A5091947230- IoT and Edge/Fog Computing
- Structural Health Monitoring Techniques
- CCD and CMOS Imaging Sensors
- Digital Transformation in Industry
- Radiation Detection and Scintillator Technologies
- Particle Detector Development and Performance
- Infrastructure Maintenance and Monitoring
- Water Quality Monitoring Technologies
- Advanced Fiber Optic Sensors
- Smart Agriculture and AI
- Industrial Automation and Control Systems
- Concrete Corrosion and Durability
- Electrical and Bioimpedance Tomography
Universidad de Sevilla
2023-2024
A complete low-power, low-cost and wireless solution for bridge structural health monitoring is presented. This work includes nodes with modular hardware design low power consumption based on a control resource management board called CoreBoard, specific sensorization SensorBoard The firmware presented as of FreeRTOS parallelised tasks that carry out the resources implement Random Decrement Technique to minimize amount data be transmitted over NB-IoT network in secure way. validated through...
The rise of the Internet Things (IoT) systems and evolution low-power wide-area networks have directly contributed to emergence a new generation structural health monitoring (SHM) based on nondestructive test (NDT) approach. Consequently, this article presents design development synchronous, low-cost, real-time, wireless, consumption SHM system for pre-existing buildings infrastructures, which has been validated structure built in High Middle Ages forming part historical heritage city...
A significant proportion of the world's agricultural production is lost to pests and diseases. To mitigate this problem, an AIoT system for early detection pest disease risks in crops proposed. It presents a based on low-power low-cost sensor nodes that collect environmental data transmit it once day server via NB-IoT network. In addition, use individual, retrainable updatable machine learning algorithms assess risk level crop every 30 min. If detected, are immediately sent. Additionally,...
Particle detector systems require data acquisition (DAQs) as their back-end. This paper presents a new edge-computing DAQ that is capable of handling multiple pixel detectors simultaneously and was designed for particle-tracking experiments. The system the ROC4SENS readout chip, but its control logic can be adapted other detectors. based on system-on-chip FPGA (SoC FPGA), which includes an embedded microprocessor running fully functional Linux system. An application using client–server...