Configure your scale with Zepp Life App on your mobile device (tested on Android 10-13);
Retrieve scale's MAC Address from Zepp Life App (Profile > My devices > Mi Body Composition Scale 2);
Turn off weigh small object in Zepp Life App (Profile > My devices > Mi Body Composition Scale 2) for better measurement quality:
3. Setting correct date and time in Mi Body Composition Scale 2
Launch Zepp Life App, go to scale (Profile > My devices > Mi Body Composition Scale 2);
Start scale and select Clear data in App;
Take a new weight measurement with App, App should synchronize date and time (UTC);
Script import_data.sh detects time zone and includes this as a time offset;
If time is still not synchronized correctly, check NTP synchronization on server or change time offset in import_data.sh file (offset parameter);
You should also synchronize scale after replacing batteries;
Script import_data.sh detects same weighing done in less than 30 seconds (protection against duplicates);
Script import_data.sh have time difference detection of more than 20 minutes (between scale data and os).
4. BLE VERSION
4.1. How does this work?
After weighing, Mi Body Composition Scale 2 is active for 15 minutes on bluetooth transmission;
USB bluetooth adapter or internal module (tested with bluetooth versions 4.0/4.1 and 5.0/5.1/5.3) scans for BLE device every 1 minute for 10 seconds and queries scale for data;
Body weight and impedance data on server are appropriately processed by scripts;
Processed data are sent by program bodycomposition to Garmin Connect;
Raw and calculated data from scale is backed up on server in backup.csv file;
backup.csv file can be imported e.g. for analysis into Excel.
Download and extract to your home directory (e.g. "/home/robert/"), make a files executable, choose correct version of boodycomposition depending on your operating system:
Raspberry Pi OS (ARM, 32-bit) use _Linux_armv6.tar.gz
Raspberry Pi OS (ARM, 64-bit) use _Linux_arm64.tar.gz
Debian (x86, 32-bit) use _Linux_i386.tar.gz
Debian (x86, 64-bit) use _Linux_x86_64.tar.gz
wget https://github.com/RobertWojtowicz/miscale2garmin/archive/refs/tags/5.tar.gz -O - | tar -xz
cd miscale2garmin-5
wget https://github.com/davidkroell/bodycomposition/releases/download/v1.7.0/bodycomposition_1.7.0_Linux_x86_64.tar.gz -O - | tar -xz bodycomposition
sudo chmod +x bodycomposition import_data.sh scanner_ble.py export_garmin.py
sudo setcap 'cap_net_raw,cap_net_admin+eip' /usr/local/lib/python3.9/dist-packages/bluepy/bluepy-helper
4.3. Configuring scripts
First script is "scanner_ble.py", you need to complete data: "scale_mac_addr", which is related to MAC address of scale;
If you have multiple BLE devices, check which device should scan scale with command sudo hcitool dev and set hci_num parameter in "scanner_ble.py" script;
Script "scanner_ble.py" has implemented debug mode, you can verify if everything is working properly, just execute it from console:
$ python3 /home/robert/miscale2garmin-5/scanner_ble.py
Mi Body Composition Scale 2 Garmin Connect v5.3 (scanner_ble.py)
* Starting BLE scan:
BLE device found with address: 3f:f1:3e:a6:4d:00, non-target device
BLE device found with address: 42:db:e4:c4:5c:d4, non-target device
BLE device found with address: 24:fc:e5:8f:ce:bf, non-target device
BLE device found with address: 00:00:00:00:00:00 <= target device
* Reading BLE data complete, finished BLE scan
1672412076;58.4;521
Second script is "export_garmin.py", you must complete data in "users" section: sex, height in cm, birthdate in dd-mm-yyyy, email and password to Garmin Connect, max_weight in kg, min_weight in kg;
Script "export_garmin.py" supports multiple users with individual weights ranges, we can link multiple accounts with Garmin Connect;
Script "import_data.sh" has implemented debug mode, you can verify if everything is working properly, just execute it from console:
$ /home/robert/miscale2garmin-5/import_data.sh
Mi Body Composition Scale 2 Garmin Connect v5.5 (import_data.sh)
* backup.csv file exists, check if temp.log exists
* temp.log file exists, checking for new data
* Importing data from a BLE scanner
* Saving import 1672412076 to backup.csv file
* Calculating data from import 1672412076, upload to Garmin Connect
* Data upload to Garmin Connect is complete
* Saving calculated data from import 1672412076 to backup.csv file
If there is an error upload to Garmin Connect, data will be sent again on next execution, upload errors and other operations are saved in temp.log file:
Purchase a cheap USB bluetooth 5.0/5.1 adapter with external antenna (tested on RTL8761B chipset, manufacturer Zexmte);
Bluetooth adapter should have a removable RP-SMA antenna;
You will have option to change if standard RP-SMA antenna included with bluetooth adapter gives too little range;
Sometimes if you increase antenna range, scan time is too short to find your scale (too many devices around), you should increase scan_time parameter in scanner_ble.py script;
After weighing, Mi Body Composition Scale 2 is active for 15 minutes on bluetooth transmission;
ESP32 module operates in a deep sleep and wakes up every 7 minutes, scans for BLE device for 10 seconds and queries scale for data, process can be started immediately via reset button;
ESP32 module sends acquired data via MQTT protocol to MQTT broker installed on server;
Body weight and impedance data on server are appropriately processed by scripts;
Processed data are sent by program bodycomposition to Garmin Connect;
Raw and calculated data from scale is backed up on server in backup.csv file;
backup.csv file can be imported e.g. for analysis into Excel.
6.2. ESP32 configuration (bluetooth gateway to WiFi/MQTT)
Use Arduino IDE to compile and upload software to ESP32, following board and libraries required:
Project is prepared to work with ESP32 board with charging module (red LED indicates charging). I based my version on Li-ion 18650 battery;
Program for ESP32 has implemented UART debug mode (baud rate must be set to 115200), you can verify if everything is working properly:
Mi Body Composition Scale 2 Garmin Connect v5.3 (esp32.ino)
* Starting BLE scan:
BLE device found with address: 3f:f1:3e:a6:4d:00, non-target device
BLE device found with address: 42:db:e4:c4:5c:d4, non-target device
BLE device found with address: 24:fc:e5:8f:ce:bf, non-target device
BLE device found with address: 00:00:00:00:00:00 <= target device
* Reading BLE data complete, finished BLE scan
* Connecting to WiFi: connected
IP address: 192.168.4.18
* Connecting to MQTT: connected
* Publishing MQTT data: 1672412076;58.4;521;3.5;5
* Waiting for next scan, going to sleep
After switching device on, blue LED will light up for a moment to indicate that module has started successfully;
If data are acquired correctly in next step, blue LED will flash for a moment 2 times;
If there is an error, e.g. data is incomplete, no connection to WiFi network or MQTT broker, blue LED will light up for 5 seconds;
Program implements voltage measurement and battery level, which are sent toger with scale data in topic MQTT;
Device has 2 buttons, first green is reset button (monostable), red is battery power switch (bistable);
Sample photo of finished module with ESP32 (Wemos LOLIN D32 Pro) and Li-ion 18650 battery (LG 3600mAh, LGDBM361865):
6.3. Preparing operating system
Minimum hardware and software requirements are: 1CPU, 512MB RAM, 2GB disk space, network connection, Raspberry Pi OS or Debian operating system;
Update your system and then install following modules:
Download and extract to your home directory (e.g. "/home/robert/"), make a files executable, choose correct version of boodycomposition depending on your operating system:
Raspberry Pi OS (ARM, 32-bit) use _Linux_armv6.tar.gz
Raspberry Pi OS (ARM, 64-bit) use _Linux_arm64.tar.gz
Debian (x86, 32-bit) use _Linux_i386.tar.gz
Debian (x86, 64-bit) use _Linux_x86_64.tar.gz
wget https://github.com/RobertWojtowicz/miscale2garmin/archive/refs/tags/5.tar.gz -O - | tar -xz
cd miscale2garmin-5
wget https://github.com/davidkroell/bodycomposition/releases/download/v1.7.0/bodycomposition_1.7.0_Linux_x86_64.tar.gz -O - | tar -xz bodycomposition
sudo chmod +x bodycomposition import_data.sh export_garmin.py
6.4. Configuring scripts
First script is "import_data.sh", you need to complete data: "user", "password" which are related to MQTT broker, "mqtt" set to "on";
Second script is "export_garmin.py", you must complete data in "users" section: "sex", "height" in cm, "birthdate" in dd-mm-yyyy, "email" and "password" to Garmin Connect, "max_weight" in kg, "min_weight" in kg;
Script "export_garmin.py" supports multiple users with individual weights ranges, we can link multiple accounts with Garmin Connect;
Script "import_data.sh" has implemented debug mode, you can verify if everything is working properly, just execute it from console:
$ /home/robert/miscale2garmin-5/import_data.sh
Mi Body Composition Scale 2 Garmin Connect v5.5 (import_data.sh)
* backup.csv file exists, check if temp.log exists
* temp.log file exists, checking for new data
* Importing data from an MQTT broker
* Saving import 1672412076 to backup.csv file
* Calculating data from import 1672412076, upload to Garmin Connect
* Data upload to Garmin Connect is complete
* Saving calculated data from import 1672412076 to backup.csv file
If there is an error upload to Garmin Connect, data will be sent again on next execution, upload errors and other operations are saved in temp.log file:
