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After an earthquake or a building collapse, victim recovery is a challenging task. Recovery methods must include the location of victims by non-visual means; human speech is one such parameter that can be used in victim and rescue operations. In this paper, we discuss the application of a voice-detection technique for the discrimination of voice and non-voice sounds, based on frequency parameters such as flux, centroid, and roll-off of audio signals. Using the cross-validation tests based on a linear discriminant analysis model, flux and centroid individually displayed the highest success rates for all categories of test sample. By combining these two parameters, the recognition rate was improved to 78% for the signals with high background noise.

Abstract. The food industry relies on various technical processes, from storing, freezing, thawing, and packaging to logistics. With the increasing population and the equational growth in food production, it is preferred to have increased automation in the food industry to reduce human labor. To provide an automated and green solution, it is required to monitor and control food-processing steps, such as thawing. This research aims to design an ultrasound-based setup that can monitor the pre-thawing state of food. A change in the signal by 20 %–27 % for herring fish and 60.7 % for chicken soup was obtained when monitored from a frozen state to a room-temperature state. Various other sample food products were tested, and related challenges and observations are discussed.