A wireless electronic nose network system has been developed for monitoring and analyzing livestock farm odour. The system utilizes electronic noses (e-noses) that can measure odour compounds and environment factors such as temperature and humidity. The e-noses are deployed at various locations on the farm, and sensor signals are transmitted via a wireless communication to a central station, where the data processing and sensor fusion algorithms analyze the collected odour data, compute the odour concentration, and display the odour dispersion plume. This system would provide users with convenient odour monitoring capabilities and help the development of an effective overall odour management strategy. In addition, an adaptive neuro-fuzzy inference approach is proposed to calibrate the e-nose responses to human panelists' perception. The proposed method can handle non-numeric information and human expert knowledge in livestock farm odour models, and can adjust the parameters in a systematic manner for optimal system performance. The proposed approach has been tested against a livestock farm odour database. Several livestock farm odour models have been developed for comparative studies. The results show that the proposed approach provides a more accurate odour prediction than a typical multi-layer feedforward neural network. Furthermore, to model odour dispersion around livestock facilities, a biologically inspired odour dispersion model is proposed, and is tested using computer simulations and a livestock farm odour database. Results show that the proposed approach is effective in providing accurate modelling of odour dispersion from multiple and various types of odour sources in both static and non-static environments.