Drilling is a costly operation, especially offshore, and disturbances caused by drilling fluid influxes (kicks or loss) pose persistent challenges and operational costs during drilling process. To minimize non-productive time induced by kick/loss of circulation, drilling systems incorporate methods monitor and measure inflow and outflow of drilling fluid for early detection of kicks/losses. Coriolis flowmeters are proven to be very accurate even under difficult mud properties. However, installation and maintenance and cost of these instruments are complex and high. Thus, new exploits of technological advances such as high-performance computations (HPC), artificial intelligence (AI), low-cost sensor technologies could enable real-time data acquisition and analysis for early kick/loss detection to improve the safety and performance of oil and gas drilling process. In this study, we focus on the outflow measurement using a combination of sensors (i.e. radar and ultrasonic sensors) to remotely obtain the flowrate in an open channel with Venturi constriction.