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CSEM Digital Journey 2019 finalist
CSEM Digital Journey 2019 finalist
To help SMEs negotiate the digital shift, CSEM has been organizing a challenge since 2018 exclusively reserved for this audience. The principle is as follows: any Swiss company with less than 250 employees already making a turnover can tap into the digital technologies of this R&D center to offer an innovation. The winner benefits from technological support from CSEM for an amount of CHF 100,000 in order to make her project a reality.
QMT was a finalist for the 2019 CSEM Digital Journey. Made up of high-level independent experts, the jury was won over by proposals from 5 companies with strong potential in fields of the future such as predictive maintenance, precision agriculture, monitoring of physiological parameters or even l early language learning. QMT is a finalist of the 2019 edition of the CSEM Digital Journey. Made up of high-level independent experts, the jury was won over by their proposals showing great potential in fields of the future such as predictive maintenance, precision agriculture, monitoring of physiological parameters or language learning. early. CSEM publication
The detailed history of 30 years of success
Our historyAutonomous and intelligent device
By relying on CSEM's expertise in high-performance intelligent vision systems, Qualimatest intends to bring a “digital guardian” to the market. This digital companion will be integrated into machines to improve industrial processes, detect and report anomalies.
The AI integrated by QMT does not replace humans but assists them. To do this, the machine takes care of repetitive, high volume tasks. Humans thus have more time and resources for value-added control and testing. The goal is to promote human work, to minimize waste and to provide elements for the continuous improvement of processes through testing and quality control.
Digital Guardian is an autonomous and intelligent device that observes very repetitive tasks, performed by a machine or by an operator. In a first phase, Digital Guardian actively learns the usual cycle of the task. When it has learned enough, it can move on to the monitoring phase where Digital Guardian can detect anomalies and provide information about the sensor and the signal that triggered the alarm. Digital Guardian is in development and we are open to partnership to have our first clients to exploit the possibilities.
