[SICE-SSS202407] 「置くだけIoT」に向けたスマートセンシング / Smart Sensing Toward Put-and-Play IoT System

Presented in SICE-SSS, 函館, July 18, 2024

石田 繁巳
「置くだけIoT」に向けたスマートセンシング
計測自動制御学会スマートセンシングシステム部会 研究発表会, July 2024

https://rcl-aoyama.jp/sice-sss/sice_seminar_20240718.html

Transcript

1. IoT <ish@fun.ac.jp> July 18, 2024
2. n p 2024 @ 頻 p 2024 7 18 p July 18, 2024 2
3. IoT July 18, 2024 28
4. July 18, 2024 29
5. (?) n (?) p n IoT p IoT (?) July 18, 2024 30 Livingroom Bedroom Bath- room Wash- room Dining/Kitchen Nature Remo Switchbot Switchbot Hub Echo Flex Echo Flex Smart power strip
6. IoT (PnP IoT) n IoT July 18, 2024 31 TV 4 ( ) ( OFF)
7. July 18, 2024 32 WPS OK ( ) ( OFF) تُ٭عتم٭؜ ԛ ԛ ԛ
8. July 18, 2024 33 WPS OK ( ) ( OFF) تُ٭عتم٭؜ ԛ ԛ ԛ
9. n IoT n July 18, 2024 34
10. July 18, 2024 35
11. n p ( ) n ( ) p July 18, 2024 36
12. [zhang 19] n p n p l l n p F ( ) ≃ 89.5% July 18, 2024 37 [zhang 19] Danger-pose detection system using commodity Wi-Fi for bathroom monitoring, Sensors, 19(4) https://doi.org/10.3390/s19040884 CSI Illustration by Storyset
13. Figure 8. Experiment setup: (a) transmitter (TX), receiver (RX), and server used in our experiment, and (b) configuration of TX, RX, and bathtub. For the dangerous situation simulation, we assumed three dangerous situations as shown in Figure 9: (1) keep the lying position in a long time, (2) sink the whole body below the water surface, and (3) sink the face below the water surface. The danger-pose detection system is used to detect dangerous situations when taking a bath. Although target dangerous situations are not limited to the three simulated situations, we conducted evaluations with these three situations to demonstrate the basic performance of our system as an initial evaluation. (a) (b) (c) Figure 9. Simulated three dangerous situations: (a) steady lying position, (b) the whole body sinks below the water surface, and (c) the face sinks below the water surface. We collected CSI data at a rate of 20 Hz on channel 40 in a 5-GHz band for couple of hours on six different days during a three-month period. During the three-month period, environmental changes including location of furniture and daily objects have been occurred. Locations of transmitter and receiver might also include errors up to approximately 10 centimeters as we put transmitter and receiver on each of the six days. For not in bath, safe, and danger activities, we collected 119,324, 288,291, and 21,572 CSI data samples, respectively, in total in six days. [zhang 19] Danger-pose detection system using commodity Wi-Fi for bathroom monitoring, Sensors, 19(4) https://doi.org/10.3390/s19040884
14. [miyazaki 18][ishida 21] n p n p p p July 18, 2024 39 [miyazaki'18] Initial Attempt on Outdoor Human Detection using IEEE 802.11ac WLAN Signal, IEEE SAS [ishida 21] IEEE 802.11ac-based outdoor device-free human localization, Sensors and Materials, 33(1) CSI Illustration by Storyset
15. n p CSI : 4 p 36m2×9 p n p CSI : 4 p 30m2×11 July 18, 2024 40 WLAN AP CSI Measuring Stations CSI Monitoring Station 1 4 7 2 5 8 3 6 9 CSI Measuring Station STA1 WLAN AP CSI Monitoring Station 30m 6m 6m Label 0: no human 30m CSI Measuring Station STA3 CSI Measuring Station STA2 4.6m 4.6m 5.9m 7.0m 6.9m 6.9m 7.0m 2.3m 1 2 3 4 5 6 7 8 9 10 11 STA2 CSI Measuring Station STA1 WLAN AP CSI Monitoring Station Label 0: no human STA4 STA3 Wall Pillar
16. [uchino 20] n p p n 2 p F : 0.83 July 18, 2024 41 [uchino 20] Initial Design of Two-Stage Acoustic Vehicle Detection System for High Traffic Roads, PerVehicle, IEEE PerCom Workshop D/2 M1 M2 x O d2 d1 D/2 L ౸དྷํ޲ͷมԽΛఆࣜԽ Time t Sound delay Δt ϩόετਪఆʹΑΔ ϑΟοςΟϯά Sound Mapper Vehicle Detector M 2 M 1 Sound Retriever LPFs Out Sound Map 2441 2442 2443 2444 2445 2446 Time [s] −1.5 −1.0 −0.5 0.0 0.5 1.0 1.5 Sound Delay [ms] ֶ ੜ F஋0.83Ͱਐߦํ޲Λࣝผ͠ͳ͕Βं྆Λݕग़
17. n 4 n 60 n ⾒ 609 n p めっちゃ時間 かかりました! July 18, 2024 42 [uchino 20] Initial Design of Two-Stage Acoustic Vehicle Detection System for High Traffic Roads, PerVehicle, IEEE PerCom Workshop TP 133 132 265 FN 165 179 344 FP 81 80 161 Precision 0.62 0.62 0.62 Recall 0.45 0.42 0.44 F-measure 0.52 0.50 0.51 harmonic mean of precision and recall, which provides a comprehensive evaluation of the classifier. B. Detection Performance Table I shows the system performance, i.e., the number of TP, FN, and FP detections as well as the calculated precision, recall, and F-measure for ✓t = 1.5s. • The precision of the proposed Two-Stage Acoustic Ve- hicle Detection System is 0.76, 14 points higher than SAVeD. By resetting the detection window in the Post- Fitting block and detecting vehicles using only sound map points in the neighborhood of the estimated vehicle passing time, the amount of FP detections was reduced. • The recall of 0.53 is a 9-point improvement compared to previous work. This is due to the system’s ability to make use of all the sound map points corresponding to a given vehicle. • The F-measure of 0.63 is 12 points higher than SAVeD. The relatively low F-measures exhibited by both the Two- Stage Acoustic Vehicle Detection System and SAVeD are due to their low recall values compared to their precision values. As the number of simultaneously passing vehicles increases, the number of sound map points corresponding to a single vehicle decreases because only one point is drawn on the sound map at each time step. As a result, the S-curve becomes sparse, increasing the probability of a FN detection. • The Two-Stage Acoustic Vehicle Detection System de- Fig. 10. Proposed system F-measure as a function of passing time error margin ✓t Microphone setup location Fig. 11. System monitoring viewpoint The above results show that our Two-Stage Acoustic Vehicle Detection System is an improvement over the SAVeD in terms of vehicle detection performance. C. Passing Time Error The detection performance of our system depends strongly on the estimated passing time used in the Post-Fitting block. As described in Section IV-A, the smaller the passing time error margin ✓ts, the higher the number of FP detections. It is therefore important to examine the influence of the passing time error margin on detection performance. Figure 10 shows the F-measures for ✓t between 0.5 s and 2.0 s. The F-measure starts to increase at about ✓t = 0.6 s and stabilizes around ✓t = 1.2 s. The optimum value of ✓t corresponds to the point at which the F-measure just begins to stabilize, as a too large value of ✓t will cause the system
18. ... n IoT n p July 18, 2024 43
19. CSI IoT [ishida 22] Room-by-Room Device Grouping for Put-and- Play IoT System, IEEE Globecom 44 July 18, 2024
20. n WiFi (CSI) p èCSI (= )IoT 45 E F v v A B C D F E G A D E G B C F July 18, 2024
21. n WiFi (IEEE 802.11n, 802.11ac) p ( ) p p 46 CSI (Channel State Information) E[k] R[k] E[k] R[k] ࡶԻn H ௨৴࿏ʢνϟωϧʣ H n Hl = 2 6 6 4 h11 h12 · · · h1j h21 h22 · · · h2j · · · · · · · · · · · · hi1 hi2 · · · hij 3 7 7 5 <latexit sha1_base64="rp1Xu21+xBCNxKf1oM4LDSrS2sg=">AAACs3icdVFRS9xAEN5E22pq21MffVk8LD5dk0BRCgXBFx8VPBUuMWw2k7utm03YnRSOkB/os0/+Gzd3UdTDgYWPb775ZnYmraQw6PuPjru2/unzl41N7+vWt+8/Bts7V6asNYcxL2Wpb1JmQAoFYxQo4abSwIpUwnV6d9rlr/+DNqJUlzivIC7YVIlccIaWSgb3Z4mkf2kkIceJF6UwFaphWrN522gbrTdLmiBo6U/agbADEc9KND3zr6VR1InCZ1G4IgqXohfqQ7B0Es9OYsVJ9E6gsn5KL9JiOsPYSwZDf+Qvgq6CoAdD0sd5MniIspLXBSjkkhkzCfwKY2uLgkuwxrWBivE7NoWJhYoVYOJmsfKWHlgmo3mp7VNIF+zrioYVxsyL1CoLhjPzPteRL7mDN60wP44boaoaQfFlp7yWFEvaHZBmQgNHObeAcS3ssJTPmGYc7Zm7LQTv/7wKrsJR4I+CC3948qffxwbZI/vkkATkiJyQM3JOxoQ7v5yxc+sk7m934qZutpS6Tl+zS96EWzwBZ0nNoQ==</latexit> <latexit sha1_base64="rp1Xu21+xBCNxKf1oM4LDSrS2sg=">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</latexit> <latexit sha1_base64="rp1Xu21+xBCNxKf1oM4LDSrS2sg=">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</latexit> <latexit sha1_base64="rp1Xu21+xBCNxKf1oM4LDSrS2sg=">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</latexit> RXΞϯςφ਺ TXΞϯςφ਺ 𝑅 𝑘 = 𝐻! 𝐸 𝑘 + 𝑛 𝑙: July 18, 2024
22. n CSI p PinLoc [sen 12], PhaseFi [wang 16], DeepFi [wang 17] ➔ n p FUSIC [jiokeng 20], SpotFi [kotaru 15] ➔ July 18, 2024 47 [sen 12] You are facing the Mona Lisa: Spot localization using PHY layer information, ACM MobiSys [wang 16] CSI phase fingerprinnting for indoor localization with a deep learning approach, IEEE Internet Things J., 3(6) [wang 17] CSI-based fingerprinting for indoor localization: A deep learrning approach, IEEE Trans. Veh. Technol., 66(1) [jiokeng 20] When FTM discovered MUSIC: Accurate WiFi-based ranging in the presence of multipath, IEEE INFOCOM [kotaru 15] SpotFi: decimeter level localization using WiFi, ACM SIGCOMM CC Review
23. 48 July 18, 2024
24. July 18, 2024 49 sin ∅"# , cos ∅"# instead of ∅"# mean median max min std p2p iqr
25. July 18, 2024 50 k-means
26. n 1LDK p AP CSI dining p dining, bedroom, living Galaxy S7 edge l : 0 90cm p 10Hz 5 CSI p 51 July 18, 2024
27. n * p NH/* = NH/OP + NH/CL p */OP = NH/OP + DN/OP + LV/ OP + BD/OP July 18, 2024 52 Dataset (5 min each) Abbrv Human walking in Doors No human w/ opened doors NH/OP Opened No human w/ closed doors NH/CL Closed Dining room w/ opened doors DN/OP Dining room Opened Dining room w/ closed doors DN/CL Dining room Closed Living room w/ opened doors LV/OP Living room Opened Living room w/ closed doors LV/CL Living room Closed Bedroom w/ opened doors BD/OP Bedroom Opened Bedroom w/ closed doors BD/CL Bedroom Closed
28. n (ARI) p p −1 ≤ ARI ≤ 1 l 1 l 0 n p July 18, 2024 53 Living room Bedroom
29. 1: n Win size = 10s, 𝑁!"# = 4 n IoT n 100 ARI July 18, 2024 54 Feature */OP */CL */* sin ∅!" , cos ∅!" 𝝍𝒍𝒋 sin ∅!" , cos ∅!" 𝝍𝒍𝒋 sin ∅!" , cos ∅!" 𝝍𝒍𝒋 mean 0.10 0.40 0.44 0.01 0.44 0.35 median 0.10 0.44 0.44 0.03 0.45 0.36 max 0.47 0.39 0.41 0.43 0.44 0.39 min 0.60 0.43 0.39 0.35 0.52 0.44 std 0.69 0.89 0.34 0.81 0.63 0.93 p2p 0.69 0.83 0.52 0.76 0.81 0.89 iqr 0.45 0.85 0.28 0.87 0.36 0.93
30. 1: n Win size = 10s, 𝑁!"# = 4 n IoT n 100 ARI July 18, 2024 55 Feature */OP */CL */* sin ∅!" , cos ∅!" 𝝍𝒍𝒋 sin ∅!" , cos ∅!" 𝝍𝒍𝒋 sin ∅!" , cos ∅!" 𝝍𝒍𝒋 mean 0.10 0.40 0.44 0.01 0.44 0.35 median 0.10 0.44 0.44 0.03 0.45 0.36 max 0.47 0.39 0.41 0.43 0.44 0.39 min 0.60 0.43 0.39 0.35 0.52 0.44 std 0.69 0.89 0.34 0.81 0.63 0.93 p2p 0.69 0.83 0.52 0.76 0.81 0.89 iqr 0.45 0.85 0.28 0.87 0.36 0.93 CSI
31. 2: n IoT n 100 ARI 56 Human location ARI 0.42 Dining room 0.27 Living room 1.00 Bedroom 0.29 Anywhere 0.95 Anywhere or no where 0.95 July 18, 2024
32. [ 23] IoT IoT CSI , IEICE CS 57 July 18, 2024
33. July 18, 2024 58 1) 0.2 0.9 … 0.1 0.8 … … … … … … 0.2 0.9 … 0.1 0.8 … … … … … … <latexit sha1_base64="vYcOXklh+gWBP/5fdMQ1Vk+XYCU=">AAAB8XicbVDLSgNBEOyNr7i+oh69DIaAp7Ab4uMY8OIxgnlIsoTZyWwyZGZ2mZkVwpKv8CQoiFc/x5N/4yTZgyYWNBRV3XR3hQln2njet1PY2Nza3inuunv7B4dHpeOTto5TRWiLxDxW3RBrypmkLcMMp91EUSxCTjvh5Hbud56o0iyWD2aa0EDgkWQRI9hY6bGfaDbIav5sUCp7VW8BtE78nJQhR3NQ+uoPY5IKKg3hWOue7yUmyLAyjHA6cyv9VNMEkwke0Z6lEguqg2xx8QxVrDJEUaxsSYMWqvtrIsNC66kIbafAZqxXvbn4n9dLTXQTZEwmqaGSLBdFKUcmRvP30ZApSgyfWoKJYvZYRMZYYWJsSK5NwV/9eZ20a1X/qnp5Xy836nkeRTiDc7gAH66hAXfQhBYQEPAMr/DmaOfFeXc+lq0FJ585hT9wPn8A7eqQXQ==</latexit> 21 Subcarrier –28 std p2p iqr … Subcarrier 28 std p2p iqr <latexit sha1_base64="pgBfoqmbH3eroXVc3hDQ/7TuQ2c=">AAAB8XicbVDLSgNBEOyNr7i+oh69DIaAp7Ar8XEMePEYwTwkWcLsZDYZMzO7zMwKYclXeBIUxKuf48m/cZLsQRMLGoqqbrq7woQzbTzv2ymsrW9sbhW33Z3dvf2D0uFRS8epIrRJYh6rTog15UzSpmGG006iKBYhp+1wfDPz209UaRbLezNJaCDwULKIEWys9NBLNOtn/HHaL5W9qjcHWiV+TsqQo9EvffUGMUkFlYZwrHXX9xITZFgZRjidupVeqmmCyRgPaddSiQXVQTa/eIoqVhmgKFa2pEFz1f01kWGh9USEtlNgM9LL3kz8z+umJroOMiaT1FBJFouilCMTo9n7aMAUJYZPLMFEMXssIiOsMDE2JNem4C//vEpa51X/snpxVyvXa3keRTiBUzgDH66gDrfQgCYQEPAMr/DmaOfFeXc+Fq0FJ585hj9wPn8AnWWQ0A==</latexit> lj … Time … Time Time Subcarrier –28 Subcarrier 28 … … <latexit sha1_base64="vYcOXklh+gWBP/5fdMQ1Vk+XYCU=">AAAB8XicbVDLSgNBEOyNr7i+oh69DIaAp7Ab4uMY8OIxgnlIsoTZyWwyZGZ2mZkVwpKv8CQoiFc/x5N/4yTZgyYWNBRV3XR3hQln2njet1PY2Nza3inuunv7B4dHpeOTto5TRWiLxDxW3RBrypmkLcMMp91EUSxCTjvh5Hbud56o0iyWD2aa0EDgkWQRI9hY6bGfaDbIav5sUCp7VW8BtE78nJQhR3NQ+uoPY5IKKg3hWOue7yUmyLAyjHA6cyv9VNMEkwke0Z6lEguqg2xx8QxVrDJEUaxsSYMWqvtrIsNC66kIbafAZqxXvbn4n9dLTXQTZEwmqaGSLBdFKUcmRvP30ZApSgyfWoKJYvZYRMZYYWJsSK5NwV/9eZ20a1X/qnp5Xy836nkeRTiDc7gAH66hAXfQhBYQEPAMr/DmaOfFeXc+lq0FJ585hT9wPn8A7eqQXQ==</latexit> 21 <latexit sha1_base64="pgBfoqmbH3eroXVc3hDQ/7TuQ2c=">AAAB8XicbVDLSgNBEOyNr7i+oh69DIaAp7Ar8XEMePEYwTwkWcLsZDYZMzO7zMwKYclXeBIUxKuf48m/cZLsQRMLGoqqbrq7woQzbTzv2ymsrW9sbhW33Z3dvf2D0uFRS8epIrRJYh6rTog15UzSpmGG006iKBYhp+1wfDPz209UaRbLezNJaCDwULKIEWys9NBLNOtn/HHaL5W9qjcHWiV+TsqQo9EvffUGMUkFlYZwrHXX9xITZFgZRjidupVeqmmCyRgPaddSiQXVQTa/eIoqVhmgKFa2pEFz1f01kWGh9USEtlNgM9LL3kz8z+umJroOMiaT1FBJFouilCMTo9n7aMAUJYZPLMFEMXssIiOsMDE2JNem4C//vEpa51X/snpxVyvXa3keRTiBUzgDH66gDrfQgCYQEPAMr/DmaOfFeXc+Fq0FJ585hj9wPn8AnWWQ0A==</latexit> lj … Feature vector 2) CSI = CSI 3) 𝑁$%&
34. n CSI p CSI n p ➔CSI ➔ CSI July 18, 2024 59 … …
35. CSI July 18, 2024 60 ... Time Device 1 Device 2 ... Device n ICA ICA i ICA j Device 1 Device 2 Device n ... ... ... ... 1) CSI (ICA) 2) ICA 3) CSI
36. : 2LDK ( ) n LAN AP 1 : Buffalo WXR-5700AX7S n IoT 9 : Raspberry Pi 3A+ ( : 0 2m) n : Intel Compute Stick n 4 (40 1 30 1 10 2 ) n CSI 24 n : 60 n 500 p ARI July 18, 2024 61 Bedroom Storeroom CL BR WC CL Living Dining Kitchen AP Data Retriever IoT Devices 2 1,3 4,6 5 7 8 9 5.3m 3.5m 2.5m 4.1m ID 1 290663 2358 2 2968 0 3 198929 2357 4 268754 2880 5 0 0 6 308506 2880 7 347484 2880 8 369627 2880 9 247124 2880
37. 1. ICA ( ) 2. PCA p ICA PCA p ICA 3. p CSI ※ 𝑁$%& = 12 p >0.8 ※ July 18, 2024 62
38. : IoT n ICA 𝑁!"#$ ARI p ICA( ) 𝑁!"#$ = 1 ARI=0.943 l 𝑁1234 = 2 ARI=0.991 l 𝑁1234 ≥ 4 ARI=1.00 p PCA p 頻 Random July 18, 2024 63 0 2 4 6 8 10 Nsamp 0.7 0.8 0.9 1.0 Mean ARI ICA PCA Random 44.4%
39. n IoT IoT p CSI p 頻 n p p window p l 44.4% ARI=1.00 July 18, 2024 64
40. [joya 21] Design of room-layout estimator using smart speaker, EAI Mobiquitous [ 21] , IPSJ DICOMO 65 July 18, 2024
41. 1. 2. July 18, 2024 66
    
    
     
    
    
    
42. : n p [ 09] p [okamoto 07] p 3D [ishi 13][ribeiro 10] → July 18, 2024 67 [ 09] , , 65(10) [okamoto 07] Estimation of sound source positions using a surrounding microphone array, Acoustical Science and Technol., 28(3) [ishi 13] Using multiple microphone arrays and reflections for 3D localization of sound sources, IEEE/RSJ ICIRS [ribeiro 10] IEEE Trans. Audio, Speech, Language Process., 18(7)
43. n p l → July 18, 2024 68 
            
    
44. 1. (4 ) 2. Sound Density Map (SDM) p 3. p 4. p 5. July 18, 2024 69 Sound Mapper Data Segmentation Clustering Room Type Estimation Steering Vector Sound Data Sound Density Map Room Angle Room Type 1 2 3 4 5
45. Sound Density Map (SDM) n MUSIC [schmidt 86] July 18, 2024 70 [schmidt 86] Multiple emitter location and signal parameter estimation, Trans. Antennas Propag., 34(3) FFT Correlation Eigen Decomposition Steering Vector Sound Data Narrow-Band <latexit sha1_base64="efRuDYv9aGKtdcCs9eFFUDwJSWg=">AAACBnicZVBNS8NAEN34WeNX1GMvwVLwVJIi6rHQix6EiqYtNCFstpt26WYTdjdCCTl48594Ez2IV3+EF/+NmzaIbR8MPN6bYWZekFAipGX9aGvrG5tb25UdfXdv/+DQODruijjlCDsopjHvB1BgShh2JJEU9xOOYRRQ3Asm7cLvPWIuSMwe5DTBXgRHjIQEQakk36i6sbKL6azjuxGUYx5lt879TTvPfaNmNawZzFVil6QGSnR849sdxiiNMJOIQiEGtpVIL4NcEkRxrtfdVOAEogkc4YGiDEZYeNnsi9ysK2VohjFXxaQ5U/V/ExmMhJhGgeos7hTLXiH+eYurZHjlZYQlqcQMzTeFKTVlbBaZmEPCMZJ0qghEnKhrTTSGHCKpktNVDPby06uk22zYF43m3XmtZZWBVEAVnIIzYINL0ALXoAMcgMATeAFv4F171l61D+1z3rqmlTMnYAHa1y9DoZjJ</latexit> PMUSIC <latexit sha1_base64="JoupCU7DWhsNfSI3LnzQ4yWlQ58=">AAACAHicZVDNSsNAGNzUvxr/ouLJy2Ip1EtJiqjHQi96ECqattCGsNlu2qW7SdjdCCX04pt4Ez2IV5/Di2/jtg1i24GFYeb7+GYnSBiVyrZ/jMLa+sbmVnHb3Nnd2z+wDo9aMk4FJi6OWSw6AZKE0Yi4iipGOokgiAeMtINRY+q3n4iQNI4e1TghHkeDiIYUI6Ul3zpp+j2O1FDw7M59uG1MKqHvnPtWya7aM8BV4uSkBHI0feu7149xykmkMENSdh07UV6GhKKYkYlZ7qWSJAiP0IB0NY0QJ9LLZvknsKyVPgxjoV+k4Ew1/21kiEs55oGenGaVy95U/PMWT6nw2stolKSKRHh+KUwZVDGctgH7VBCs2FgThAXVaSEeIoGw0p2ZugZn+dOrpFWrOpfV2v1FqW7nhRTBKTgDFeCAK1AHN6AJXIBBBl7AG3g3no1X48P4nI8WjHznGCzA+PoF5j6VHA==</latexit> PMUSIC(f1) <latexit sha1_base64="td5vBxd1fIuZk86anZcdQyZPo64=">AAACAHicZVDNSsNAGNzUvxr/ouLJy2Ip1EtJiqjHQi96ECqattCGsNlu2qW7SdjdCCX04pt4Ez2IV5/Di2/jtg1i24GFYeb7+GYnSBiVyrZ/jMLa+sbmVnHb3Nnd2z+wDo9aMk4FJi6OWSw6AZKE0Yi4iipGOokgiAeMtINRY+q3n4iQNI4e1TghHkeDiIYUI6Ul3zpp+j2O1FDw7M59uG1MKqFfO/etkl21Z4CrxMlJCeRo+tZ3rx/jlJNIYYak7Dp2orwMCUUxIxOz3EslSRAeoQHpahohTqSXzfJPYFkrfRjGQr9IwZlq/tvIEJdyzAM9Oc0ql72p+OctnlLhtZfRKEkVifD8UpgyqGI4bQP2qSBYsbEmCAuq00I8RAJhpTszdQ3O8qdXSatWdS6rtfuLUt3OCymCU3AGKsABV6AObkATuACDDLyAN/BuPBuvxofxOR8tGPnOMViA8fUL58WVHQ==</latexit> PMUSIC(f2) … <latexit sha1_base64="/+Snuy+l7085NUCfV22dfL5VYck=">AAACAHicZVDLSsNAFJ3UV42vqLhyM1gKFaQkRdRlwY3LCvYBTSiT6aQdOnkwcyOU0I1/4k50IW79Djf+jZM2iLUHBg7n3Ms9c/xEcAW2/W2U1tY3NrfK2+bO7t7+gXV41FFxKilr01jEsucTxQSPWBs4CNZLJCOhL1jXn9zmfveRScXj6AGmCfNCMop4wCkBLQ2sEzckMPaDjMxqLowZkAscnA+sil2358CrxClIBRVoDawvdxjTNGQRUEGU6jt2Al5GJHAq2MysuqliCaETMmJ9TSMSMuVl8/wzXNXKEAex1C8CPFfNPxsZCZWahr6ezNOq/14u/nrLpyC48TIeJSmwiC4uBanAEOO8DTzkklEQU00IlVynxXRMJKGgOzN1Dc7/T6+STqPuXNUb95eVpl0UUkan6AzVkIOuURPdoRZqI4oy9Ixe0ZvxZLwY78bHYrRkFDvHaAnG5w9XQ5Vk</latexit> a(✓, f) <latexit sha1_base64="G66eZzL/Im+8JVIHqXdWzZD+4KI=">AAAB+3icZVDLSsNAFL3xWeMr6tLNYClUkJIUUZcFNy4r2Ae0oUymk3bo5MHMpFhC/sSd6ELc+idu/BsnbRDbHhg4nHMv98zxYs6ksu0fY2Nza3tnt7Rn7h8cHh1bJ6dtGSWC0BaJeCS6HpaUs5C2FFOcdmNBceBx2vEm97nfmVIhWRQ+qVlM3QCPQuYzgpWWBpbVD7Aae376nFX9K6QuB1bZrtlzoHXiFKQMBZoD67s/jEgS0FARjqXsOXas3BQLxQinmVnpJ5LGmEzwiPY0DXFApZvOo2eoopUh8iOhX6jQXDX/baQ4kHIWeHoyDypXvVz885ZPKf/OTVkYJ4qGZHHJTzhSEcqLQEMmKFF8pgkmgum0iIyxwETpukxdg7P66XXSrtecm1r98brcsItCSnAOF1AFB26hAQ/QhBYQmMILvMG7kRmvxofxuRjdMIqdM1iC8fULlDyTSw==</latexit> x(f, t) <latexit sha1_base64="0CB8+QoTUPZjS1c8h0NkTwrVJ2M=">AAAB9nicZVDLSsNAFL3xWeOr6tLNYCnUTUmKqMuCG5dV7APaUCbTSTt0MokzE7GEfoc70YW49WPc+DdO2iC2PTBwOOde7pnjx5wp7Tg/1tr6xubWdmHH3t3bPzgsHh23VJRIQpsk4pHs+FhRzgRtaqY57cSS4tDntO2PbzK//USlYpF40JOYeiEeChYwgrWRvF6I9cgP0vtpJTjvF0tO1ZkBrRI3JyXI0egXv3uDiCQhFZpwrFTXdWLtpVhqRjid2uVeomiMyRgPaddQgUOqvHSWeorKRhmgIJLmCY1mqv1vI8WhUpPQN5NZSrXsZeKft3hKB9deykScaCrI/FKQcKQjlHWABkxSovnEEEwkM2kRGWGJiTZN2aYGd/nTq6RVq7qX1drdRanu5IUU4BTOoAIuXEEdbqEBTSDwCC/wBu/Ws/VqfVif89E1K985gQVYX78+dJIW</latexit> R(f) <latexit sha1_base64="sfTp17xqs+gZl3DaBHMvJl+V+fc=">AAAB+nicZVDLSsNAFL3xWeOjUZdugqVQNyUpoi4LIrisYB/QhjCZTtqhk0mYmQgl9kvciS7ErZ/ixr9x0gax7YGBwzn3cs+cIGFUKsf5MTY2t7Z3dkt75v7B4VHZOj7pyDgVmLRxzGLRC5AkjHLSVlQx0ksEQVHASDeY3OZ+94kISWP+qKYJ8SI04jSkGCkt+VZ5ECE1DsLsbubzWnjhWxWn7sxhrxO3IBUo0PKt78EwxmlEuMIMSdl3nUR5GRKKYkZmZnWQSpIgPEEj0teUo4hIL5snn9lVrQztMBb6cWXPVfPfRoYiKadRoCfznHLVy8U/b/mUCm+8jPIkVYTjxaUwZbaK7bwHe0gFwYpNNUFYUJ3WxmMkEFa6LVPX4K5+ep10GnX3qt54uKw0naKQEpzBOdTAhWtowj20oA0YUniBN3g3no1X48P4XIxuGMXOKSzB+PoFL6uTGw==</latexit> En(f) <latexit sha1_base64="srK5AseOBeGGICoFciQAW47NHP8=">AAACAHicZVDNSsNAGNzUvxr/ouLJy2Ip1EtJiqjHQi96ECqattCWsNlu2qW7SdjdCCX04pt4Ez2IV5/Di2/jpg1i24GFYeb7+GbHjxmVyrZ/jMLa+sbmVnHb3Nnd2z+wDo9aMkoEJi6OWCQ6PpKE0ZC4iipGOrEgiPuMtP1xI/PbT0RIGoWPahKTPkfDkAYUI6Ulzzppej2O1Ejw9M59uG1MK4E3Pveskl21Z4CrxMlJCeRoetZ3bxDhhJNQYYak7Dp2rPopEopiRqZmuZdIEiM8RkPS1TREnMh+Oss/hWWtDGAQCf1CBWeq+W8jRVzKCff1ZJZVLnuZ+OctnlLBdT+lYZwoEuL5pSBhUEUwawMOqCBYsYkmCAuq00I8QgJhpTszdQ3O8qdXSatWdS6rtfuLUt3OCymCU3AGKsABV6AObkATuACDFLyAN/BuPBuvxofxOR8tGPnOMViA8fULPuOVVg==</latexit> PMUSIC(fk) Narrow-Band Narrow-Band Wide-Band Frequency Component Correlation Matirx Noise Eigen Vector <latexit sha1_base64="8DqL6w+rUUPnIyk5AKFSMFFWDwg=">AAAB6nicZVBNS8NAEJ3Urxq/qh69BEvBU0mKqMeCFy9CC/YD2lA220m7dLMJuxuhhP4Cb6IH8epP8uK/cdsGse2Dgcd7M8zMCxLOlHbdH6uwtb2zu1fctw8Oj45PSqdnbRWnkmKLxjyW3YAo5ExgSzPNsZtIJFHAsRNM7ud+5xmlYrF40tME/YiMBAsZJdpIzcdBqexW3QWcTeLlpAw5GoPSd38Y0zRCoSknSvU8N9F+RqRmlOPMrvRThQmhEzLCnqGCRKj8bHHpzKkYZeiEsTQltLNQ7X8TGYmUmkaB6YyIHqt1by7+eaurdHjnZ0wkqUZBl5vClDs6duZ/O0MmkWo+NYRQycy1Dh0TSag26dgmBm/96U3SrlW9m2qteV2uu3kgRbiAS7gCD26hDg/QgBZQQHiBN3i3uPVqfVify9aClc+cwwqsr1+Fio0c</latexit> M Microphones MUSIC Sound Density Map (SDM)
46. Sound Density Map (SDM) n MUSIC [schmidt 86] July 18, 2024 71 [schmidt 86] Multiple emitter location and signal parameter estimation, Trans. Antennas Propag., 34(3) FFT Correlation Eigen Decomposition Steering Vector Sound Data Narrow-Band <latexit sha1_base64="efRuDYv9aGKtdcCs9eFFUDwJSWg=">AAACBnicZVBNS8NAEN34WeNX1GMvwVLwVJIi6rHQix6EiqYtNCFstpt26WYTdjdCCTl48594Ez2IV3+EF/+NmzaIbR8MPN6bYWZekFAipGX9aGvrG5tb25UdfXdv/+DQODruijjlCDsopjHvB1BgShh2JJEU9xOOYRRQ3Asm7cLvPWIuSMwe5DTBXgRHjIQEQakk36i6sbKL6azjuxGUYx5lt879TTvPfaNmNawZzFVil6QGSnR849sdxiiNMJOIQiEGtpVIL4NcEkRxrtfdVOAEogkc4YGiDEZYeNnsi9ysK2VohjFXxaQ5U/V/ExmMhJhGgeos7hTLXiH+eYurZHjlZYQlqcQMzTeFKTVlbBaZmEPCMZJ0qghEnKhrTTSGHCKpktNVDPby06uk22zYF43m3XmtZZWBVEAVnIIzYINL0ALXoAMcgMATeAFv4F171l61D+1z3rqmlTMnYAHa1y9DoZjJ</latexit> PMUSIC <latexit sha1_base64="JoupCU7DWhsNfSI3LnzQ4yWlQ58=">AAACAHicZVDNSsNAGNzUvxr/ouLJy2Ip1EtJiqjHQi96ECqattCGsNlu2qW7SdjdCCX04pt4Ez2IV5/Di2/jtg1i24GFYeb7+GYnSBiVyrZ/jMLa+sbmVnHb3Nnd2z+wDo9aMk4FJi6OWSw6AZKE0Yi4iipGOokgiAeMtINRY+q3n4iQNI4e1TghHkeDiIYUI6Ul3zpp+j2O1FDw7M59uG1MKqHvnPtWya7aM8BV4uSkBHI0feu7149xykmkMENSdh07UV6GhKKYkYlZ7qWSJAiP0IB0NY0QJ9LLZvknsKyVPgxjoV+k4Ew1/21kiEs55oGenGaVy95U/PMWT6nw2stolKSKRHh+KUwZVDGctgH7VBCs2FgThAXVaSEeIoGw0p2ZugZn+dOrpFWrOpfV2v1FqW7nhRTBKTgDFeCAK1AHN6AJXIBBBl7AG3g3no1X48P4nI8WjHznGCzA+PoF5j6VHA==</latexit> PMUSIC(f1) <latexit sha1_base64="td5vBxd1fIuZk86anZcdQyZPo64=">AAACAHicZVDNSsNAGNzUvxr/ouLJy2Ip1EtJiqjHQi96ECqattCGsNlu2qW7SdjdCCX04pt4Ez2IV5/Di2/jtg1i24GFYeb7+GYnSBiVyrZ/jMLa+sbmVnHb3Nnd2z+wDo9aMk4FJi6OWSw6AZKE0Yi4iipGOokgiAeMtINRY+q3n4iQNI4e1TghHkeDiIYUI6Ul3zpp+j2O1FDw7M59uG1MKqFfO/etkl21Z4CrxMlJCeRo+tZ3rx/jlJNIYYak7Dp2orwMCUUxIxOz3EslSRAeoQHpahohTqSXzfJPYFkrfRjGQr9IwZlq/tvIEJdyzAM9Oc0ql72p+OctnlLhtZfRKEkVifD8UpgyqGI4bQP2qSBYsbEmCAuq00I8RAJhpTszdQ3O8qdXSatWdS6rtfuLUt3OCymCU3AGKsABV6AObkATuACDDLyAN/BuPBuvxofxOR8tGPnOMViA8fUL58WVHQ==</latexit> PMUSIC(f2) … <latexit sha1_base64="/+Snuy+l7085NUCfV22dfL5VYck=">AAACAHicZVDLSsNAFJ3UV42vqLhyM1gKFaQkRdRlwY3LCvYBTSiT6aQdOnkwcyOU0I1/4k50IW79Djf+jZM2iLUHBg7n3Ms9c/xEcAW2/W2U1tY3NrfK2+bO7t7+gXV41FFxKilr01jEsucTxQSPWBs4CNZLJCOhL1jXn9zmfveRScXj6AGmCfNCMop4wCkBLQ2sEzckMPaDjMxqLowZkAscnA+sil2358CrxClIBRVoDawvdxjTNGQRUEGU6jt2Al5GJHAq2MysuqliCaETMmJ9TSMSMuVl8/wzXNXKEAex1C8CPFfNPxsZCZWahr6ezNOq/14u/nrLpyC48TIeJSmwiC4uBanAEOO8DTzkklEQU00IlVynxXRMJKGgOzN1Dc7/T6+STqPuXNUb95eVpl0UUkan6AzVkIOuURPdoRZqI4oy9Ixe0ZvxZLwY78bHYrRkFDvHaAnG5w9XQ5Vk</latexit> a(✓, f) <latexit sha1_base64="G66eZzL/Im+8JVIHqXdWzZD+4KI=">AAAB+3icZVDLSsNAFL3xWeMr6tLNYClUkJIUUZcFNy4r2Ae0oUymk3bo5MHMpFhC/sSd6ELc+idu/BsnbRDbHhg4nHMv98zxYs6ksu0fY2Nza3tnt7Rn7h8cHh1bJ6dtGSWC0BaJeCS6HpaUs5C2FFOcdmNBceBx2vEm97nfmVIhWRQ+qVlM3QCPQuYzgpWWBpbVD7Aae376nFX9K6QuB1bZrtlzoHXiFKQMBZoD67s/jEgS0FARjqXsOXas3BQLxQinmVnpJ5LGmEzwiPY0DXFApZvOo2eoopUh8iOhX6jQXDX/baQ4kHIWeHoyDypXvVz885ZPKf/OTVkYJ4qGZHHJTzhSEcqLQEMmKFF8pgkmgum0iIyxwETpukxdg7P66XXSrtecm1r98brcsItCSnAOF1AFB26hAQ/QhBYQmMILvMG7kRmvxofxuRjdMIqdM1iC8fULlDyTSw==</latexit> x(f, t) <latexit sha1_base64="0CB8+QoTUPZjS1c8h0NkTwrVJ2M=">AAAB9nicZVDLSsNAFL3xWeOr6tLNYCnUTUmKqMuCG5dV7APaUCbTSTt0MokzE7GEfoc70YW49WPc+DdO2iC2PTBwOOde7pnjx5wp7Tg/1tr6xubWdmHH3t3bPzgsHh23VJRIQpsk4pHs+FhRzgRtaqY57cSS4tDntO2PbzK//USlYpF40JOYeiEeChYwgrWRvF6I9cgP0vtpJTjvF0tO1ZkBrRI3JyXI0egXv3uDiCQhFZpwrFTXdWLtpVhqRjid2uVeomiMyRgPaddQgUOqvHSWeorKRhmgIJLmCY1mqv1vI8WhUpPQN5NZSrXsZeKft3hKB9deykScaCrI/FKQcKQjlHWABkxSovnEEEwkM2kRGWGJiTZN2aYGd/nTq6RVq7qX1drdRanu5IUU4BTOoAIuXEEdbqEBTSDwCC/wBu/Ws/VqfVif89E1K985gQVYX78+dJIW</latexit> R(f) <latexit sha1_base64="sfTp17xqs+gZl3DaBHMvJl+V+fc=">AAAB+nicZVDLSsNAFL3xWeOjUZdugqVQNyUpoi4LIrisYB/QhjCZTtqhk0mYmQgl9kvciS7ErZ/ixr9x0gax7YGBwzn3cs+cIGFUKsf5MTY2t7Z3dkt75v7B4VHZOj7pyDgVmLRxzGLRC5AkjHLSVlQx0ksEQVHASDeY3OZ+94kISWP+qKYJ8SI04jSkGCkt+VZ5ECE1DsLsbubzWnjhWxWn7sxhrxO3IBUo0PKt78EwxmlEuMIMSdl3nUR5GRKKYkZmZnWQSpIgPEEj0teUo4hIL5snn9lVrQztMBb6cWXPVfPfRoYiKadRoCfznHLVy8U/b/mUCm+8jPIkVYTjxaUwZbaK7bwHe0gFwYpNNUFYUJ3WxmMkEFa6LVPX4K5+ep10GnX3qt54uKw0naKQEpzBOdTAhWtowj20oA0YUniBN3g3no1X48P4XIxuGMXOKSzB+PoFL6uTGw==</latexit> En(f) <latexit sha1_base64="srK5AseOBeGGICoFciQAW47NHP8=">AAACAHicZVDNSsNAGNzUvxr/ouLJy2Ip1EtJiqjHQi96ECqattCWsNlu2qW7SdjdCCX04pt4Ez2IV5/Di2/jpg1i24GFYeb7+GbHjxmVyrZ/jMLa+sbmVnHb3Nnd2z+wDo9aMkoEJi6OWCQ6PpKE0ZC4iipGOrEgiPuMtP1xI/PbT0RIGoWPahKTPkfDkAYUI6Ulzzppej2O1Ejw9M59uG1MK4E3Pveskl21Z4CrxMlJCeRoetZ3bxDhhJNQYYak7Dp2rPopEopiRqZmuZdIEiM8RkPS1TREnMh+Oss/hWWtDGAQCf1CBWeq+W8jRVzKCff1ZJZVLnuZ+OctnlLBdT+lYZwoEuL5pSBhUEUwawMOqCBYsYkmCAuq00I8QgJhpTszdQ3O8qdXSatWdS6rtfuLUt3OCymCU3AGKsABV6AObkATuACDFLyAN/BuPBuvxofxOR8tGPnOMViA8fULPuOVVg==</latexit> PMUSIC(fk) Narrow-Band Narrow-Band Wide-Band Frequency Component Correlation Matirx Noise Eigen Vector <latexit sha1_base64="8DqL6w+rUUPnIyk5AKFSMFFWDwg=">AAAB6nicZVBNS8NAEJ3Urxq/qh69BEvBU0mKqMeCFy9CC/YD2lA220m7dLMJuxuhhP4Cb6IH8epP8uK/cdsGse2Dgcd7M8zMCxLOlHbdH6uwtb2zu1fctw8Oj45PSqdnbRWnkmKLxjyW3YAo5ExgSzPNsZtIJFHAsRNM7ud+5xmlYrF40tME/YiMBAsZJdpIzcdBqexW3QWcTeLlpAw5GoPSd38Y0zRCoSknSvU8N9F+RqRmlOPMrvRThQmhEzLCnqGCRKj8bHHpzKkYZeiEsTQltLNQ7X8TGYmUmkaB6YyIHqt1by7+eaurdHjnZ0wkqUZBl5vClDs6duZ/O0MmkWo+NYRQycy1Dh0TSag26dgmBm/96U3SrlW9m2qteV2uu3kgRbiAS7gCD26hDg/QgBZQQHiBN3i3uPVqfVify9aClc+cwwqsr1+Fio0c</latexit> M Microphones MUSIC
47. : n SDM DBSCAN p SDM → OK July 18, 2024 72
48. : n p k-means l k ( ) → = July 18, 2024 73 OK
49. n p Random Forest July 18, 2024 74 [ 11] ActivityAnalyzer, ([ 11] ) MFCC Room 2 Room 1 Windowing RFC MUSIC =1 OK
50. n p AZDEN SGM-990 x4 , Behringer UMC404HD p 5cm, 70cm p 16bit@44.1kHz July 18, 2024 75 
        Kitchen Bedroom Living Room Washroom Bathroom Microphones 270cm 350cm 258cm 258cm 350cm 166cm ( 40 ×20) 1: A 2: B DS (10 ) (10 ) (10 ) (10 ) DS DS DS
51. 1: n p ARI( ) n p July 18, 2024 76 Kitchen Bedroom Living Room Washroom Bathroom Microphones 270cm 350cm 258cm 258cm 350cm 166cm ARI DS 0.897 0.783 DS 0.327 0.683 DS 0.746 0.967 DS 0.925 0.967 全データ 0.725 0.850 3
52. 2: n p 3 p 120 @ n p 1 p 30 @ July 18, 2024 77 , ( , ), , , , , , , , 学習データに含まれる⾏動 規定⾏動 , , , ⾃由⾏動 living kitchen bedroom Predicted Class living kitchen bedroom Actual Class 0.867 0.133 0.000 0.133 0.867 0.000 0.000 1.000 0.000 living kitchen bedroom Predicted Class living kitchen bedroom Actual Class 0.736 0.264 0.000 0.250 0.750 0.000 0.000 0.361 0.639 0.714
53. n IoT p p p n p : ARI=0.725 p : 0.850 p : 0.714 July 18, 2024 78
54. 79 July 18, 2024
55. n IoT p IoT p IoT p n p CSI IoT p n p : ish@fun.ac.jp p Web: https://pman0214.netlify.app/ July 18, 2024 80
56. © 2024 Shigemi ISHIDA, distributed under CC BY-NC 4.0