The CCTVal Electronics Group has focused on scientific research and the modeling of modern industrial processes, providing solutions to complex engineering problems. It covers various fields including the control of electrical drives, telecommunications and microwave systems, and design of digital circuits and systems.
Along with their own scientific activity, the members of the Group lend support to the initiatives of other CCTVal researchers, generating synergistic alliances between science and engineering.
CCTVal Electronics Group
Research projects
Modeling of Electromagnetic Wave Propagation with Application to Wireless Telecommunications
Through scientific collaboration with Nokia's Bell Laboratories in the USA (Nokia/Bell-Labs) started in 2013, the project has aimed to characterize, through mathematical models, the propagation characteristics of radio waves in different types of urban environments, with the purpose of predicting coverage of cellular wireless networks.
As part of this research, CCTVal has manufactured various equipment using modern technology components supplied by Nokia/Bell-Labs. These developments have been widely implemented in Chile, USA, Germany and Finland to obtain the empirical data used in the formulation and validation of the models.
Model-Based Predictive Control of Grid-Connected AC Drives
Derived from research in the control of converters connected to the grid, as an enabling technology for the development of the Microgrid concept, the work on predictive controllers since 2021 is aimed at implementing in real time the optimization algorithms necessary for MPC control, involving FPGA algorithms for accelerated processing.
Hardware and firmware development for particle physics detectors
The work with FPGAs of the electronics group is also synergistic with the activities of the CCTVal's experimental particle physics group, working together to create embedded hardware for detectors. The development of an intelligent digitizer card, based on SoC, with high and flexible communication capacity, which allows it to be used autonomously from bench-top experiments, as well as integrated into the acquisition systems of large experiments, stands out.
Multimodal IoT platform integrated with robotics and artificial vision for intelligent sensing in the agro-industry
Through a scientific-technological collaboration for the development of R&D solutions for the agro-industry, since 2017 a multidisciplinary team of academics, researchers and engineers have been working together to develop an IoT platform adaptable to the different needs of the field agriculture (forestry, agriculture and aquaculture), always maintaining strong collaboration with entities and companies from the social and productive environment.
The work has been co-financed by two FONDEF projects (ID16|10114, ID19I10032): the first was aimed at developing a collaborative drone multimodal system for the automated monitoring of forest fires, achieving automation of drone navigation, georeferenced capture of images using a UAV (Unmanned Aerial Vehicle), the integration of specialized sensors for the detection of specific multispectral characteristics and a platform system capable of integrating sensor readings of different nature and purpose. The second, still underway, was based on these results, achieving to date a prototype for ROV positioning in salmon farming cages using ultrasound and supported by artificial vision techniques, neural network models (CNN) and vision algorithms. by computer for inspection processes (detection of breakages and characterization of fouling (algae attached to the cages) with precision greater than 85%, CNN models for detecting fruits for agriculture, positioning networks for harvesters using LoRa-GPS technologies and a Modular software architecture for modular data acquisition, analysis and visualization for the fields of aquaculture and fruit farming, integrating visualization of satellite images (agriculture) and 3D models (positioning of the ROV in culture cage).
Hardware and firmware development for particle physics detectors
The work with FPGAs of the electronics group is also synergistic with the activities of the CCTVal's experimental particle physics group, working together to create embedded hardware for detectors. The development of an intelligent digitizer card, based on SoC, with high and flexible communication capacity, which allows it to be used autonomously from bench-top experiments, as well as integrated into the acquisition systems of large experiments, stands out.
