Method and system of crowd- sourced pedestrian localization

Abstract

Methods and systems of broadcasting crowd-sourced localization data from a mobile device are described. The method, executed in the processor of the mobile device, comprises localizing the mobile device by determining an estimated position of the mobile device based on fingerprint data; broadcasting, at a first broadcast power level, a localization data packet that includes the estimated position to one or more peer mobile devices; and continuing the broadcasting at one of a lower broadcast power level than the first broadcast power level and a higher broadcast power level than the first broadcast power level based on a degree of accuracy of the estimated position.

1 . A method of broadcasting crowd-sourced localization data from a mobile device, the mobile device including a processor and a memory, the method executed in the processor and comprising:
 broadcasting, at a first broadcast power level, a localization data packet that includes an estimated position of the mobile device to one or more peer mobile devices; and
 continuing the broadcasting at one of a lower broadcast power level than the first broadcast power level and a higher broadcast power level than the first broadcast power level based on a degree of accuracy of the estimated position, the degree of accuracy being defined by a confidence level determined by fusing probabilistic results of one or more concurrent location estimates of the mobile device. 
   
     
     
         2 . (canceled) 
     
     
         3 . The method of  claim 1 , wherein continuing the broadcasting comprises lowering the first broadcast power level, when it is determined that the confidence level is below a threshold confidence level and increasing the first broadcast power level when it is determined that the confidence level is above the threshold confidence level. 
     
     
         4 . The method of  claim 2  wherein the threshold confidence level indicates 60 to 90 percent probability of the estimated position being accurate. 
     
     
         5 . The method of  claim 2  wherein the lower and higher broadcast power levels range from −100 to +20 Decibel-milliwatts (dBm). 
     
     
         6 . The method of  claim 1  wherein the localization data packet comprises location coordinate information and floor number information within a pedestrian area. 
     
     
         7 . The method of  claim 1  wherein the localization data packet further comprises a preamble component, the preamble component including a company identifier associated with formatting of the localization data packet. 
     
     
         8 . The method of  claim 1  wherein the localizing is based on at least one of an orientation, a magnetic field strength and direction, a received wireless communication signal strength, a wireless connectivity indication and a barometric pressure in accordance with fingerprint data. 
     
     
         9 . The method of  claim 8  wherein the fingerprint data includes respective time-stamps whereby the orientation, the magnetic field strength and direction, the received wireless signal strength, the wireless connectivity indication and the barometric pressure are correlated in accordance with the respective time-stamps. 
     
     
         10 . The method of  claim 1  wherein the estimated position comprises a probabilistic estimate expressed as the confidence level. 
     
     
         11 . A crowd-sourced system for localizing a mobile device within a pedestrian area, the system comprising:
 a first mobile device including a processor and a memory, the memory including instructions executable in the processor of the first mobile device to:
 broadcast, at a first broadcast power level, a localization data packet that includes an estimated position of the first mobile device to one or more peer mobile devices; and 
 continue the broadcasting at one of a lower broadcast power level than the first broadcast power level and a higher broadcast power level than the first broadcast power level based on a degree of accuracy of the estimated position, the degree of accuracy being defined by a confidence level determined by fusing probabilistic results of one or more concurrent location estimates of the first mobile device; and 
   a second mobile device including a memory and a processor, the memory including instructions executable in the processor of the second mobile device to:
 during the continuation of the broadcast, receive the localization data packet at the second mobile device; and 
 localize the second mobile device using the estimated position in the localization data packet corresponding to the first mobile device. 
   
     
     
         12 . (canceled) 
     
     
         13 . The crowd-sourced system of  claim 11  continuing the broadcasting comprises lowering the first broadcast power level, when it is determined that the confidence level is below a threshold confidence level and increasing the first broadcast power level when it is determined that the confidence level is above the threshold confidence level. 
     
     
         14 . The crowd-sourced system of  claim 12  wherein the threshold confidence level indicates 60 to 90 percent probability of the estimated position being accurate. 
     
     
         15 . The crowd-sourced system of  claim 12  wherein the lower and higher broadcast power levels range from −100 to +20 Decibel-milliwatts (dBm). 
     
     
         16 . The crowd-sourced system of  claim 11  wherein the localization data packet comprises location coordinate information and floor number information within a pedestrian area. 
     
     
         17 . The crowd-sourced system of  claim 11  wherein the localization data packet further comprises a preamble component, the preamble component including a company identifier associated with formatting of the localization data packet. 
     
     
         18 . The crowd-sourced system of  claim 11  wherein the localizing is based on at least one of an orientation, a magnetic field strength and direction, a received wireless communication signal strength, a wireless connectivity indication and a barometric pressure in accordance with fingerprint data. 
     
     
         19 . The crowd-sourced system of  claim 11  wherein the fingerprint data includes respective time-stamps whereby the orientation, the magnetic field strength and direction, the received wireless signal strength, the wireless connectivity indication and the barometric pressure are correlated in accordance with the respective time-stamps. 
     
     
         20 . The crowd-sourced system of  claim 11  wherein the estimated position comprises a probabilistic estimate expressed as the confidence level. 
     
     
         21 . The method of  claim 1 , wherein the method comprises localizing the mobile device by determining the estimated position of the mobile device based on fingerprint data. 
     
     
         22 . The crowd-sourced system of  claim 11 , wherein the processor of the first mobile device is to localize the first mobile device by determining the estimated position of the mobile device based on fingerprint data.