Kutluhan Aktar / AI-driven BLE Travel Emergency Assistant Public
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Test data

Set confidence thresholds
Model variants
Test 'Unoptimized (float32)' model Test 'Quantized (int8)' model
Set the 'expected outcome' for each sample to the desired outcome to automatically score the impulse.
Sample name Expected outcome Length F1 score Result
Call_Test_0 call - 100%
Show classification Show in data acquisition
Danger_Test_2 danger - 0%
Show classification Show in data acquisition
Call_Test_2 call - 100%
Show classification Show in data acquisition
Danger_Test_1 danger - 0%
Show classification Show in data acquisition
Stolen_Test_1 stolen - 100%
Show classification Show in data acquisition
Danger_Test_0 danger - 0%
Show classification Show in data acquisition
Stolen_Test_2 stolen - 100%
Show classification Show in data acquisition
Assist_Test_2 assist - 100%
Show classification Show in data acquisition
Assist_Test_1 assist - 100%
Show classification Show in data acquisition
Assist_Test_0 assist - 100%
Show classification Show in data acquisition
Fine_Test_0 fine - 100%
Show classification Show in data acquisition
Call_Test_1 call - 0%
Show classification Show in data acquisition
Stolen_Test_0 stolen - 100%
Show classification Show in data acquisition
Fine_Test_1 fine - 100%
Show classification Show in data acquisition
Fine_Test_2 fine - 100%
Show classification Show in data acquisition

Model testing output

Results

Model version:
Accuracy
73.33%

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