stored in said memory, for conducting active and passive observations on events, actions and/or properties detectable relative to the mobile terminal in response to active and passive triggers, respectively, wherein each active trigger is associated with a triggering rule, such as a timing rule, for conducting a related observation, and each passive trigger is associated with a change in the observation environment, such as a certain event or action, the occurrence of which in the mobile terminal triggers conducting the observation linked to said passive trigger, and

a data handling logic ( 350 ), executed by said processing entity and stored in said memory, for storing, analysing, and aggregating observation data points of the gathered observation data to timed observation data transmissions via the wireless transceiver towards an external entity.

2 . The mobile terminal of claim 1 , configured to temporally monitor the instances of actions and/or events taking place in the mobile terminal over a time period and to define, on the basis of a detected historically substantially regularly occurred action or event, an active trigger incorporating a timer for conducting an active observation the timing of which is adjusted relative to the detected substantially regular timing of the action or event.

3 . The mobile terminal of claim 1 , wherein a passive trigger for conducting a passive observation is associated with detecting a plurality of predetermined changes in the observation environment, such as multiple instances of the same or different events or actions, optionally within a predetermined time window.

4 . The mobile terminal of claim 1 , configured to combine a first data point relative to a first observation, such as location observation, with a second data point relative to a second observation, such as a communication action observation, supplemented with a time stamp and optional further information such as temperature information.

5 . The mobile terminal of claim 1 , configured to observe at least one element selected from the group consisting of: active cell tower, all visible cell towers and their corresponding signal strengths, a call, a message, a calendar entry, application usage, camera usage, data transfer, media consumption, sound input, sound output, user input, profile change, tactile output, battery status, device status, GPS coordinates, blog entry, micro-blog entry, diary entry, a notebook entry, a phonebook operation, and temperature.

6 . The mobile terminal of claim 1 , configured to time observation data transmissions based on at least one condition selected from the group consisting of: location of the device, movement of the device, context of the device, time of day, day of week, behavioural input, and device status information.

7 . The mobile terminal of claim 1 , configured to process the observation data prior to transmission utilizing at least one technique selected from the group consisting of: outlier filtering, data conversion such as conversion from raw hexadecimal observation to the standardized XML Unicode feed, factor analysis, weighted averaging, data sorting, and matching of locally available information with a data point.

8 . The mobile terminal of claim 1 , configured to extract information, such as the frequency of occurrences of an action or an event, from a number of observations and adapt the observation logic accordingly, optionally by conducting the associated observation more or less frequently.

9 . A server arrangement ( 112 , 234 , 258 ) for analysis, distribution and control of mobile terminal-based life observations relative to a number of mobile users comprising a processing entity ( 250 ) for processing data, a memory ( 252 ) for storing data, and a communications interface ( 254 ) for transferring data,

an analytics and data processing logic ( 360 ), executed by said processing entity and stored in said memory, for obtaining triggered observation data transmissions on events, actions and/or properties relative to each mobile terminal from a plurality of mobile terminals and optionally supplementary data from a number of other external data sources, and performing analysis, said analysis comprising context and behavioural modelling, collectively applying the observation data by a plurality of mobile terminals and optional supplementary data, and

a data distribution logic ( 370 ), executed by said processing entity and stored in said memory, for guiding conducting observations in the mobile terminals by control data established on the basis of the analysis and sent towards mobile terminals via the communications interface, and optionally further providing other external entities with analysis results.

10 . The server arrangement of claim 9 , configured to apply gradual aggregation and temporal resolution adjustment for the obtained data such that the more current data is retained more granular and accurate than the older data.

11 . The server arrangement of claim 9 , configured to identify relationships between data points of the received observation data.

12 . The server arrangement of claim 9 , configured to transmit intelligent messages, such as geo-social advertisements or contextual notifications, towards mobile terminals such that upon detecting, on the basis of the received observation data, one user's presence in a predetermined location, the server arrangement is arranged to send a message, via the data distribution logic, to the mobile terminal of the user informing of an option to transmit a location-context dependent message to one or more mobile terminals of respective one or more friends located in the neighbourhood based on the observation data received from said mobile terminals of said one or more friends.

13 . The server arrangement of claim 9 , configured to model the context or user behaviour by first constructing an initial graph with nodes representing distinguishable locations or users, respectively, and the weights of the links between them indicating the associated distances or correlation coefficients, and then applying a predetermined clustering algorithm so as to group at least two nodes together to form a plurality of clusters from the nodes.

14 . The server arrangement of claim 9 , configured to identify semantic contexts, such as home or work, on the basis of a time distribution-based semantic algorithm applied for the observation data.

15 . The server arrangement of claim 9 , configured to apply, on the received observation data, at least one data mining or statistical tool selected from the group consisting of: multi-variate generalized non-linear regression, classification, linear regression, neural network, factor analysis, cluster analysis, non-parametric test and survival analysis.

16 . The server arrangement of claim 9 , configured to provide an analysis result comprising at least one element selected from the group consisting of: user location, user context, users currently in a certain location, users having used a predetermined application, such as the web browser, at least once during a predetermined time period, a list of countries a specific user has visited, the most common location for a specific user, a likelihood estimate for a particular user's location at a predetermined instant, and updated behavioural profile of a user based on the application usage patterns.

17 . The server arrangement of claim 9 , configured to determine the data for the output of the data distribution logic on the basis of at least one received query element selected from the group consisting of: user id, time, location, user status, context, and behavioural pattern.

18 . A method for providing life observations based on events, actions and/or properties detectable in a mobile device, comprising

determining ( 804 ) a number of active and passive triggers for conducting active and passive observations on events, actions and/or properties detectable relative to the device, respectively, each active trigger associated with a triggering rule, such as a timing rule, for conducting a related observation, and each passive trigger associated with a change in the observation environment, such as a certain event or action, the occurrence of which in the device triggers conducting the observation linked to said passive trigger, conducting ( 806 , 808 ) active and passive observations in the device in response to the fulfillment of corresponding triggering conditions determined by the active and passive triggers, respectively, and

storing, analysing, and aggregating observation data points of the gathered observation data to timed observation data transmissions ( 810 , 812 ) towards an external entity.

19 . A method for analysing and controlling mobile device-based life observations relative to a number of mobile users, comprising

obtaining ( 816 ) triggered observation data transmissions on events, actions and/or properties relative to each mobile device from a plurality of mobile devices and optionally supplementary data from a number of other external data sources,

performing ( 818 ) analysis, said analysis comprising context and behavioural modelling, collectively applying the observation data by the plurality of mobile devices and optional supplementary data, and

guiding ( 820 ) conducting observations in the mobile devices by control data established on the basis of the analysis and sent towards mobile devices via the communications interface, and optionally further providing other external entities with analysis results.

20 . The mobile terminal of claim 2 , wherein a passive trigger for conducting a passive observation is associated with detecting a plurality of predetermined changes in the observation environment, such as multiple instances of the same or different events or actions, optionally within a predetermined time window.