How to write an MLC generation script

Fields for ARFF and UCF generation

• name: MLC-capable device name

  { "name": "LSM6DSV16X" }

• mlc_odr: MLC output rate (Hz) (see Device settings)

  { "mlc_odr": "30 Hz" }

• input_type: MLC input type (see Device settings)

  { "input_type": "accelerometer_only" }

• <input_name>**_fs**: Sensor full-scale range* (see Device settings)

  {"accelerometer_fs": "8 g" }

• <input_name>**_odr**: Sensor output data rate (Hz)* (see Device settings)

  { "accelerometer_odr": "30 Hz" }

• <ext_name>**_sensitivity**: External sensor sensitivity written as a 4-digits hex value (<ext_unit>/LSB)* (see Device settings)

  { "ext_sensitivity": "3C00" }

  Note: this value represents a half-precision floating-point number: SEEEEEFFFFFFFFFF (S: 1 sign bit; E: 5 exponent bits; F: 10 fraction bits)

• decision_tree_count: Number of decision trees (#trees) (see Device settings)

  { "decision_tree_count": 1 }

• window_length: Buffer length for features computation (#samples), choose a value between 1 and 255

  { "window_length": 60 }

• filters (optional): List of filter objects, each specifying the following fields:

  • filter_id: Unique filter name to be used as suffix to feature input field
  • filter_type: Filter type name
  • input: Filter input name in the form <input_name>_<axis_name> (see Device settings)

  {
      "filters": [
          { "filter_id": "filter_1", "filter_type": "BP", "input": "Acc_V2", "a2": "-1.66", "a3": "0.81", "gain": "0.09" },
          "..."
      ]
  }

  Note: Depending on the filter_type value, filter objects may require extra fields (see Device settings)

• features: List of feature objects, each specifying the following fields:

  • feature_name: Feature name (see Device settings)
  • input: Feature input name in the form <input_name><axis_name> to use raw input data or <input_name><axis_name>_<filter_id> to use filtered input data (see Device settings)
  • signed: Boolean flag to specify feature signedness

  {
      "features": [
          { "feature_name": "MEAN",         "input": "Acc_V2"          },
          { "feature_name": "MEAN",         "input": "Acc_V2_filter_1" },
          { "feature_name": "VARIANCE",     "input": "Acc_V2"          },
          { "feature_name": "VARIANCE",     "input": "Acc_V2_filter_1" },
          { "feature_name": "ENERGY",       "input": "Acc_V2"          },
          { "feature_name": "ENERGY",       "input": "Acc_V2_filter_1" },
          { "feature_name": "PEAK_TO_PEAK", "input": "Acc_V2"          },
          { "feature_name": "PEAK_TO_PEAK", "input": "Acc_V2_filter_1" },
          "..."
      ]
  }

  Note: Depending on the feature_name value, feature objects may require extra fields (see Device settings)

Fields for ARFF generation only

• datalogs: List of data log objects, each specifying the following fields:

  • filename: Input path of data log file
  • label: Class name (multiple logs may share the same value)

  {
      "datalogs": [
          { "filename": "path/to/workspace/data/stationary.csv", "label": "stationary" },
          { "filename": "path/to/workspace/data/walking.csv",    "label": "walking"    },
          { "filename": "path/to/workspace/data/cycling.csv",    "label": "cycling"    },
          { "filename": "path/to/workspace/data/running.csv",    "label": "running"    },
          "..."
      ]
  }

• arff: Output feature file path

  { "arff": "/path/to/workspace/features.arff" }

Fields for UCF generation only

• dectree_features (optional): An ordered list of custom feature names used by the decision trees corresponding to the hardware ones configured in the features field. Note that if not specified, it is assumed that decision trees will use feature names defined in the .arff file generated before.

  {
      "dectree_features": [
          "F1_MEAN_ACC_V2",
          "F2_MEAN_ACC_V2_FILTER_1",
          "F3_VARIANCE_ACC_V2",
          "F4_VARIANCE_ACC_V2_FILTER_1",
          "F5_ENERGY_ACC_V2",
          "F6_ENERGY_ACC_V2_FILTER_1",
          "F7_PEAK_TO_PEAK_ACC_V2",
          "F8_PEAK_TO_PEAK_ACC_V2_FILTER_1",
          "..."
      ]
  }

• dectrees: A list of decision tree objects, each specifying the following fields:

  • filename: Input file path of decision tree in Weka format
  • results: Mappings of class names to integer values
  • metaclassifier: List of metaclassifier end counter thresholds

  {
      "dectrees": [
          {
              "filename": "/path/to/workspace/dectree.txt",
              "results": [
                  { "label": "stationary", "value": 1  },
                  { "label": "walking",    "value": 4  },
                  { "label": "cycling",    "value": 8  },
                  { "label": "running",    "value": 12 },
              ],
              "metaclassifier": [ 2, 2, 2, 2 ]
          },
          "..."
      ]
  }

• ucf: Output configuration file path

  { "ucf": "/path/to/workspace/mlc_conf.ucf" }

Device settings

Depending on the specific MLC-based device, specifications and settings may vary quite a lot. In order to use the generate command and create a valid configuration for a given device, the user must be aware of the available settings to properly write the MLC generation script.

For more information on device-specific settings, please follow the link corresponding to the target MLC-based device below:

• MLC settings for ASM330LHB
• MLC settings for ASM330LHBG1
• MLC settings for ASM330LHHX
• MLC settings for ASM330LHHXG1
• MLC settings for IIS2ICLX
• MLC settings for ISM330BX
• MLC settings for ISM330DHCX
• MLC settings for LIS2DUX12
• MLC settings for LIS2DUXS12
• MLC settings for LSM6DSO32X
• MLC settings for LSM6DSOX
• MLC settings for LSM6DSRX
• MLC settings for LSM6DSV16BX
• MLC settings for LSM6DSV16X
• MLC settings for LSM6DSV32X
• MLC settings for ST1VAFE3BX
• MLC settings for ST1VAFE6AX

Complete example

{
    "datalogs": [
        { "filename": "/path/to/workspace/data/stationary.csv", "label": "stationary" },
        { "filename": "/path/to/workspace/data/walking.csv",    "label": "walking"    },
        { "filename": "/path/to/workspace/data/cycling.csv",    "label": "cycling"    },
        { "filename": "/path/to/workspace/data/running.csv",    "label": "running"    },
        "..."
    ],
    "name": "LSM6DSV16X",
    "mlc_odr": "30 Hz",
    "input_type": "accelerometer_only",
    "accelerometer_fs": "8 g",
    "accelerometer_odr": "30 Hz",
    "decision_tree_count": 1,
    "window_length": 60,
    "filters": [
        { "filter_id": "filter_1", "filter_type": "BP", "input": "Acc_V2", "a2": "-1.66", "a3": "0.81", "gain": "0.09" },
        "..."
    ],
    "features": [
        { "feature_name": "MEAN",         "input": "Acc_V2"          },
        { "feature_name": "MEAN",         "input": "Acc_V2_filter_1" },
        { "feature_name": "VARIANCE",     "input": "Acc_V2"          },
        { "feature_name": "VARIANCE",     "input": "Acc_V2_filter_1" },
        { "feature_name": "ENERGY",       "input": "Acc_V2"          },
        { "feature_name": "ENERGY",       "input": "Acc_V2_filter_1" },
        { "feature_name": "PEAK_TO_PEAK", "input": "Acc_V2"          },
        { "feature_name": "PEAK_TO_PEAK", "input": "Acc_V2_filter_1" },
        "..."
    ],
    "dectree_features": [
        "F1_MEAN_ACC_V2",
        "F2_MEAN_ACC_V2_FILTER_1",
        "F3_VARIANCE_ACC_V2",
        "F4_VARIANCE_ACC_V2_FILTER_1",
        "F5_ENERGY_ACC_V2",
        "F6_ENERGY_ACC_V2_FILTER_1",
        "F7_PEAK_TO_PEAK_ACC_V2",
        "F8_PEAK_TO_PEAK_ACC_V2_FILTER_1",
        "..."
    ],
    "dectrees": [
        {
            "filename": "/path/to/workspace/dectree.txt",
            "results": [
                { "label": "stationary", "value": 1  },
                { "label": "walking",    "value": 4  },
                { "label": "cycling",    "value": 8  },
                { "label": "running",    "value": 12 },
            ],
            "metaclassifier": [ 2, 2, 2, 2 ]
        },
        "..."
    ],
    "arff": "/path/to/workspace/features.arff",
    "ucf": "/path/to/workspace/mlc_conf.ucf"
}