The objective of this project was to obtain a predictive maintenance system that, applying the new technologies in sensors and information processing, would improve the productivity of wind turbines in the North Sea.
The system consists of a hardware part based on a data acquisition card to which twelve piezoelectric sensors are connected. The signals of the sensors are processed by a central processing unit that, through algorithms (machine learning), detect the malfunction of one of the six shafts of the wind turbine.

It is a project in operation in which the temperature measurement is communicated to the company's own cloud, through the Sigfox communication protocol. This protocol consists of using narrow spectrum channels to reach large distances with a minimum energy requirement.
The device has an electrovalve connected, which is activated and deactivated from the platform that the company uses, offering control over the installation of the water. In order to control the flow of water and as a safety measure, after the solenoid valve, a flow meter has been introduced that sends reports with the same frequency as the temperature measurements.

With the aim of providing a solution to the detection of irregularities in the production line, a sensorization system was installed with an RGB camera for the automatic recognition of the correct filling of the product boxes. Once designed and installed it and after the different test cases, the alert system was configured based on a web interface accessible from any point of the factory.
With a period of approximately 7 months the rate of return of pallets had fallen by 60%.

In this project, a tracking device was installed to commercial vehicles at the entrance of the country to control their route. When a commercial vehicle leaves the country the device is withdrawn and the process proceeds with the payment of the distance traveled since the last payment made. This device is able to maintain a communication with a beacon DSRC that is used among other applications to know the exact location of the vehicle when it is traveling on multi-level roads (superimposed roads).

For the study of animal behavior in response to different stimuli, a sensorization device was created. This device allowed the extraction of information from the impulses generated by connecting neuronal sensors (64 electrodes) into the cerebral cortex.
In this project, a PCB design was created which, due to its characteristics of size and number of layers, belongs to the group of the most complicated plates.

For this project the requirement was to have a predictive maintenance system on elevators sensing voltage, current and acceleration. From the data obtained from the acceleration sensor, the elevator could be located between the different floors, applying algorithms based on the Fourier transform. On the other hand, by means of a clamp sensor based on the principle of the hall effect accompanied by the voltage data, it was possible to obtain consumption of both the movement of the cabin and the activity of the electric doors and possible anomalies.