>Lukowicz Consumer Confidence Index

>Paul Lukowicz taked in the symposium on Interaction with Smart Artifacts in Tokyo about “Large scale, context aware socio-technical systems”. As a number of other talks in our symposium he also pointed out that value of the massive amounts of data that become available by mobile sensing and crowd interaction.

Paul gave one example how such sensing data could be used. I think this is really interesting that is why I share here the Paul “Lukowicz Consumer Confidence Index” (CCIL) which is based on detecting the whereabouts of people. It assumes that we can estimate the number of people shopping at various places based on the use of their mobile devices.

Lukowicz Consumer Confidence Index

Paul Lukowicz taked in the symposium on Interaction with Smart Artifacts in Tokyo about “Large scale, context aware socio-technical systems”. As a number of other talks in our symposium he also pointed out that value of the massive amounts of data that become available by mobile sensing and crowd interaction.

Paul gave one example how such sensing data could be used. I think this is really interesting that is why I share here the Paul “Lukowicz Consumer Confidence Index” (CCIL) which is based on detecting the whereabouts of people. It assumes that we can estimate the number of people shopping at various places based on the use of their mobile devices.

Lukowicz Consumer Confidence Index

Paul Lukowicz taked in the symposium on Interaction with Smart Artifacts in Tokyo about “Large scale, context aware socio-technical systems”. As a number of other talks in our symposium he also pointed out that value of the massive amounts of data that become available by mobile sensing and crowd interaction.

Paul gave one example how such sensing data could be used. I think this is really interesting that is why I share here the Paul “Lukowicz Consumer Confidence Index” (CCIL) which is based on detecting the whereabouts of people. It assumes that we can estimate the number of people shopping at various places based on the use of their mobile devices.