Sensors form the basis for the distribution Internet of Things in electricity, especially the distributed optical fiber sensors based on Brillouin scattering are widely used in this field. To improve the measurement speed of distributed optical fiber sensing based on Brillouin scattering and to lay the foundation for the condition sensing of electrical equipment based on temperature, the adaptability of the optical fiber temperature measurement method based on the slope-assisted technique is investigated. The computer programs of the spectral fitting method and the slope-assisted technique based on the pseudo-Voigt model are written. The temperature along the optical fiber for the Brillouin spectra with different signal-to-noise ratios (SNRs) are estimated by the above spectral fitting method and the slope-assisted technique. Results reveal that within a certain signal-to-noise ratio and BFS fluctuation range along the optical fiber, the accuracy of the slope-assisted technique is close to that of the spectral fitting method. However, the spectrum measurement time of the former can be shortened to a few tenth of the latter, and the corresponding computation time is only 1/758 of the latter. The influence of SNR and BFS on the error is studied. Results show that the temperature error decreases rapidly with SNR (in dB), and then it gradually tends to a stable value. The temperature error increases with the difference between the Brillouin frequency shift and the working point, and the accelerated speed also increases with the difference. The temperature error increases with the linewidth error.