Enhanced Attitude and Altitude Estimation for Indoor Autonomous UAVs

In recent years the use of Unmanned Aerial Vehicles (UAVs) has considerably grown in the civil sectors, due to their high flexibility of use. Currently, two important key points are making them more and more successful in the civil field, namely the decrease of production costs and the increase in navigation accuracy. In this paper, we propose a Kalman filtering-based sensor fusion algorithm, using a low cost navigation platform that contains an inertial measurement unit (IMU), five ultrasonic ranging sensors and an optical flow camera. The aim is to improve navigation in indoor or GPS-denied environments. A multi-rate version of the Extended Kalman Filter is considered to deal with the use of heterogeneous sensors with different sampling rates, and the presence of non-linearities in the model. The effectiveness of the proposed sensor platform is evaluated by means of numerical tests on the dynamic flight simulator of a quadrotor. Results show high precision and robustness of the attitude estimation algorithm, with a reduced computational cost, being ready to be implemented on low-cost platforms.

Printed microfluidic sweat sensing platform for cortisol and glucose detection

An inexpensive microfluidic sweat sensor platform for single-use and continuous biomarker measurements integrated with a synthetic skin for characterization at various sweat rates.

Optimisation of Technological Processes by Solving Inverse Problem through Block-Wise-Transform-Reduction Method Using Open Architecture Sensor Platform

This paper presents an open architecture for a sensor platform for the processing, collection, and image reconstruction from measurement data. This paper focuses on ultrasound tomography in block-wise-transform-reduction image reconstruction. The advantage of the presented solution, which is part of the project “Next-generation industrial tomography platform for process diagnostics and control”, is the ability to analyze spatial data and process it quickly. The developed solution includes industrial tomography, big data, smart sensors, computational intelligence algorithms, and cloud computing. Along with the measurement platform, we validate the methods that incorporate image compression into the reconstruction process, speeding up computation and simplifying the regularisation of solving the inverse tomography problem. The algorithm is based on discrete transformation. This method uses compression on each block of the image separately. According to the experiments, this solution is much more efficient than deterministic methods. A feature of this method is that it can be directly incorporated into the compression process of the reconstructed image. Thus, the proposed solution allows tomographic sensor-based process control, multidimensional industrial process control, and big data analysis.

Comprehensive Review of High Performing Electrochemical Biosensors for Biomedical and Environmental Applications

Since the outbreak of COVID 19 in 2020, being able to detect diseases and chemicals with quick turn-around time becomes ever so needed and important. We have mounted seven different biocatalysts on a sensor platform to examine the performance of this electrochemical sensing system for the detection of different biomolecules/metabolites and environmental important molecules, with such we also compared how this sensing system fares with literature results of similar measurements. The sensor platform constitutes of a layer of bio composite mounted on different electrodes made out of Au, Ag, Pt, and glass carbon; the bio composite is fabricated with polymers and sol-gel Au nanoparticles with or without an extra layer of branching biomolecules. The targeting species for measurements include NH4+, NO3-, CN-, H2O2, and the biomolecules that post specific biomedical functions/identities. In this report, we provide a systematic update of analyses of this sensing system, including the unique identification potentials and sensitivities. This novel sensing system can be a valuable tool in biomedical diagnosis and environmental forensics; in particular the sensor platform used here, any biomedical diagnosis can be conducted with extremely high sensitivity as long as the biomolecules and their antigens are known.