Table 9 Comparative study of the RAIHFAD-RFE model on the Edge-IIoT dataset^43,44,45.

Method

\(\:\varvec{A}\varvec{c}\varvec{c}{\varvec{u}}_{\varvec{y}}\)

\(\:\varvec{P}\varvec{r}\varvec{e}{\varvec{c}}_{\varvec{n}}\)

\(\:\varvec{R}\varvec{e}\varvec{c}{\varvec{a}}_{\varvec{l}}\)

\(\:{\varvec{F}1}_{\varvec{S}\varvec{c}\varvec{o}\varvec{r}\varvec{e}}\)

Inference Latency (ms)

Memory Footprint (MB)

Shallow ANN

93.36

93.73

87.11

96.16

17.96

560

Isolated LSTM

98.27

93.72

88.93

89.31

19.53

1003

CNN Classifier

96.90

93.15

79.47

95.61

10.68

363

RF Method

82.51

90.31

88.04

92.22

22.91

607

SVM Model

79.23

88.07

85.79

96.24

22.52

488

DNN Algorithm

96.38

91.85

79.60

93.40

10.21

429

Inception Time

96.60

80.81

89.26

94.69

22.08

402

RAIHFAD-RFE

99.39

96.37

96.37

96.37

7.63

328