Up from the archives is this material to give the mental model....
WHALLEY: SENSOR FUSION ESSENTIALLY MAKES THE WHOLE GREATER THAN THE SUM OF THE PARTS. WHERE MULTIPLE SENSOR DATA POINTS AND INPUTS CAN BE COMBINED, THIS PROVIDES A MUCH RICHER PICTURE OF WHAT IS HAPPENING AND WHAT MUST BE ACTED UPON. THE FUSION CAN BE DATA FROM THE PHYSICAL SENSORS ON A DEVICE, AND IT CAN INCLUDE INFORMATION FROM “SOFT” SENSORS SUCH AS A CALENDAR APPOINTMENT, CONTACT LIST, EMAILS, FLIGHT INFORMATION UPDATES, ETC.
IT CAN ALSO INCLUDE DATA FROM GOOGLE MAPS REGARDING, FOR EXAMPLE, TRAFFIC CONDITIONS, WEATHER UPDATES, POLLEN COUNTS, ETC. MORE INFORMATION CAN BE COLLECTED TO MAKE A MORE INFORMED DECISION ON WHAT TO ACT ON. THE KEY IS NOT TO CONFUSE THE USER WITH TOO MUCH INFORMATION: PROVIDE JUST THE ESSENTIALS, SUCH AS LEAVE FOR THE AIRPORT 30 MINUTES EARLIER THAN PLANNED DUE TO A TRAFFIC ACCIDENT, OR DON’T RUN OUTSIDE THIS MORNING BECAUSE THE AIR QUALITY IS IN THE RED ZONE.
IT CAN ALSO INCLUDE DATA FROM GOOGLE MAPS REGARDING, FOR EXAMPLE, TRAFFIC CONDITIONS, WEATHER UPDATES, POLLEN COUNTS, ETC. MORE INFORMATION CAN BE COLLECTED TO MAKE A MORE INFORMED DECISION ON WHAT TO ACT ON. THE KEY IS NOT TO CONFUSE THE USER WITH TOO MUCH INFORMATION: PROVIDE JUST THE ESSENTIALS, SUCH AS LEAVE FOR THE AIRPORT 30 MINUTES EARLIER THAN PLANNED DUE TO A TRAFFIC ACCIDENT, OR DON’T RUN OUTSIDE THIS MORNING BECAUSE THE AIR QUALITY IS IN THE RED ZONE.
SAXE: DATA IS OF NO USE UNLESS IT IS TURNED INTO ACTIONABLE INFORMATION. SENSOR FUSION IS KEY BECAUSE IT INCREASES THE QUALITY OF THE INFORMATION TO THE POINT THAT USEFUL ACTIONS CAN BE GENERATED.
CONSIDER THE WELL-BEING CASE: 250,000 ACCELERATION MEASUREMENTS TAKEN OVER THE COURSE OF A DAY ARE TURNED INTO INFORMATION ABOUT HOW MANY STEPS YOU TOOK AND HOW MUCH DEEP SLEEP YOU GOT, ALL THROUGH FUSION. THE NEXT STEP IS BIG DATA, WHICH RELATES THE STEPS TO THE QUALITY OF SLEEP AND PROVIDES GUIDANCE ON HOW TO IMPROVE SLEEP.
INTERESTING THINGS HAPPEN AT THE INTERSECTION OF SENSOR DATA STREAMS. CONSIDER THE CASE OF A PHONE HELD UP TO AN EAR. THE ACCELEROMETER CAN TELL THAT THE PHONE IS IN THE RIGHT ORIENTATION, BUT DOESN’T KNOW IF THE PHONE IS JUST BEING HELD UP OR IS ACTUALLY AT THE EAR. THE PROXIMITY DETECTOR KNOWS IF THE PHONE IS CLOSE TO SOMETHING, BUT DOESN’T KNOW IF IT IS SIMPLY FACE DOWN ON THE TABLE OR CLOSE TO YOUR HEAD. BY FUSING THE ORIENTATION INFORMATION WITH THE PROXIMITY INFORMATION, WE CAN BE MORE CONFIDENT THAT THE PHONE IS HELD TO THE EAR, EXCEPT MAYBE IT IS IN A PURSE AT ABOUT THE RIGHT ORIENTATION AND THE PROXIMITY IS TO A BOOK IN THE PURSE. IF WE COULD FUSE THAT WITH AN IR TEMP SCAN THAT TOLD US THE PHONE WAS CLOSE TO SOMETHING AT 98.6°, THEN WE COULD BE EVEN SURER OF ITS PROXIMITY.
CONSIDER THE WELL-BEING CASE: 250,000 ACCELERATION MEASUREMENTS TAKEN OVER THE COURSE OF A DAY ARE TURNED INTO INFORMATION ABOUT HOW MANY STEPS YOU TOOK AND HOW MUCH DEEP SLEEP YOU GOT, ALL THROUGH FUSION. THE NEXT STEP IS BIG DATA, WHICH RELATES THE STEPS TO THE QUALITY OF SLEEP AND PROVIDES GUIDANCE ON HOW TO IMPROVE SLEEP.
INTERESTING THINGS HAPPEN AT THE INTERSECTION OF SENSOR DATA STREAMS. CONSIDER THE CASE OF A PHONE HELD UP TO AN EAR. THE ACCELEROMETER CAN TELL THAT THE PHONE IS IN THE RIGHT ORIENTATION, BUT DOESN’T KNOW IF THE PHONE IS JUST BEING HELD UP OR IS ACTUALLY AT THE EAR. THE PROXIMITY DETECTOR KNOWS IF THE PHONE IS CLOSE TO SOMETHING, BUT DOESN’T KNOW IF IT IS SIMPLY FACE DOWN ON THE TABLE OR CLOSE TO YOUR HEAD. BY FUSING THE ORIENTATION INFORMATION WITH THE PROXIMITY INFORMATION, WE CAN BE MORE CONFIDENT THAT THE PHONE IS HELD TO THE EAR, EXCEPT MAYBE IT IS IN A PURSE AT ABOUT THE RIGHT ORIENTATION AND THE PROXIMITY IS TO A BOOK IN THE PURSE. IF WE COULD FUSE THAT WITH AN IR TEMP SCAN THAT TOLD US THE PHONE WAS CLOSE TO SOMETHING AT 98.6°, THEN WE COULD BE EVEN SURER OF ITS PROXIMITY.
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