End-to-end effective citizen engagement via advanced analytics and sensor-based personal assistant capability (EECEASPA)

A system for providing an end-to-end citizen engagement, comprising:

• a hardware processor;
• a data model comprising a set of data types;
• the hardware processor obtaining data from a plurality of disintegrated sources from one or more of communication and social computing channels via at least one adapter communicatively coupled to the one or more of communication and the social computing channels, the plurality of disintegrated sources comprising at least a mobile device having at least one sensor sensing user activities and a mobile application deployed on the mobile device communicating with the hardware processor;
• the hardware processor refactoring and integrating the data according to the data model as data attributes of the data model;
• the hardware processor performing at least one analytics based on the data attributes stored according to the data model and input specified to the at least one analytics, the at least one analytics comprising at least a trust analytics that determines a trust metric for a campaign participant by attribute type and prior knowledge of a subject, the trust metric input to an evaluation phase to provide a different weight to a campaign response of the campaign participant;
• the hardware processor transmitting in real time at least one result computed by performing the at least one analytics and causing displaying, via the mobile application deployed on the mobile device, the at least one result comprising at least an effectiveness of a wellness program within a geographic location based on comparing the user activities comprising physical activities with anonymous aggregate data of other participants within the geographic location determined from the performing of the at least one analytics, the anonymous aggregate data aggregated as a function of the different weight associated with the campaign participant, for each of the campaign participants whose data is aggregated into the anonymous aggregate data.