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IOT

  • in IOT
  • 1 min read
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Raspberry PI with github actions runner

Overview

Figure 1 DevOps with AI

Dashboard to overview the runners

Raspberry PI 5 to enable read/write google sheet

Raspberry PI to get self-hosted runner status from github API

Raspberry PI 5 to enable camera

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sudo apt install -y python3-picamera2
sudo apt install -y python3-opencv

Refrences

  • in Data, IOT
  • 2 min read
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AIOT data collection- Part 2

This post focuses on concepts of big data before go deeper of technology.

Bigger picture of Big Data

Better service cycling from a deeper insights of data

Deeper insights of data

Deeper insights of data: Coming from evolution of data analytics service

Deeper insights of data: Coming from more automation

  • in Data, IOT
  • 2 min read
Draft

AIOT data collection

AIOT data collection

AIOT is the combination of AI and IOT. Three major steps for AIOT: data, intelligence, actions mean data collection, smart data intelligence, then actions accordingly. For data collection, IOT devices events and user behaviorial events might be collected via several approaches. Here we focus on the approaches of data collections and aggreagration.

via InfluxDB

Data collection, or IOT devices and user behaviorial events collection, can be formulated as time series or events and and stored in times series database (TSDB)

a time series or event can be in the form of

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measurement tag fields timestamp
andd an example as 
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temperature,device=device1,buidling=b1 internal=80,external=18 1443782126

influxDB is the top solution for (TSDB) as collectors, aggregators and visualizer and its block digram as below.

A showcase of IOT data collection architecture via influxDB.

A detailed pipeline for telegraf plugins: Inputs, outputs, processors plugins to process the data.

An example show how FLUX to handle the data source buckets, pipe, and forward operator, and tables.

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from(bucket:"mongo")
  |> range(start:-1h)
  |> filter(fn:(r) =>
    r._measurement == "cpu" and
    r.cpu == "cpu-total"
  )
  |> aggregateWindow(every: 1m, fn: mean)

References

  • in Data, IOT
  • 10 min read

Pytorch POC 6: WIFI Indoor Positioning

Project Map of DLC

Overview

This is still a very early stage of POC. With a pre-defined datasets, with many WIFI APP signal strengths data try to prdict the real location of the indoor room.

This might be the first POC try to define our input and output data formats.

Also, this POC also be a high level connector of several different components together since it will leaverage multi factor information to conclude a precise indoor locationing.

When it comes to localization within buildings, a distinction can be made between client-based (Active tracking) and server-based positioning ( Passive tracking + Active tracking as optional). Client-based localization enables determining the position directly on the end user's device (e. g. smartphone). In the case of server-based localization, positioning takes place on a server.

Technologies for Client-Based Indoor Positioning

Client-Based Indoor Positioning Compared: Wi-Fi vs. BLE vs. UWB vs. RFID vs. Ultrasound

Technology Accuracy Range
WIFI <15m <150m
BLE 4 <8m <75m
BLE 5.1 <1m <75m
UWB <30cm <150m
RFID Present detection only <1m

Technologies for Server-Based Indoor Positioning

Server-Based Indoor Positioning Compared: Wi-Fi vs. BLE vs. UWB vs. RFID vs. Ultrasound

Technology Accuracy Range
WIFI <15m <150m
BLE 4 <8m <75m
BLE 5.1 <1m <75m
UWB <30cm <150m
RFID Present detection only <1m
Ultrasound <4m <8m or Wall
Indoor Positioning Technology Comments
Client-Based No server setup. Use existing framework. but, low precision
Server-Based (Passive tracking only) Server only. 3-5 sec delay. Not realtime application
Server-Based (Passive+Active tracking) Need sever+client to get hybrid info for realtime & stable location info

Deeper insights of Client-Based Indoor Positioning

Indoor Positioning Use Cases

Many different use cases.

POC using find3

Git Repo Status Progress Comments
find3 status progress Family=barco
API:Devices by Loc (w 1 mins)

Get info of device='dlc2.barco.com' & family='barco' from find3 server 

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curl -s -L -XGET "http://dlc1.barco.com:8005/api/v1/location_basic/barco/dlc2.barco.com"
Get WIFI/BT SSID, BSSID, RSSID of the location and device

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curl -XGET http://dlc1.barco.com:8005/api/v1/location/barco/dlc2.barco.com

Get all devices within 1 minsfrom family='barco' from find3 server and output it as a table

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curl -s -L -XGET "http://dlc1.barco.com:8005/api/v1/by_location/barco?history=1&num_scanners=1" | jq -s '.[] | .locations | .[] |.devices' | jsoncsv -A  | mkexcel | csvcut  -d , -C 5  |csvlook --snifflimit 0  | sudo tee output.txt
Update GPS info of location 'Aris Cube' (device=dlc2.barco.com)

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curl -s -L -XPOST "http://dlc1.barco.com:8005/api/v1/gps" -H "Content-Type:application/json" --data-binary '{"f":"Barco","l":"Aris Cube","gps":{"lat":25.01290,"lon":121.46701,"alt":0}}'
Delete family=barco data (Dangersous operation!!! Warning!!!)

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 curl -s -L -XDELETE "http://dlc1.barco.com:8005/api/v1/database/barco"

Block diagram of find3

Signal strength (dBm) Expected Quality
-90 Chances of connecting are very low at this level
-80 Unreliable signal strength
-67 Reliable signal strength– the edge of what Cisco considers to be adequate to support Voice over WLAN
-55 Anything down to this level can be considered excellent signal strength.
-30 Maximum signal strength, you are probably standing right next to the access point.

A snapshot of find3 active RSSI & its BSSID, SSID on 2020/08/31 nearby dlc2.barco.com

Rssi Freq Type Algo Rate BSSID SSID
-50 2.412 GHz 802.11n 6 12 E8 D0 FC BF 18 0D ClickShare-Mobile-CX20
-52 5.825 GHz 802.11ac 7 8 04 D4 C4 D3 42 84 ASUS_Automation_5G
-72 5.825 GHz 802.11ac 7 8 E4 AA EA 58 43 93 CX-50-DEMO-RICHEN
-50 2.457 GHz 802.11n 7 12 B0 7F B9 82 03 04 NETGEAR25
-66 2.437 GHz 7 7 F0 1D 2D 5D A9 C0 Barco
-58 5.24 GHz 802.11n 6 8 28 24 FF 69 5B B7 TestRoom_CSE800_mac (5GHz)
-55 2.437 GHz 7 7 F0 1D 2D 5B 54 61 Barco Guest
-61 5.24 GHz 802.11ac 1 8 3C 91 80 84 95 07 ClickShare-HW-UniSee
-71 5.24 GHz 802.11ac 7 8 E4 AA EA 35 04 65 ClickShare-1863551994
-55 2.437 GHz 802.11n 7 12 BE 42 4F CB C3 44 TestRoom-EAP-WinServer
-46 5.785 GHz 6 8 7C 10 C9 61 97 84 TAI-QA-ASUSROG-6E_5G
-49 5.18 GHz 802.11ac 7 8 10 63 C8 97 03 9F TAI_MR08
-58 5.785 GHz 802.11ac 7 8 BC CF 4F CB C3 43 TestRoom-EAP
-63 5.18 GHz 802.11ac 6 8 3C 91 80 84 9C 5D ClickShare-1862300001
-59 5.3 GHz 7 6 F0 1D 2D 5A D5 6F Barco
-57 2.412 GHz 802.11n 7 12 D4 6E 0E 41 61 EA keroro24
-60 5.32 GHz 9 6 F0 1D 2D 5B 54 6E Barco Guest
-68 5.58 GHz 7 6 F0 1D 2D 5A D9 8D BarcoIoT
-55 5.18 GHz 802.11ac 7 8 3C 91 80 84 9C 5F TAI_MR09
-59 5.745 GHz 802.11ac 7 8 E4 AA EA 74 46 FF ClickShare-Mobile-CX50
-53 2.412 GHz 7 7 F0 1D 2D 5A D5 62 BarcoIoT
-69 5.805 GHz 802.11ac 6 8 D4 6E 0E 41 61 E9 keroro5
-62 5.24 GHz 802.11ac 7 8 F8 A2 D6 6E 09 CF TestRoom_CSE200P_mac
-58 5.785 GHz 802.11ac 7 8 BE 43 4F CB C3 45 TestRoom-EAP-WinServer
-73 5.68 GHz 7 6 F0 1D 2D 5C 27 CF
-39 2.447 GHz 802.11n 7 12 2C FD A1 CD 32 38 ASUS
-69 5.765 GHz 802.11ac 7 8 70 2E D9 42 F4 76 MAXHUB-6BF
-56 5.745 GHz 802.11ac 7 8 E4 AA EA 35 21 3F SClickShare-1863551600
-58 5.785 GHz 802.11ac 7 8 BE 43 4F CB C3 44 TestRoom-PSK2
-62 2.412 GHz 802.11n 7 12 E8 D0 FC BF 13 5F ClickShare-1862300251
-59 5.18 GHz 802.11ac 7 8 E4 AA EA 74 2C D3 ClickShare-1863553421
-60 2.452 GHz 802.11n 7 12 04 D4 C4 35 69 E8 ASUS_SQA_JessicaHsu_2.4G
-59 5.18 GHz 802.11ac 7 8 3C 91 80 84 95 D3 ClickShare-MR12
-69 2.412 GHz 1 7 F0 1D 2D 5A D9 82 BarcoIoT
-61 2.412 GHz 802.11n 7 12 BC 30 7E F1 1D 9B ClickShare Audi-1
-61 5.18 GHz 802.11ac 7 8 3C 91 80 84 97 59 ClickShare-1862300078
-60 5.32 GHz 7 6 F0 1D 2D 5B 54 6F
-78 2.437 GHz 802.11n 7 8 02 21 6A F8 2F AF DIRECT-ZWTAICLT24036msZe
-62 5.24 GHz 802.11ac 1 8 02 12 5F 17 67 2F WiCS-2100-72E
-59 2.462 GHz 802.11n 7 12 00 D0 41 DC 13 C8 myvita
-55 5.18 GHz 802.11ac 7 8 3C 91 80 84 9F 25 ClickShare-0716174986
-71 5.18 GHz 802.11ac 7 8 10 63 C8 A7 9E 23 TAI_MR04
-86 5.18 GHz 802.11ac 1 8 10 63 C8 96 FF 87 TAI_MR01
-28 2.427 GHz 802.11n 1 12 7A DA 88 B2 74 EC
-66 2.422 GHz 802.11n 7 12 BC 30 7E DD 3D FE WiPG-1000-78C
-56 5.18 GHz 802.11ac 7 8 F8 A2 D6 8D BF 8F ClickShare-1863550102
-59 5.3 GHz 7 6 F0 1D 2D 5A D5 6D BarcoIoT
-73 5.24 GHz 802.11n 7 8 D8 61 62 8B 1D EF TAI-MR06-Pingtung
-52 5.18 GHz 802.11ac 7 8 12 63 C8 14 92 3B DIRECT-BM
-83 5.68 GHz 7 6 F0 1D 2D 5A CC AE Barco Guest
-81 5.26 GHz 7 6 F0 1D 2D 5D B2 AF
-68 2.437 GHz 802.11n 7 12 BC EE 7B 7D 46 C0
-81 5.745 GHz 802.11ac 7 8 02 12 5F 17 68 8C WiCS-2100-88B
-68 5.58 GHz 7 6 F0 1D 2D 5A D9 8E Barco Guest
-55 2.437 GHz 802.11n 1 12 BE 42 4F CB C3 43 TestRoom-PSK2
-77 5.745 GHz 802.11ac 7 8 02 12 5F 17 66 66 WiCS-2100-665
-52 5.18 GHz 802.11n 7 8 28 24 FF 4D 1B FD ClickShare-1872075087
-82 5.2 GHz 802.11n 1 8 BC 30 7E D9 C3 F4 ClickShare-8000000049
-72 5.18 GHz 802.11ac 7 8 E4 AA EA 74 26 59 CX-50_Service
-71 5.18 GHz 802.11ac 7 8 E8 D0 FC BF 15 D1 Agile 01
-58 5.18 GHz 802.11ac 7 8 3C 91 80 84 95 B3 ClickShare-1862300131
-48 5.745 GHz 802.11ac 7 8 2C FD A1 CD 32 3C ASUS_5G
-47 5.18 GHz 802.11ac 6 8 E4 AA EA 58 45 8B ClickShare-1863552495
-84 5.22 GHz 802.11ac 7 8 3C 91 80 84 98 13 TAI_MR03
-69 5.18 GHz 802.11n 7 8 B8 B7 F1 01 B0 2D ClickShare-1873124000
-45 2.412 GHz 802.11n 1 12 C8 60 00 AC FB 30 ASUS-FA
-64 2.462 GHz 1 7 F0 1D 2D 5C 27 C0
-68 5.58 GHz 7 6 F0 1D 2D 5A D9 8F Barco
-54 2.412 GHz 7 7 F0 1D 2D 5A D5 61 Barco Guest
-64 5.745 GHz 802.11ac 7 8 02 12 5F 17 67 F2 WiCS-2100-LIN
-53 5.2 GHz 802.11ac 9 8 04 D4 C4 35 69 EC ASUS_SQA_JessicaHsu_5G
-64 2.462 GHz 7 7 F0 1D 2D 5C 27 C2 BarcoIoT
-59 5.18 GHz 802.11ac 7 8 F8 A2 D6 8D BF 5D ClickShare-1863550098
-81 5.745 GHz 802.11ac 7 8 02 12 5F 30 00 AC WiCS-2100-0AB
-53 2.462 GHz 802.11n 7 12 00 4E 35 1A C8 60 TAI-ClickShare-WPA2-DFS
-73 5.68 GHz 9 6 F0 1D 2D 5C 27 CD BarcoIoT
-59 5.18 GHz 802.11ac 7 8 F8 A2 D6 8D CB 39 ClickShare-1863550140
-75 5.22 GHz 802.11n 7 8 28 24 FF 5B 05 05 CSE-200-demo
-61 5.18 GHz 802.11ac 7 8 10 63 C8 BF B1 81 ClickShare-1862337967
-80 5.26 GHz 7 6 F0 1D 2D 5D B2 AE Barco Guest
-53 5.18 GHz 802.11ac 1 8 A0 40 A0 82 49 0E QA-test-5G
-51 2.412 GHz 802.11n 7 12 10 63 C8 96 F7 F3 ClickShare-T20
-60 5.32 GHz 7 6 F0 1D 2D 5B 54 6D BarcoIoT
-43 5.22 GHz 7 8 6C CD D6 F5 9D 69 HW_WIFI6E_5G
-52 2.462 GHz 802.11n 7 12 18 31 BF C5 D1 38 SQA_Balloon_24G
-82 5.68 GHz 7 6 F0 1D 2D 5A CC AF Barco
-84 5.745 GHz 802.11ac 7 8 02 12 5F 30 06 4F WiCS-2100-64E
-45 2.437 GHz 7 12 7C 10 C9 61 97 80 TAI-QA-ASUSROG-6E_2.4G
-58 5.18 GHz 802.11ac 7 8 E4 AA EA 58 43 81 ClickShare-1863552454
-75 5.5 GHz 7 6 F0 1D 2D 5D A9 CD BarcoIoT
-75 5.18 GHz 802.11ac 7 8 D8 F3 BC 54 4B 89 ClickShare-1862375851
-43 2.472 GHz 7 12 08 36 C9 2F 78 F5 TAI-QA-NetGear-2.4G
-63 2.412 GHz 802.11n 7 12 3C 91 80 84 9C 91 ClickShare-1862300102
-68 2.412 GHz 6 7 F0 1D 2D 5A D9 80 Barco
-66 2.437 GHz 7 7 F0 1D 2D 5D A9 C2 BarcoIoT
-63 5.5 GHz 802.11ac 7 8 00 4E 35 1A C8 70 TAI-ClickShare-WPA2-DFS

Live demo of find3 passive RSSI of dlc2.barco.com

live demo

PPT

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References