20161209 JAWS-UG AI支部 #2 LT : Moving story of AWS/ML beginner engineer
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Transcript of 20161209 JAWS-UG AI支部 #2 LT : Moving story of AWS/ML beginner engineer
Moving story of AWS/ML
beginner engineer
Fujitsu Software Technologies
Global Knowledge Center
9 Dec. 2016
• Development / Porting
• Embedded Linux Kernel
• Wi-Fi MW/Drv for Android
• SSD firmware
Q.
Is it possible to identify indoor
location by using Wi-Fi AP
signal strength ?
Yes, it is.
• Cisco Meraki
• CSI based indoor location
• CSI : Channel State Info
and so on..
But…
• Difficult !! ( For me !! )
• You’ll need special hardware,
skill and privilege.
Cutting corners !
• Using Machine Learning
• To calculate position from AP
signals
• I’ve just started this trial since
this week.
Scenario
606
607
Let’s training!
Training!
Training Data 1
mac_001
ch_001
rssi_001
ssid_001
mac_002
ch_002
rssi_002
ssid_002
mac_003
ch_003
rssi_003
ssid_003
mac_004
ch_004
rssi_004
ssid_004
mac_005
ch_005
rssi_005
ssid_005
mac_006
ch_006
rssi_006
ssid_006
mac_007
ch_007
rssi_007
ssid_007
mac_008
ch_008
rssi_008
ssid_008
mac_009
ch_009
rssi_009
ssid_009
mac_010
ch_010
rssi_010
ssid_010
floor
84:8E:DF:ED:1B:B1
11 -19 nekiap
00:23:26:73:58:29
6 -58 FST-WIFI-NETWORK
00:23:26:73:58:2E
6 -59 00:23:26:73:58:28
6 -60 00:23:26:73:58:2F
6 -61 58:7F:66:0A:46:2E
3 -65 W01_587F660A462E
E0:18:77:70:6E:50
9 -65 fstsoumu
00:23:26:77:F9:29
1 -67 FST-WIFI-NETWORK
00:23:26:77:F9:2F
1 -68 00:23:26:77:F9:2E
1 -68 601
84:8E:DF:ED:1B:B1
11 -19 nekiap
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 601
84:8E:DF:ED:1B:B1
11 -19 nekiap
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 602
84:8E:DF:ED:1B:B1
11 -19 nekiap
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 602
84:8E:DF:ED:1B:B1
11 -19 nekiap
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 603
84:8E:DF:ED:1B:B1
11 -19 nekiap
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 603
84:8E:DF:ED:1B:B1
11 -19 nekiap
0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 603
84:8E:DF:ED:1B:B1
11 -25 nekiap
00:23:26:73:58:2F
6 -55 00:23:26:73:58:2E
6 -57 00:23:26:73:58:29
6 -58 FST-WIFI-NETWORK
E0:18:77:70:6E:50
9 -63 fstsoumu
00:23:26:73:58:28
6 -63 58:7F:66:2A:14:7B
11 -63 W01_587F662A147B
00:23:26:77:F9:29
1 -66 FST-WIFI-NETWORK
58:7F:66:0A:46:2E
3 -66 W01_587F660A462E
DC:FB:02:DD:A7:E0
10 -72 WTHDIYKETBKM-24G
604
• Just serializing the following:
• 10 Wi-Fi AP Info
• floor index <-- this is target !
Result 1
Training Data 2
• Gathered more training data.
• about 10 times more
Training Data 2
• Gathered more training data.Training 1
Result 2
Training Data 3
• Changed data structure.
84:8E:DF:ED:1B:B1 FA:8F:CA:32:CF:88 00:23:26:73:58:29 00:23:26:77:F9:29 00:23:26:77:F9:28 00:23:26:77:F9:2F 00:23:26:73:58:2E 00:23:26:73:58:28 00:23:26:73:58:2F floor-19 -44 -51 -66 -63 -65 -61 -59 -60 601-19 -46 -49 -61 -255 ・・・ -255 -61 -59 -60 601-19 -43 -50 -66 -255 -255 -51 -50 -60 601-18 -47 -47 -62 -255 -255 -60 -60 -59 601
1 data consist from about 130 AP RSSI + floor
Result 3
Result 2
Further research
• Launch an application to track location.
• Add other sensor infos as training data
• BLE beacon
• Geomagnetic field sensor
It’s extremely EASY!!
Let’s dive in !
• You can just start it without any special knowhow.
• You don’t need much money (it takes only $5, so far).
• You don’t need any special machine.
Appendix:
Result Score
Result 1
Result 2
Result 3