Distributed optical fibre sensors based on Brillouin scattering have find many applications in different application areas. In particular, there have been significant interest in BOTDA based system in recent years. The performance of such systems is often limited by signal to noise ratio of detected signal which in turn is limited by limited pump and probe power due to fibre nonlinearity and nonlocal effect. The detection speed is often limited by the need for large number of averaging and the number of pulses that can be sent over a round trip time. In this talk, work on attempting to address these issues are discussed. In particular, the use of machine learning technique such as artificial neural network(ANN) and principal component analysis(ANN) for improving measurement accuracy and measurement speed is discussed. Results obtained using coherent detection for improving noise performance as well as the use of electronic generated multicarrier probe signal with amplitude and phase detection for improving measurement speed are presented.