This thesis discussed the development of electronic nose (e-nose) for monitoring the atmospheric hazards in a confined space. A confined space is large enough for workers to enter and perform work. It has a limited means of entry or exit and is not designed for continuous occupancy. It can contribute towards atmospheric hazards accidents that threaten the worker safety and industry progress. The most critical atmospheric hazards are too high or low oxygen in the atmosphere or atmospheres that contain flammable or toxic gases. Current technology to monitor the atmospheric hazards is applied before entering confined spaces called pre-entry by using a gas detector. This study aims to develop an instrument to assist workers during pre-entry for atmosphere testing. E-nose is the integration between hardware and software that can identify and classify different concentrations of gases in an air sample using pattern recognition techniques. The developed instrument using specific sensor arrays which were identified based on main hazardous gasses effective value. The temperature and humidity rates are also measured. The instrument utilizes multivariate statistical analysis that is Principal Component Analysis (PCA) for discriminate the different concentrations of gases. The Support Vector Machine (SVM) and Artificial Neural Network (ANN) that is Radial Basis Function (RBF) Network are used to classify the acquired data from the air sample. This will increase the instrument capability while the portability will minimize the size and operational complexity as well as increase user friendliness. The instrument was successfully developed, tested and calibrated using fixed concentrations of gases samples. The results proved that the developed instrument is able to discriminate an air sample using PCA with total variation for 99.42%, while the classifier success rate for SVM and RBF Network indicates at 99.28% for train performance and 98.33% for test performance. This will contribute significantly to acquiring a new and alternative method of using the instrument for monitoring the atmospheric hazards in confined space. This will ensure the safety of workers during work progress in a confined space.
