The global population is increasing steadily, and will necessitate a marked increase in food production so as to support the estimated 9.1 billion people expected to exist on planet earth by 2050 . Poultry farming is an agricultural sector which plays, and will continue to contribute a significant role in realizing the envisaged food security [2, 3]. Chicken (Gallus domesticus L.) is the most domesticated poultry bird in the world, with a global number of 33 billion in 2020 . This is because they can efficiently convert feeds into eggs, feathers and meat within a short period of time. Their eggs are ranked second after milk in terms of nutritive value .
Despite the nutritional contribution of poultry, pests and diseases tend to cause enormous losses in the sector. Representative examples of respiratory diseases in poultry include Newcastle disease, bronchitis, avian influenza, infectious laryngotracheitis, Mycoplasma gallisepticum and chronic respiratory disease which affects the performance of growing broilers and layers by inducing morbidity, enteritis, diarrhea, reducing egg production, higher mortality due to respiratory infection (plaques in trachea), paralysis, suppression of immune responses and prostration of the head and the neck [6, 7].
Most of the cited diseases are highly contagious, characterized by respiratory signs such as gasping, coughing, snoring, snicking or sneezing, tracheal rales and nasal discharge [8, 9]. In the wake of industry 4.0 technologies , signal processing and machine learning algorithms have advanced in several sectors and have led to the release of innovative products [11, 12]. Speech recognition, automatic photo tagging and music recommendation engines are among the most successful [9, 13]. However, there are many other unexplored domains that could potentially be of benefit to the poultry sector . In this study, the design and assembly of a thermoacoustic system for the detection of respiratory diseases in chicken is reported for the first time.